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Does patient dementia limit the use of cardiac catheterization in st-elevated myocardial infarction?

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Title:
Does patient dementia limit the use of cardiac catheterization in st-elevated myocardial infarction?
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Chanti-Ketterl, Marianne
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Subjects / Keywords:
Alzheimer's
STEMI
Elderly
Cardiovascular
Disparity
Dissertations, Academic -- Dean's Office -- Masters -- USF   ( lcsh )
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non-fiction   ( marcgt )

Notes

Abstract:
ABSTRACT: Regardless of age or mental capacity, percutaneous coronary intervention (PCI) is the first line of treatment for ST-elevated myocardial infarction (STEMI). This study evaluates the disparities in the use of diagnostic cardiac catheterization and PCI in STEMI patients with dementia. A retrospective analysis was performed of Florida's comprehensive inpatient surveillance system for the years 2006-2007 with admission diagnosis of STEMI. Logistic regression analysis was used to identify disparities in the use of intervention among all STEMI patients. A total of 8,331 STEMI patients met the inclusion criteria. Of these, 77% were catheterized and of these 67% received PCI. A total of 605 (7.3%) were demented. Patients with dementia were less likely to be catheterized (RR 0.4, 95% CI 0.3-0.5) and less likely to receive PCI within 24 hours (RR 0.5, 95% CI 0.4-0.6). This study concludes that STEMI patients with dementia were much less likely to receive cardiovascular interventions.
Thesis:
Thesis (MSPH)--University of South Florida, 2010.
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Includes bibliographical references.
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by Marianne Chanti-Ketterl.
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ABSTRACT: Regardless of age or mental capacity, percutaneous coronary intervention (PCI) is the first line of treatment for ST-elevated myocardial infarction (STEMI). This study evaluates the disparities in the use of diagnostic cardiac catheterization and PCI in STEMI patients with dementia. A retrospective analysis was performed of Florida's comprehensive inpatient surveillance system for the years 2006-2007 with admission diagnosis of STEMI. Logistic regression analysis was used to identify disparities in the use of intervention among all STEMI patients. A total of 8,331 STEMI patients met the inclusion criteria. Of these, 77% were catheterized and of these 67% received PCI. A total of 605 (7.3%) were demented. Patients with dementia were less likely to be catheterized (RR 0.4, 95% CI 0.3-0.5) and less likely to receive PCI within 24 hours (RR 0.5, 95% CI 0.4-0.6). This study concludes that STEMI patients with dementia were much less likely to receive cardiovascular interventions.
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Does Patient Dementia Limit the Use of Cardiac Catheterization in ST Elevated Myocardial Infarction? b y Marianne Chanti Ketterl A thesis submitted in partial fulfillment of the requirements for the degree of Master of Science in Public Health Department of Epidemiology and Biostatistics College of Public Health University of South Florida Major Professor: Elizabeth Pathak, Ph.D. James A. Mortimer, Ph.D. Wei Wang Ph.D. Date of Approval: October 22 2010 Elderly, Cardiovascular, Disparity Copyright 2010, Marianne Chanti Ketterl

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DEDICATION For Thomas, Calvin, Coco and Nana! Without your constant support I would not have made it this far!

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ACKNOWLEDGEMENTS I would like to first and foremost ackno wledge my advisor Dr. Elizabeth Barnett Pathak for her valuable mentorship throughout the process of this thesis and for allowing me t o work with data supported by her grant in aid from the American Heart Association Much is owed to Dr. James Mortimer for the many insightful consulting sessions and critiques of the manuscript; and my deep gratitude to Dr. Wei Wang for taking the challenge in the last lap and helping me reach the finish line. I am also deeply thankful to Dr. Amy Borenstein for giving me p ermission to use the table of risk factors for Alz and the rich class lessons received. Much is owe d t o George Renner for his expert advice in medical coding I am also very grateful to Dr. Ashok Raj for support ing me through this process a nd proofreading my work and t o Dr. Theresa Beckie for introducing me to the wonderful world of research. L ast but not least I would like to thank the National Institutes of Nursing Research for awarding me the Minority Supplement Grant No. 3 R01 NR007678 04S1 which support ed most of the tuition for the classes needed to fulfill t he requirements for this degree and to the College of Public Health

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at the University of South Florida for supporting the partial presentation of this thesis through the Student Ho norary Award for Research and Practice (SHARP) at the Quality of Care and Outcomes Research in Cardiovascular Disease and Stroke, Scientific Sessions 2010 in Washington, D.C.

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i TABLE OF CONTENTS LIST OF TABLES i v LIST OF FIGURES v i LIST OF ABBREVIATIONS vi i i ABSTRACT x CHAPTER ONE: INTRODUCTION 1 1.1 Main A im of the S tudy 3 1.2 Secondary Aims of the S tudy 4 CHAPTER TWO: LITERATURE REVIEW 7 2.1 Descriptive Epidemiology of Dementia 7 2.1. 1 Pathology of Alzheimer type Dementia 9 2.1.2 Risk Factors f or AD 10 2.1.2.1 Age 10 2.1. 2.2 Genetics 12 2.1. 2.3 Gender and Hormones 13 2.1. 2.4 Education & Socioeconomic Status (SES) 14 2.1. 2.5 Cardiovascular Risk Factors & Cognition 15 2 .1. 2.6 Environmental Factors & Physical Activity 1 6 2.2 Treatment for De mentia 18 2.3 Cardiovascular Epidemiology STEMI 1 8 2.3.1 Statistics for 2009 1 8 2.3.2 STEMI 21 2.3.3 Treatment Guidelines for STEMI and PCI 2 2 2.3. 4 Preventive Treatment 22 2.3. 5 Recommendations for Transportation of STEMI P atient 2 3 2.3. 6 Treatment Guidelines 24 CHAPTER THREE: METHODS 28 3.1 Study Design 28 3.2 Study Population 29 3.2.1 Coding of main variables of interest using ICD 9 CM codes 30 3.2.2 Coding for all other study variables 3 2

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ii 3.2.3 Coding for comorbidity variables 36 3.2.4 Oth er variables of interest to be analyzed 3 9 3.3 Research Questions 39 3.3.1 Main Research Question 39 3.3.2 Secondary Research Questions 40 3.4 Statistical Analysis 4 2 3.4.1 Sample Size and Power Analysis 43 3.4.2 Stratified Analysis 43 3.4.3 Statistical Models 46 3.4.3 .1 Main Research Question Model 46 3.4.3 .2 Secondary Research Question Models 4 8 3.4. 3 .2.1 Secondary question #1 model s 48 3.4.3 .2.2 Secondary question #2 models 50 3.4.3 .2.3 Secondary question #3 models 53 3.4.3 .2.4 Secondary question #4 mo dels 57 3.4.3.3 Sensitivity analysis for definition of dementia 5 9 CHAPTER FOUR: RESULTS 61 4. 0 Descriptive Statistics 61 4.1 Characteristics of the Cohort 61 4.1.1 Age 63 4.1.2 Ethnicity 65 4.1.3 Comorbidity of the Cohort 66 4.1. 4 Source and Days of Admissions 6 8 4.1. 5 Type of Admissions and Payer 6 9 4.1. 6 Length of Hospital Stay 70 4.2 Outcomes for Cardiovascular Interventions 71 4.3 Comorbidities and Use of Interventions 7 6 4.3.1 Hypertension 7 6 4.3.2 Hyperlipidemia 77 4.3.3 Diabetes Type 2 78 4.3.4 Stroke 79 4.3.5 Smoking and Alcohol abuse 80 4.3.6 Congestive Heart Failure 8 2 4.3.7 End Stage Renal Disease and Chronic Kidney Disease 82 4.3.8 Depression 85 4.3.9 Obesity 8 6 4.4 Overview of Descriptive Statistics by Dementia 8 6 4.5 Overview o f Descriptive Statistics by Gender 89 4.6 Multivariate Logistic Regression 90 4.6.1 Main Research Question 90 4.6.2 Secondary Research Questions 9 4 4.6.2.1 Secondary Question #1 9 4

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iii 4.6.2.2 Secondary Question #2 9 6 4.6.2.3 Secondary Question #3 98 4.6 .2.4 Secondary Question #4 102 4.7 Sensitivity Analysis 10 6 CHAPTER FIVE: DISCUSSION 10 8 5.1 Findings 108 5.2 Strengths and Limitations of the Study 11 6 5. 3 Future Research 1 20 5.4 Conclusion 121 REFERENCES 122 APENDICES 1 3 3 Appendix 1. Summary of recommendations from the American College of Cardiology and the American Heart Association for the management of STEMI, pg.e104 13 4 A ppendix 2 App lying Classification of Recommendations and Level of Evidence pg.e87 13 5 A ppendix 3 ICD 9 CM Coding Use f or Comorbity 13 6

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iv LIST OF TABLES T able 4 1 Baseline Characteristics of Elderly STEMI Patients in Florida during 2006 2007. 62 Table 4 2 Ethnic Characteristics of Elderly STEMI Patients in Florida during 2006 2007. 65 Table 4 3 Day of Week of Hospital Admission for STEMI Patients with and without dementia in Florida during 2006 2007. 69 Table 4 4 Length of Hospital Stay for survivor STEMI Patients with and without dementia in Florida during 2006 2007. 70 Table 4 5 Characteristics of h ypertensive STEMI patients in Florida during 2006 2007. 77 Table 4 6 Results of Multivariate Logistic Regression for main research question modeling the probability of diagnostic cardiac catheterization. 93 Table 4 7 Results of Multivariate Logistic Regr ession for secondary research question #2 modeling the probability of having PCI for those patients that received diagnostic cardiac catheterization. 95 Table 4 8 Results of Multivariate Logistic Regression for secondary research question #3 modeling the probability of having CABG for those patients that received diagnostic cardiac catheterization. 97 Table 4 9 Results of Multivariate Logistic Regression models for secondary research question #3 modeling the probability of same day PCI for STEMI patients. 9 9 Table 4 10 Results of Multivariate Logistic Regression models for secondary research question #3 modeling the probability of same day CABG for STEMI patients. 101 Table 4 11 Results of Cox r egression analysis for secondary research question #4 model ing length of hospital STEMI patients. 105

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v Table 4 12 Results of sensitivity analysis evaluating the broad disease. 107

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vi LIST OF FIGURES Figure 2 1 Table modified from Borenstein AR. [Unpublished Lecture Notes on Analysis and Presentation of Results]. Class: Practical Issues in Epidemiology, Summer Semester 2010. University of South Florida; 2010. Accessed with permission, 8/20/2010 ( 1 2 ) 11 Figure 2 2 Algorithm of process of care for STEMI patients as recommended by the AHA/ACC. 2 6 Figure 4 1 Age distribution of Elderly STEMI patie n ts in Florida during 2006 2007. 64 Figure 4 2 Age distribution of Elderly STEMI patients in Florida during 2006 2007 by Dementia Status Percent of STEMI patients is shown for each diagnostic category. 64 Figure 4 3 Prevalence of Comorbidities among STEMI patients by ethnicity. 6 8 Figure 4 4 Percent of STEMI patients who received interventions in Florida during 2006 2007. 71 Figure 4 5 Percent of STEMI patients who received interventions by dementia st atus 72 Figure 4 6 Percent of STEMI patients who received interventions by gender. 72 Figure 4 7 Percent of STEMI patients who received interventions by age category. 73 Figure 4 8 Percent of STEMI patients who received diagnostic cardiac catheteri zati on by age category and dementia status. 74 Figure 4 9 Percent of STEMI patients who received PCI by age category and dementia status. 7 4

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vii Figure 4 10 Percent of STEMI patients who received CABG by age category and dementia 75 Figure 4 1 1 Percent of STEMI patients who received interventions by SES category. 75 Figure 4 1 2 Prevalence of Comorbidities for STEMI patients in Florida by age category. 76 Figure 4 1 3 Percent of smoker and non smoker STEMI patients in Florida during 2006 2007 who received i nterventions. 81 Figure 4 1 4 Prevalence of dementia among STEMI patients with ESRD* and CKD* who received interventions. 8 3 Figure 4 1 5 Prevalence of common risk factors among STEMI patients with e nd stage renal disease (ESRD) or chronic kidney disease ( CKD) in Florida during 2006 2007. 85 Figure 4 1 6 Prevalence of c om mon risk factors for STEMI patients by dementia status 88

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viii LIST OF ABBREVIATION S ACC American College of Cardiology ACS Acute Coronary Syndrome A D AHA American Hear t Association APOE Apolipoprotein E AR Attributable Risk CDC Centers for Disease Control and Prevention CHF Congestive Heart Failure CKD Chronic Kidney D isea s e COPD Chronic Obstructive Pulmonary Disease CVD Cardiovascular disease DM Diabetes Mellitus Type 2 ECG Electrocardiogram EMS Emergency Medical Service ESRD End Stage Renal D isease HLP Hyperlipidemia HTN Hypertension ICD International Classification of Diseases MCI Mild Cognitive Impairment MI Myocardial Infarction OH Chronic Alcohol Abuse

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ix PCI Percuta neous Coronary Intervention PTCA Percutaneous Transluminal Coronary Angioplasty SES Socio Economic Status SMK Smoking Status STRK Stroke STEMI ST Elevated Myocardial Infarction

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x Does Patient Dementia Limit the Use of Cardiac Catheterization in ST Elevated Myocardial Infarction? Marianne Chanti Ketterl ABSTRACT Regardless of age or mental capacity, p ercutaneous coronary intervention (PCI) is the first line of treatment for ST elevated myocardial infarction (STEMI). This study evaluate s the di sparities in the use of diagnostic cardiac c atheterization and PCI in STEMI patients with dementia. A retrospective system for the years 2006 2007 with admission diagnosis of STEMI L ogistic regression analysis was used to identify disparities in the use of intervention among all STEMI patients. A total of 8,3 3 1 STEMI patients met the inclusion criteria. Of these, 77 % were catheterized and of these 67 % received PCI. A total of 605 (7.3 %) were demented. P atients with dementia were less likely to be catheterized (RR 0.4, 95% CI 0.3 0.5) and less likely to receive PCI within 24 hours (RR 0. 5 95% CI 0. 4 0.6 ). This study concludes that STEMI patients with dementia were much less likely to r eceive cardiovascular interventions

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1 CHAPTER ONE INTRODUCTION According to the American Heart Association (AHA), an American will suffer some form of coronary event every 25 seconds. The annual incidence of myocardial infarctions (MI) in the United S tates for 2009 is projected to be 610,000 new attacks and 325,000 recurrent ones ( 3 ) The AHA Get Wit h the Guidelines estimates that about 32% of these MIs are ST Elevated Myocardial Infarctions (STEMIs) ( 3 ) ; about one third of these will result in death within 24 hours of the onset of symptoms ( 4 ) Although the trend in the number of people afflicted by myocardial infarction has steadily decreased in recent years, due in part to advancements in technology and treatment such as the use of Percutaneous Coronary Intervention (PCI), the disparities in care for certain groups have not improved. Studies still report that minorities, the elderly, and women with heart disease are undertreated, less likely to receive PCI, and are more likely to die during hospitalization ( 3 5 7 )

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2 The aging of the population and the rising number of seniors suffering from chronic degenerative diseases have major impacts on public health. The Centers for Disease Control and Prevention estimate that 80% of older Americans are living today with at least one chronic illness ( 6 ) One such growing problem is dementia; a syndrome characterized by progressive mental deterioration. The World Alzheimer Report conducted a systematic review of 147 studies globally and estimated that in the year 2010, 35.6 million people will suffer fr om dementia worldwide ( 8 ) An earlier estimate by Plassman et al. from the Aging, Demographics, and Memory Study (ADAMS) sample, a subcohort from the Health and Retirement Study (HRS) of 856 individuals 70 years or older from different regions in the United States, estimated the prevalence of dementia among peopl e older than 71 at 13.9% which translates to about 3.4 million people in the United States in 2002 and approximately 9.7% for those over 71 years of age for that year ( 9 ) Association suggests (AD) ( 10 ) S tudies show that the prevalence of dementia doubles with every 5 year increase after 65 years of age ( 6 8 11 ) Association report for 2009, from the year 2000 to 2006 the death

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3 sease increased 46.1% in contrast to heart disease, which decreased 11.1% ( 12 ) The health cost of dementia is profound; it not only affects the patient but the entire family and society as well. The economic worldwide expenditure for dementia is $315 billion ( 8 ) In 2005, the direct cost to Medicare and States ( 10 ) The estimated to tal cost of cardiovascular disease for 2009 was $475.3 billion dollars ( 3 ) ; it seems evident that thi s is a public health crisis. Consequently it is imperative to recognize the impact of these two diseases combined and acknowledge the health and socio economic cost to future generations. 1.1 Main Aim of the Study The magnitude of this problem is notewor thy, the increased risk of disability from the combination of dementia and heart disease is large, and the health care costs associated with both pathologies are worrisome for this and future generations. This alarming health care problem prompted me to pe rform a retrospective cohort analysis of the inpatient surveillance data from Florida to determine if there is disparity in the use of diagnostic cardiac catheterization for ST Myocardial Infarction patients with a diagnosis of dementia versus patients wit hout a diagnosis of dementia after controlling for the following patient and hospital factors: age; gender; ethnicity; zip code SES; year of

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4 hospital admission; hour of arrival at the emergency department; source of admission; principal payer and the follo wing comorbidities: hypertension (HTN), diabetes mellitus type 2 (DM), stroke (STRK), hyperlipidemia (HLP), obesity, smoking history (SMK), depression (DEP), e nd stage renal disease (ESRD), chronic kidney disease (CKD), congestive heart failure (CHF), chro nic obstructive pulmonary disease (COPD) and alcohol abuse (OH) 1.2 Secondary Aims of the Study 1. To determine if there is a difference in PCI use between STEMI patients with and without dementia who underwent cardiac catheterization after controlling for the following patient and hospital factors: age; gender; ethnicity; zip code SES; year of hospital admission; hour of arrival at the emergency department; source of admission; principal payer and the following comorbidities: hypertension (HTN), diabetes me llitus type 2 (DM), stroke (STRK), hyperlipidemia (HLP), obesity, smoking history (SMK), depression (DEP), e nd stage renal disease (ESRD), chronic kidney disease (CKD), congestive heart failure (CHF), chronic obstructive pulmonary disease (COPD) and alcoho l abuse (OH). 2. To ascertain if there is a disparity of CABG use between STEMI patients with and without dementia who underwent cardiac catheterization after controlling for the following patient and hospital factors: age; gender;

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5 ethnicity; zip code SES; ye ar of hospital admission; hour of arrival at the emergency department; source of admission; principal payer and the following comorbidities: hypertension (HTN), diabetes mellitus type 2 (DM), stroke (STRK), hyperlipidemia (HLP), obesity, smoking history (S MK), depression (DEP), e nd stage renal disease (ESRD), chronic kidney disease (CKD), congestive heart failure (CHF), chronic obstructive pulmonary disease (COPD) and chronic alcohol abuse (OH). 3. To determine if there is a difference between the days to pro cedure (PCI or CABG) for STEMI patients with and without dementia after controlling for the following patient and hospital factors: age; gender; ethnicity; zip code SES; year of hospital admission; hour of arrival at the emergency department; source of adm ission; principal payer and the following comorbidities: hypertension (HTN), diabetes mellitus type 2 (DM), stroke (STRK), hyperlipidemia (HLP), obesity, smoking history (SMK), depression (DEP), e nd stage renal disease (ESRD), chronic kidney disease (CKD), congestive heart failure (CHF), chronic obstructive pulmonary disease (COPD) and chronic alcohol ab use (OH). 4. To identify if having dementia affects the length of hospital stay for STEMI patients after controlling for the following patient and hospital f actors: age; gender; ethnicity; zip code SES; year of hospital admission; hour of arrival at the emergency department; source of admission; principal

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6 payer and the following comorbidities: hypertension (HTN), diabetes mellitus type 2 (DM), stroke (STRK), h yperlipidemia (HLP), obesity, smoking history (SMK), depression (DEP), end stage renal disease (ESRD), chronic kidney disease (CKD), congestive heart failure (CHF), chronic obstructive pulmonary disease (COPD) and chronic alcohol ab use (OH). Other f actors that will be considered in the analyses include, hospital PCI volume in hospital mortality, day of the week admitted, socio economic status, and any additional procedures that were performed during the hospital stay. This study was approved and exempted by the Institutional Review Board of the University of South Florida on March 19 th 2010.

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7 CHAPTER TWO LITERATURE REVIEW 2.1 Descriptive Epidemiology o f Dementia Dementia is a chronic syndrome caused by a variety of pathologies and conditions that in volve the loss of mental capacity, with emphasis in memory loss, severe enough to interfere with activities of daily living ( 10 13 14 ) It includes memory, learning, orientation, language, comprehension and judgment deterioration ( 8 13 14 ) When mild problems in these areas are observed that do not interfere with daily life, the syndrome is referred to as Mild Cognitive Impairment ( MCI) ( 10 ) Some cases of MCI develop into dementia and others do not; the reason for this is still not clear. Recent studies approximate th e prevalence of dementia in the United States at about 13% ( 9 10 12 ) Studies also confirmed that this prevalence doubles with every 5 year increase in age after age 65 ( 6 8 11 13 ) The most (AD) with approximately 5.3 million Americans affected in 2010 ( 12 ) The

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8 the United States every 70 seconds ( 10 ) and that by the year 2050 this estimate will have decreased to every 33 seconds ( 12 ) Data from the CDC ( 15 ) reported the annual crude death rate of AD at 24.2 per 100,000 population in 2006 the same figure as diabetes mellitus. The age adjusted death rate for AD that year was 22.6 per 100,000 U.S. standard population ( 15 ) a decrease of 1.3% from 2005 to 2006, making it the seventh leading cause of death in the United States in 2006 ( 15 16 ) According to Heron et al., in 2006 there were 72,432 deaths caused by constituted 3% of the total deaths in the United States ( 15 16 ) However underreporting AD on death certificates as cause of death has been well documented and more recent estimates suggest that AD is the fifth leading cause of d eath in Americans aged 65 and older ( 10 ) A meta estimates that the prevalenc e of dementia in North America will increase 63 percent over the next twenty years, mainly due to the demographic shift. Current estimates indicate that there are currently 35.6 ( 8 ) million people worldwide with this syndrome and of these 5.3 ( 10 ) dementia in the United States, of which 5.1 ( 10 ) million are over the age of 65. Two hundred thousand people younger than 65 have what scientists call ( 10 ) and the rest are late ons et dementia.

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9 2.1.1 Pathology of Alzheimer Type Dementia Even though it is known that the underlying cause of most dementias, including AD is genetic, the exact mechanisms are stil l unknown. Dementia is now known to be the result of a combination of pathol ogical disruptions in the brain that end up injuring brain cells, making them loose their functional capacity. Most scientists agree that the pathology of AD may have multiple causes with some factors yet to be discovered. Among the most commonly understo od pathological risk factors to date are genetic inflammation, oxidative stress, hormonal changes and head injury ( 17 18 ) pathological studies are amyloid (neuritic) plaques, neurofibrillary tangles and loss of connection between the cells which lead to cell death ( 13 17 19 21 ) Neuritic plaques are composed mainly of deposits of beta amyloid pro tein which can lead to increased microglia and reactive astrocytes ( 21 ) ; while neurofibrillary tangles, or intraneuronal bundles, are composed mainly of a protein called tau, port system l eading it to fail ( 13 ) F ew epidemiological studies have focus ed on the neuropatholog y of dementia ( 21 22 ) A recent study by Matthews et al. ( 21 ) demonstrated that

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10 neocortical pleuritic plaques accounted for 8% of the attributable risk at death for dementia and 11% neurofibrillary tangles ( 21 ) However although dementia severity seems to correlate better with the tangles than the plaques ( 17 23 ) it has to be noted that tangles are not specific of AD ( 18 ) these can be seen in many other pathologies 2.1.2 Risk Factors for AD Epidemiological studies have demonstrated that A D may be caused by multiple factors; some from early life exposures ( 18 24 ) and others from risk factors pre sent later in life ( 18 25 27 ) Figure 2 1 shows a summary of sease. The middle column shows how these risk factors are associated with brain reserve ( 28 ) and how they modify the clin ical expression of dementia/AD. 2.1.2.1 Age The main risk factor for dementia is age ( 6 8 9 18 21 29 30 ) and it is also the main contributor to the attributable risk at death (18% AR) ( 21 ) The Centers for Disease Control and Prevention (CDC) estimate that by the year 2030, one in five Americans will be over 65 years old ( 6 ) Consequ ently as the population experiences demographic ageing, the prevalence of dementia increases.

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11 Figure 2 1 Table modified from Borenstein AR. [Unpublished Lecture Notes on Analysis and Presentation of Results]. Class: Practical Issues in Epidemiology, Summer Semester 2010. University of South Florida; 2010. Accessed with permission, 8/20/2010 ( 1 2 ) The state of Florida has one of the largest elderly populations in the country. In 200 6 and 2007 18,089,888 ( 31 ) and 18,251,243 ( 32 ) respectively. Of these in 2006 there were 3,037,704 ( 33 ) adults sixty five years and over, and in 2007 there were 60,660 more seniors over 65 than the previous year ( 34 ) In 2009 the population over 65 years of age in Florida totaled 3,195,841 ( 35 ) an increase of 158,137 seniors in 3 years Based on the U.S. Census Bureau statistics, it is estimated that

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12 ( 36 ) or 27.1% ( 37 ) by the year 2030. 2.1. 2.2 Genetics is seen in fewer than 5% of cases ( 10 ) Several studies in twins have confirmed that heritability plays a major role at any age ( 26 38 ) In those over the age of 70 heritability or the proportion of disease explained by genetic inheritance is remarkably high at 79% ( 38 ) Heritability does not differ in gender after controlling for age ( 38 ) One of the most studied genes involved with AD is apolipoprotein E. This gene is involved in the transport of cholesterol in the blood. There are several forms or alleles of the gene, allele e4 is the one that has been found to influence the development of dementia. Recent research confirms that although everyone who inherits one APOE e4 gene is at high risk, those who inherit two genes are at even higher risk ( 10 13 ) However just like all multifactorial conditions, carryi ng the gene does not guarantee that a person will inherit AD. A recent study found that APOE e4 has a stronger effect on women than men but the attributable risk due to APOE decreases with increasing age ( 26 )

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13 However, o disease occurs in people o lder than 60 years old, which is referred to as ( 13 ) The early onset form of the disease seems to be linked to a chromosome 14 (14q24.3), while the late onset and sporadic cases of AD has been linked to apolipoprotein (APOE) on chromosome 19 ( 17 ) 2.1.2.3 Gender and Hormones Alth ough some recent studies show no gender difference in the overall incidence risk of developing dementia ( 9 39 ) some say there is ( 10 25 ) Studies where prevalence has been measured show consistently higher rates for wom en than for men, but this could be explained by longer life spans of the former. Some studies propose that postmenopausal women taking hormone replacement therapy have greater risk of developing dementia type compared to those who do not take h ormone replacement therapy ( 29 ) Women who are APOE e4 carriers are at greater risk of developing AD than men ( 26 ) Much r esearch in men and women ha s focu s ed on the role of hormones estrogen in particular, a n d B asic scien tists have demonstrated the benefits of estroge n on cognition ( 2 ) ; however a

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14 disease in humans has been obscured by poorly design studies ( 2 17 40 ) yielding inconclusive results due to many factors such as the use of different estrogen formulations, patterns and methods use d to measure the biomarker ( 40 ) A lthough controversial, most of these studies conclude that further research is needed with younger volunteers willing to be fol lowed for longer periods of time 2.1. 2.4 Education & Socioeconomic Status (SES) Epidemiological studies have shown that low education is a risk factor for AD and that higher socioeconomic status delays the onset of the disease ( 10 13 17 24 28 ) Th is effect may be modified and/or confounded by many other early life developmental factors, such as parental education, occupation, poor nutrition, and other deprivations in childhood ( 24 ) which may lead to lower brain volume, lower IQ and consequently lower educational achievement ( 28 ) One of the main contributors to AR [attributable risk] at death for dementia was small brain (12%) ( 21 ) T hese observations are consistent with reserve ( 24 28 ) Mortimer proposed that in order to see the clinical expression of AD two conditions must be met: first, propensity to form the pathognomonic AD lesions in the brain and second second, reach ing a critical functional brain volume in which normal cognitive function cannot be

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15 sustained ( 28 ) Although ( 28 ) Although it may be possible to reverse the accumulation of AD pathology because of its strong dependence on inherited genes, controlling for cardiovascular comorbidities may hinder the progression of brain loss through preservation of functiona l brain tissue 2.1. 2.5 Cardiovascular Risk Factors & Cognition W ell known risk factors for dementia include hypertension, hyperlipidemia, and type 2 diabetes mellitus ( 28 30 41 ) The atherosclerotic process is a common link between cardiovascular disease and dementia. Controversy remains as to wheth er pharmacological treatment for cardiovascular disease, such as statin therapy, has the ability to reduce the incidence of dementia. Some studies have not found an association between statin use and AD ( 42 43 ) while others have ( 44 45 ) ; however many que stions remain. Different studies have studied different types of sta tins and this may explain some of the differences in the findings. Statins can be lipophilic (simvastatin, atorvastatin, cervastatin) or hydrophilic (pravastatin, fluvastatin, rosuvastatin) ( 46 ) Different study designs, cross sectional vs. prospective, have been used in different populations; therefore results cannot be easily compared The findings suggest that cross sectional analyses are likely to find an inverse relationship between statin use and dementia, but that prospective do not ( 47 ) Some prospective studies have not seen significant

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16 differences in incidence ( 43 ) ; this may be due in part to the different study designs, indication bias and/or confounding ( 48 ) Haag et al. ( 46 ) studied the different types of statins in relation to AD in a prospective study using the population based Rotterdam Study and surprisingly found that effect sizes were similar for both lipophilic and hydrophilic statins; there was no dose response relationship and a protective effect was obse rved regardless of treatment duration ( 46 ) Overall the literature is inconclusive about preventive treatment with statins needed with a standardized approach to come to any valid conclusions. 2.1.2.6 Environmental Factors & Physical Activity Some environmen tal protective and risk factors for AD occur early in life. Borenstein et al. (2006) reviewed the early life risk factors that may influence the development of AD and found that Down Syndrome and trauma to the head ha s been closely associated with AD in s everal studies; birth weight and sibship size were inversely related to the development of AD ; and the protective effect o f learning multiple languages during childhood had inconclusive results and required further studies ( 24 )

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17 Recent studies are looking closer at the effect of diet in the prevention or delay of AD Based on the same cardiovascular benefit s, diets rich in antioxidants, low saturated fats, a nd high unsaturated fats also seem to be protective of dementia ( 25 49 51 ) S ome s tudies indicate that polypheno ls such as polyphenolic flavanoids found in grapes, apples and wine have neuroprotective properties that slow down the beta amyloid deposition via oxidative stress resistance ( 49 50 ) a nd reduction in toxin build up and chronic inflammation ( 52 ) Other environmental f actors such as smoking have been known to increase the risk of AD ( 53 56 ) S ome studies have reported benefits of smoking at older age but t his may reflect selection bias ( 57 ) Physical activity is known to improve cardiovascular hea lth and thus many studies have linked it to better outcomes on patient cognition ( 58 ) risk and progression of dementia ( 25 59 60 ) Depression has been lin ked with both cardiovascular disease and dementia ( 30 34 41 61 62 ) as well. It is considered a prodromal manifestation of dementia ( 63 ) and has been associated to a two fold increase risk for demen tia ( 34 ) ; recent studies found that this association is not explained by vascular risk factors ( 64 )

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18 2.2 Treatment f or Dementia Unfortunately the majority of dementias are irreversible and do not respond well to treatment A few types of dementia are reve rsible, such as those caused by hormone or vitamin imbalances, depression, and/or drugs, including alcohol. There are several treatments available to try to slow down the progression of AD and control some of the symptoms. Antioxidants; cholinesterase in hibitors such as Donepezil (Aricept), Rivastigmine (Excelon),Galantamine (Razadyne), and Cognex; memantine (Namenda) which is a glutamate inhibitor; and antipsychotics or neuroleptics that can help control behavior in later stages of AD. Antipsychotic s or neuroleptics, antidepressants and anxiolytics may be needed to control some of the symptomatology. 2.3 Cardiovascular Epidemiology STEMI 2.3.1 Statistics f or 2009 According to the American Heart Association Heart Disease & Stroke Statistics 2009 Update, the prevalence of cardiovascular disease (CVD) in the

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19 United States for 2006 was 36.3% (80.0 Million people), which is one in every three adult Americans. Over 38 million of these, or a prevalence of 47.6%, were over the age of 60 ( 3 ) The number of myocardial infarctions in the United States in both men and women in 2006 was 7,900,000 (9.87% of all cardiovascular diseases). O f these, about 29% were STEMIs ( 3 ) In 2006 55% of seniors 65 and ov er had a first listed diagnosis of CHD in short stay hospitals ( 3 ) In people 40 59 years old the pr evalence of cardiovascular disease was roughly 38% and it almost doubled for the age group 60 79 to 73% ( 3 ) Given the increase in the prevalence and incidence of dementia and coronary heart disease with age their combined occurrence increases more than exponentially. In the last several decades the mortality rate from myocardial infarctions has decreas ed gradually, tha nks in part to better treatment. However, the prevalence remains at 3.6% for the year 2006 ( 3 ) Acute coronary syndromes, STEMI in particular, have been a significant public health problem in developed nations for many years. The American Heart Association estimates that about half a million STEMI events occur in

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20 the United States per ye ar and one third of the patients with these will die within 24 hours of the onset of ischemia ( 4 5 ) In the ten year span from 1996 to 2006 the number of cardiac catheterizations decreased by 46,000 annually ( 3 ) Statistics confirm that 1.3 million PCIs, previously refered to as percutaneous transluminal coronary angioplasty (or PTCA) were performed in the United States in 2006 alone and approximately 50% of these were carried out in people over 65 years of a ge. ( 3 ) Although the morbidity as well as the mortality of heart disease has declined in the last d ecades, the use of PCI has increased. Statistics show a 30% increase in PCI procedures from 1996 to 2006 ( 3 ) associated with a staggering economic cost ( 65 ) In 2006 the average fee of a PCI procedure per patient was $48,399 ( 3 ) It is estimated that the direct and indirect total cost of cardiovascular disease in the United States for 200 9 reached $475.3 billion ( 3 ) Despite global treatment improvement in cardiovascular diseases, diffe rences in interventions are still evident and the allocation of PCI is no different. Minorities, women, the elderly and those with low socioeconomic conditions

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21 are still undertreated ( 4 7 66 67 ) Some scientists argue that the overall outcome of STEMI patients despite known disparities, is not yet optimal ( 5 ) This may be in part due to a lack of translation from b ench to practice amongst clinicians. To decrease this gap in knowledge and treatment, the American College of Cardiology (ACC) and the American Heart Association have teamed up to produce reports with the latest scientific evidence, provide guidelines for clinicians to follow when treating STEMI patients ( 68 ) and supply algorithms and tables to help with critical management decisions 2.3.2 STEMI In order to understand the treatment for STEMI, it is necessary to review the basic pathophysiology of this condition. STEMI is a type of transmural acute ischemia that is typically recognized early in the electrocardiogram (ECG) by an ele vation of the ST segment; the more ST segments that are elevated, the more extensive the injury. The location of the ischemia can be documented by the altered leads on the ECG. The diagnosis of STEMI is also supported by the presence of ascending cardiac e nzymes, specifically troponin. The usual cause of a STEMI is a compromise in the blood flow to the myocardium, due most frequently to a rupture of an atherosclerotic plaque; but it can also be caused by other mechanical or dynamic obstructions (vessel spas m) as well as inflammatory mechanisms ( 4 )

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22 2.3.3 Treatment Guidelines for STEMI and PCI Treatmen t for STEMI patients should be based on the recommendations provided in the guidelines for the management of patients with ST elevated myocardial infarctions from the American College of Cardiology Foundation (ACC) and the American Heart Association Task F orce on Practice Guidelines (AHA) ( 4 5 68 69 ) The latest update was provided the last quarter of 2009. 2.3. 4 Preventive Treatment According to the 10 year risk based on the Framingham equation, amongst the elderly, comorbid conditions such as established coro nary heart disease, hypertension, hypercholesterolemia, diabetes and peripheral vascular disease increase the risk of STEMI by over 20% ( 4 ) The ACC/AHA recommends quitting smoking and maintaining a low fat diet rich in fruits, vegetables, whole grains and soluble fibers. Maintaining an ideal weight and an active lifestyle is vital for preventing card iovascular events and adverse outcomes after the onset of the disease ( 3 ) Recommendations for the pr oper treatment of hypertension are emphasized in the elderly, since many research studies indicate that systolic hypertension is predictive of adverse outcomes in this population, and should be treated even with normal diastolic blood pressure ( 4 )

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23 2.3. 5 Recommendations for Transportation of STEMI Patients Modified recommendations from the ACC/AHA no w encourage patients with symptoms suggestive of STEMI to call the emergency medical services (EMS) and seek medical treatment as soon as symptoms begin ( 4 ) Several studies have confirmed the association between the mode of transportation to the hospital and early reperfusion therapy ( 5 68 69 ) Better prognosis is e xpected for those patients who arrive promptly after the onset of sym ptoms to a PCI capable faci lity or who are transferred within 4 hou rs of arriving to a non PCI capable facility to a facility that can perform PCI ( 68 ) See Ap pendix 1. A study by Canto JG, Zalenski RJ, Ornato JP, et al (2002) estimated that 76% of the patients choose alternative modes of transportation to the emergency department instead of using EMS ( 4 ) Other studies indicate longer waiting times if the patient does not arrive to the emergency department through EMS, especially if the patient is elderl y or a female ( 4 ) The 2009 Update from the ACC/AHA for the triage and transfer for PCI newly rec ommends that each community develop a system of care for STEMI patients with specific protocols for the management and destination of those patients who are primary PCI candidates and are not eligible for fibrinolytic drugs and/or are in cardiogenic shock. It is advised that when patients arrive

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24 at non PCI capable centers that they receive fibrinolytic therapy as the main source of reperfusion and be transferred, prepared with antithrombotic medication (an anticoagulant plus an antiplatelet), as soon as pos sible to a PCI capable facility 2.3. 6 Treatment Guidelines Treatment should be instated as soon as possible but sometimes patient or systemic factors delay the process. Patient factors may include refusal from the patient ( 5 ) ; and although systemic factors delay the process they do not result in exclusion of treatment. Guidelines from 2004 2009 provide evide nce from recent clinical trials of the benefits of timing in treatment execution for STEMI patients ( 4 5 68 69 ) Studies show a higher adjusted risk of in hospital mortality in any delays to reperfusion after arrival to the hospital. Figure 2 2 shows an algori thm for the recommended process of care for STEMI patients. Primary PCI is indicated as Class I if immediately available within the first 12 hours of the onset of symptoms or 90 minutes or less after ar rival to a PCI capable facility for those patients th at present with Acute Coronary Syndrome (ACS) and ST segment elevation in the electrocardiogram in leads V7 to V9 due to left circumflex arterial occlusion ( 5 ) Primary PCI is

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25 considered Class II a for selected STEMI patients older than 75 years of age. See appendix 2 for complete description of classifications. Aside from primary PCI, it is important to differe ntiate the other types of PCI offered. Facilitated PCI refers to access to the procedure after the administration of pharmacological treatment such as a high dose heparin, platelet GP IIb/IIIa inhibitors, fibrinolytic therapy or a combination of the last t wo, which act as facilitators for the PCI ( 69 ) The advantage of this method is that it provides shorter times to reperfusion, better recovery, fewer adverse events and better survival rates ( 69 ) Fibrinolyti c therapy works best for those patients that present early to the hospital after the onset of symptoms; while sometimes the clinical and graphic signs resolve with fibrinolytic therapy, most of the time this is not the case. Thus after 90 minutes of fibrin olytic therapy and a failed reperfusion, a rescue PCI is to be performed. Rescue PCI has been indicated given a combination of clinical and electrocardiographic traces that indicate an infarct artery that has not reperfused, such as a maintained ST segmen t elevated ( 68 )

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26 Figure 2 2 Algorithm of process of care for STEMI patients as recommended by the AHA/ACC. The recent guidelin e update in 2009 modified the previous recommendation in the triage of patients. It is now suggested that rescue PCI should be offered to any eligible STEMI patient, regardless of age, since it offers the greatest benefit when initiated right after the on set of ischemic symptoms ( 68 ) Therefore elderly people that have no contraindication should be offered the same opportunity of re ceiving PCI. The recommendation does STEMI PCI Capable Facility Catheterization (within 90 minutes) Patient is prepared with antithrombotics (anticoagulant + antiplatelet ) Diagnostic Angioplasty 3 Possible Treatments: 1. Medical/Drug therapy 2. PCI 3. CABG Non PCI Capable Facility Fibrinolisis (door to needle within 30 min) Transfer to PCI Capable Facility

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27 not mention any contraindications for PCI because of mental or cognitive status. When faced with a less than optimal scenario, such as great distances from a PCI capable facility, emphasis is placed in traditional est ablished fibrinolytic adrenoceptor blocking agents, vasodilator therapies, angiotensin converting enzyme (ACE) inhibitors, and cholesterol lowering therapy ( 4 )

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28 CHAPTER THREE METHODS 3.1 Study Design comprehensi ve inpatient surveillance system for the years 2006 and 2007. These data includes complete coverage for all 1393 zip code areas or 67 counties in the state of Florida for the reference years. Hospital discharge data were analyzed to determine if there is a disparity in the use of cardiac catheterization in patients 65 years of age or older with ST Elevation Myocardial Infarction (STEMI) with and without a diagnosis of dementia at high volume PCI Florida hospitals. Although PCI is the first line of treatme nt for patients with STEMI, individuals receiving this treatment must first undergo cardiac catherization. To determine where in the sequence, the possible disparity between persons with and without dementia in usage of PCI occurs, the initial analysis was performed based on those that undergo cardiac catheterization to determine if indeed a PCI is the treatment of choice. Some patients that go through

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29 cardiac catheterization may require CABG instead. Therefore secondary analyses were carried out to detect any possible disparities in the use of PCI or CABG in those patients with cardiac catheterization with and without dementia. To measure any gender disparities, a separate model was done to separate the cohort by gender. 3.2 Study Population Subjects fo r the study were identified using the International Classification of Diseases (ICD), Ninth Revision, Clinical Modification (ICD 9 CM) codes. The ICD Clinical Modification is the official coding system used in the United States to code diagnoses and proced ures when a patient receives services at a hospital or clinic and is used to classify mortality as well ( 70 ) The database under study contains ten primary codes and up to 30 secondary codes u sing the referenced format. There are over 200 hospitals in Florida ( 66 ) but not all have the same capacity to perform Percutaneous Coronary Interventions (PCI). In order to reduce confounding by the volume PCIs were considered in the statistical model s High volume PCI hospital were identified ac cording to the American College of Cardiology and

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30 the American Heart Association practice guidelines for PCI ( 71 72 ) as those that perform over 400 PCIs annually The study population consists of men and women 65 years of age and over admitted to a high volume PCI Florida hospital during 2 006 and 2007 with a primary diagnosis of STEMI. Patients younger than 65 years of age were excluded given that dementia is prominent in the older cohort. 3.2.1 Coding of main variables of interest using ICD 9 CM codes Subjects for the cohort were identifi ed using the following ICD 9 CM codes: Acute myocardial infarction: 410.0 410.6, and 410.8 with a fifth digit of 0 or 1. The fifth digit describes the episode of care; in this case 0 represents episode of care unspecified and 1 represents initial episode of care. In order to detect any disparity of care in interventions, the following procedural codes were used: Catheterization codes: 37.21, 32.22, 37.23 PCI: procedure codes: 00.66, 36.01, 36.02, and 36.05.

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31 CABG codes: 36.10, 36.11, 36.12, 36.13, 36.14, 36.15, 36.16, 36.17, 36.18, 36.19 without additional surgeries such as valvular or aortic, and without PCI were used. Intervention: this variable was created to account for any PCI or CABG procedure performed on a patient. From the reference study popula tion, a secondary code was extracted to categorize those with a diagnosis of dementia. This comparison group was identified using the following codes for dementia: Persistent Mental Disorders: 294.0, 294.1, 294.8, 294.9 Other cerebral degenerations: 331. 0 331.2, 331.7, 331.81, 331.82, 331.89, 331.9 It is important to note that code 331.83 was excluded from the analysis because it represents mild cognitive impairment and these patients can be fully functional. Memory loss and altered mental status: 780.93, 780.97 Senility without mention of dementia: 797. This code was included because it is commonly used as a synonym for loss of mental deterioration due to aging.

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32 3.2. 2 Coding for all other study variables Additional variables included in this study were as follows: Socio demographic factors Gender : Male, Female (male was used as the reference category) Age : this variable was first analyzed as a continuous variable and then categorized as follows: (used as reference category) Ethnicity : American Indian or Alaska Native; Asian or Pacific Islander; Black or African American; White; White Hispanic; Black Hispa nic; Other (if none of the ones mentioned before); or No Response. Based on previous study findings ( 12 ) ethnicity was summarized for analysis under three categories: white non Hispanic (used as reference category) ; black non Hispanic/African American; and Hispanic/Other. Zip code S ocio E conomic S tatus (SES) measured by proxy and was calculated as follows:

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33 Individual income was obtained from individual adjusted gross income reported on the income tax returns from the s Individual Master File system for the year 2006 which includes records for every 1040, 1040A, and 1040EZ for reporting zip code area of residence) ( 73 ) The mean income reported for a given zip code was used in the calculation for SE S for that particular zip code. On July 1 st ( 74 ) was 18,089,888 According to the cumulative estimate of population change for 2006, Florida had a 13.2% change from 2000 to 2006 ( 40 ) This perc ent change was used to calculate the population change for each zip code reported in the year 2000 for Florida It is important to note that zip codes with census data used in this analysis were only those that participated in the Census 2000. Given that p er capita income is the mo st accurate method of measuring income in a population, the formula used to calculate it follows: [Average adjusted g ross i ncome for zip code / (Population reported for that income in 2000 + 13.2% population growth ( 75 ) )]*1000

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34 Tax brackets from government statistics ( 76 ) for the year 2006 were : Tax bracket 10% = less than $7750 Tax bracket 15% = i ncome greater or equal to $ 7550 and less than $ 30650 Tax bracket 25% = income greater or equal to $30650 and less than $74200 Tax bracket 28% = income greater or equal to $74200 or less than $154800 Tax bracket 33% = income greater or equal to $154800 or less than $336550 Tax bracket 35% = income greater or equal to $336550 In order to translate the above information into a categorical zip code SES applicable to the cohort under study the following categories were constructed: a) If tax bracket is in the 10% or less, it is considered zip code SES category 1 = income less than $7,750

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35 b) If tax bracket is in the 15% it is considered zip code SES category 2 = income greater or equal to $7,550 but less than $30,650 c) If tax bracket is greater than 25% then zip code SE S category is 3 = Principal Payer will be categorized as: (1) Medicare (HMO or PPO); (2) Self Pay, Underinsured/Charity; and (3) Other (includes Medicaid HMO; commercial Insurance (includes all types: HMO, ate or Local Government). Category 3 was used as the reference category. Source of Admission : categories include (1) Outside the hospital p hysician Referral; (2)Transfer from a Skilled Nursing Facility; (3)ER Physician Recommendation; (4) Court/Law Enforc ement; and (5) Information not available. Patients transferred from a hospital were not analyzed nor those who were transfers from other facility. Given the low number of some of these categories, the variable was re categorized into the following three: 1. R eferral from physician outside the hospital 2. Recommendation from emergency room physician. 3. Other (this category included: t ransfer from a s killed nu rsing f acility; c ourt/ l aw e nforcement; and i nformation

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36 not available ). This category was used as reference c ategory. Admission Type : (1) Emergency; (2) Urgent; (3) Elective; or (4) Trauma. Hour of Arrival : used first as a continuous variable and then categorized as follows : 00:00 06:00 = Early Morning 07:00 12:00 = Morning (used as reference) 13:00 17:00 = Afternoon 18:00 23:00 = Night Weekday: this variable represents the day of the week the patient was admitted to the hospital (Monday Sunday). 3.2. 3 Coding for comorbidity variables Comorbidity: conditions measured at time of admission using the 30 secondary ICD 9 CM diagnosis codes in the database. Individual analysis were performed for comorbid risk factors listed under the AHA guidelines for

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37 Alzheim ( 3 12 ) with the following ICD 9 CM codes: Hypertension : 401.0, 401.1, 401.9, 403, 403.0, 403.01, 403.10, 403.11, 403.9, 403.90, 403.91 Diabetes : 250.00, 250.01, 250.02, 250.03, 250.10, 250.11, 250.12, 250.13, 250.20, 250.21, 250.22, 250.23, 250.30, 250.31, 250.32, 250.33, 250.40, 250.41, 250.42, 250.43, 250.50, 250.51 250.52, 250.53, 250.60, 250.61, 250.62, 250.63, 250.70, 250.71, 250.72, 250.73, 250.80, 250.81, 250.82, 250.83, 250.9, V58.67 Stroke : 430, 431, 432.0, 432.1, 432.9, 433.00, 433.01, 433.10, 433.11, 433.20, 433.21, 433.30, 433.31, 433.80, 433.81, 433.90, 4 33.91, 434.00, 434.01, 434.10, 434.11, 434.90, 434.91, 435, 435.1, 435.2, 435.3, 435.8, 435.9, 436, 997.02, V12.54 Hyperlipidemia : 272, 272.0, 272.1, 272.2, 272.3, 272.4 Obesity : 278.00 Cigarette smoking : 305.1 Chronic Alcohol Abu se : 303, 303.00, 303.01, 3 03.02, 303.03, 303.9, 303.90, 303.91, 303.92, 303.93, V11.3, V79.1 Depression : V79.0, 300.4, 311, 296.2, 296.20, 296.21, 296.22, 296.23, 296.24, 296.25, 296.26, 296.3, 296.30, 296.31, 296.32,

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38 296.33, 296.34, 296.35, 296.36, 296.5, 296.50, 296.51, 296.52, 296.53, 296.54, 296.55, 296.56 Chronic Kidney Disease : 404, 404.0, 404.01, 404.02, 404.03, 404.9, 404.90, 404.91, 404.92, 404.93, 403, 403.00, 403.01, 403.10, 403.11, 403.9, 403.90, 403.91, 585, 585.1, 585.2, 585.3, 585.4, 585.5, 585.9 End Stage Renal Dise ase: 585.6 Congestive Heart Failure : 402.0, 402.00, 402.01, 402.1, 402.10, 402.11, 402.9, 402.90, 402.91, 404, 404.0, 404.01, 404.02, 404.03, 404.1, 404.10, 404.11, 404.12, 404.13, 404.9, 404.90, 404.91, 404.92, 404.93, 428.0, 428.1, 428.9 Chronic Obstruct ive Pulmonary Disease: 490, 491, 491.0, 491.1, 491.2, 491.20, 491.21, 491.22, 492, 492.0, 492.8, 493, 493.0, 493.00, 493.01, 493.02, 493.1, 493.10, 493.11, 493.12, 493.2, 493.20, 493.21, 493.22, 493.9, 493.90, 493.91, 493.12, 494, 494.0, 494.1, 495, 495.0, 495.1, 495.2, 495.3, 495.4, 495.5, 495.6, 495.7, 495.8, 495.9, 496 Note: Heart disease is listed as a risk factor for dementia, thus the nature of this data.

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39 3.2. 4 Other varia bles of interest to be analyzed Days to procedure (PCI and/or CABG): to proper ly d etermine the days to procedure it was assumed that if the principal procedure or other procedure had a PCI or CABG code greater than or equal to 3 and less than or equal to 1 the procedure took place within 24 hours thus creating Length of hospital stay : this variable represents the number of days from when the patient was admitted to discharge. To analyze this variable those patients that passed away while hospi talized were excluded from the analysis 3.3 RESEARCH QUESTIO NS 3.3.1 Main Research Question Is there disparity in the use of cardiac catheterization for ST Myocardial Infarction patients with a diagnosis of dementia versus patients without a diagnosis of dementia after controlling for the foll owing patient and hospital factors: age; gender; ethnicity; zip code SES; year of hospital admission; hour of arrival at the emergency department; source of admission; principal payer and the following comorbidities: hypertension (HTN), diabetes mellitus t ype 2 (DM), stroke (STRK), hyperlipidemia (HLP), obesity, smoking history (SMK), depression (DEP), end stage renal disease (ESRD), chronic kidney

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40 disease (CKD), congestive heart failure (CHF), chronic obstructive pulmonary disease (COPD) and chronic alcoho l ab use (OH) ? 3.3.2 Secondary Research Questions 1. Is there is a difference in PCI use between STEMI patients with and without dementia who underwent cardiac catheterization after controlling for the following patient and hospital factors: age; gender; eth nicity; zip code SES; year of hospital admission; hour of arrival at the emergency department; source of admission; principal payer and the following comorbidities: hypertension (HTN), diabetes mellitus type 2 (DM), stroke (STRK), hyperlipidemia (HLP), obe sity, smoking history (SMK), depression (DEP), end stage renal disease (ESRD), chronic kidney disease (CKD), congestive heart failure (CHF), chronic obstructive pulmonary disease (COPD) and chronic ab use (OH) ? 2. Is there is a disparity of CABG use between S TEMI patients with and without dementia who underwent cardiac catheterization after controlling for the following patient and hospital factors: age; gender; ethnicity; zip code SES; year of hospital admission; hour of arrival at the emergency department; s ource of admission; principal payer and the following comorbidities: hypertension (HTN), diabetes mellitus type 2 (DM), stroke (STRK), hyperlipidemia (HLP), obesity, smoking history (SMK), depression

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41 (DEP), end stage renal disease (ESRD), chronic kidney di sease (CKD), congestive heart failure (CHF), chronic obstructive pulmonary disease (COP D) and chronic alcohol ab use (OH)? 3. Is there is a difference between the days to procedure (PCI or CABG) for STEMI patients with and without dementia after controlling for the following patient and hospital factors: age; gender; ethnicity; zip code SES; year of hospital admission; hour of arrival at the emergency department; source of admission; principal payer and the following comorbidities: hypertension (HTN), diabete s mellitus type 2 (DM), stroke (STRK), hyperlipidemia (HLP), obesity, smoking history (SMK), depression (DEP), end stage renal disease (ESRD), chronic kidney disease (CKD), congestive heart failure (CHF), chronic obstructive pulmonary disease (COPD) and ch ronic ab use (OH) ? 4. Does having dementia affects the length of h ospital stay for STEMI patients after controlling for the following patient and hospital factors: age; gender; ethnicity; zip code SES; year of hospital admission; hour of arrival at the emerg ency department; source of admission; principal payer and the following comorbidities: hypertension (HTN), diabetes mellitus type 2 (DM), stroke (STRK), hyperlipidemia (HLP), obesity, smoking history (SMK), depression (DEP), end stage renal disease

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42 (ESRD), chronic kidney disease (CKD), congestive heart failure (CHF), chronic obstructive pulmonary disease (COP D) and chronic ab use (OH)? 3.4 Statistical Analysis Data analysis was performed using Statistical Analysis Software (SAS) version 9.1.2 software prog ram. De identified data were provided by year in separate SAS files and merged to one main data set containing all necessary information for the analysis for the years 2006 and 2007. Before starting the study, a feasibility sample size was performed usin g a PS program that works in Microsoft Windows operating system ( 77 ) Sample size and power analysis wa s based on study by Sloan et al. (2004) ( 78 ) Based on the literature review ( 78 80 ) it is expected that patients with a diagnosis of dementia have a lower probability of receiving cardiac catheterization. The assumption is that the failure rate is 0.15 or 15% of non demented STEMIs receiv ing PCI. T he risk ratio of PCI in people with ratio of non demented patients with STEMI, which are treated as the unexposed to dement ed patients with STEMI, considered as the exposed.

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43 of unexposed to exposed subjects, and the relative risk of failure for exposed T herefore, given that the PS program used assumes two tailed tests, alpha will be set at 0.1 corresponding to alpha 0.05 for a one tailed test. Since for this analysis the outcome can only take one of two values, received procedure or not, an uncorrected c hi square test was performed to evaluate the null hypothesis. 3.4.1 Sample Size and Power Analysis This study was planned as a retrospective cohort study with 21.06 unexposed subjects per group. Prior data ( 78 ) indicate that the failure rate among unexposed is 0.15. If the true relative risk of failure for exposed subjects relative t o unexposed is 0.267, we need to study 49 exposed subjects and 1031.94 unexposed subjects to be able to reject the null hypothesis that this relative risk equals 1 with probability (power) 0.8. The Type I error probability associated with this test of this null hypothesis is 0.1. 3.4.2 Stratified Analysis Baseline characteristics of the population were first analyzed by tabulating the frequency of admission characteristics and comorbid conditions.

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44 Stratified by analyses by dementia status were carried ou t to identify potential confounders among the following variables: 1. Age: Multiple meta analysis studies have demonstrated the link between age and dementia ( 8 30 ) and between age and heart disease ( 3 ) 2. Gender: Some studies have demonstrated that females are more likely to suffer from dementia ( 29 30 ) and more males than females seem to have PCI ( 66 ) 3. Ethnicity: Black patients are known to receive PCI less often than whites ( 7 66 ) 4. S ocio economic status: there is no conclusive data on whether the prevalence and i ncidence of dementia is higher in low socioeconomic environments, the incidence of PCI has been found to be lower for those with a disadvantaged SES class ( 67 ) 5. Year of hospital admission : to determine if there was improvement of care over time 6. Hour of arrival at the emergency d epartment: Many studies indicate the association of arrival time and possible PCI ( 68 ) 7. Source of Admission: Patients who arrive a t the hospital using the emergency medical services have better survival rates ( 4 )

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45 8. Principal Paye r: patients with commercial insurance seem to receive better care than Medicare beneficiaries ( 81 ) 9. Hospital PCI volume category: Hospitals with high volume PCI tend to have less disparity of care in PCI ( 71 ) 10. Comorbidities of importance in the association between dementia and STEMI were: h ypertension ; h yperlipidemia ; o besity; smoking s tatus; c hronic alcohol abuse ; d iabetes m ellitus type II ; d epression ; s troke; end s tage r enal d is ease; c hronic k idney d isease; c ongestive h eart f ailure; c hroni c o bstructive p ulmonary d isease. Patients were also stratified by gender and according to the presence of each of the previously mentioned risk factors: hypertension, hyperlipidemia, obesity, diabetes, stroke, cigarette smoking, alcohol abuse, depression, chronic kidney disease (CKD) end stage renal disease (ESRD) congestive heart failure (CHF) and chronic obstructive pulmonary disease (COPD). Chi square tests were used for discrete variables and t tests for continuous variables when comparing those with and without a diagnosis of dementia. Age adjusted relative r isks and 95% confidence intervals were estimated when comparing the groups using logistic regression procedures.

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46 Univariate models were performed to look at the distribution of continuous risk factors for STEMI and dementia (age, length of hospital stay a nd SES ) as it provides the most descriptive statistics. 3.4. 3 Statistical Models 3.4. 3 1 Main Research Question Model To address the main research question, multivariate logistic regression analysis was performed to examine any differences in the use of diagnostic cardiac catheterization for STEMI patients with and without a diagnosis of dementia: Model 1 : Logit=Log (p x /(1 p x 1 dementia where p x is the probability of the x th STEMI patient re ceiving diagnostic cardiac catheterization The second model used adjust s for all potential confounders and provides data related to the independent effects of each variable: age ca tegory,

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47 gender, ethnicity, zip code socio economic status (SES), year of hospitalization, hour of arrival, source of admission, type of payer, and the following comorbidities: hypertension (HTN), diabetes mellitus type 2 (DM), stroke (STRK), hyperlipidemia (HLP), obesity, smoking history (SMK), depression (DEP), end stage renal disease (ESRD), chronic kidney disease (CKD), congestive heart failure (CHF), chronic obstructive pulmonary disease (COPD) and chronic alcohol abuse (OH). Model 2 : Log [p x /(1 p x )]= 0 + 1 dementia + 2 age category + 3 gender + 4 ethnicity + 5 SES + 6 year of admission + 7 hour of arrival + 8 source of admission + 9 payer + 1 0 HTN + 1 1 DM + 1 2 STRK + 1 3 HLP + 1 4 obesity + 1 5 SMK + 16 OH + 1 7 DEP + 1 8 ESRD + 19 CKD + 2 0 CHF + 2 1 COPD where p x is the probability of the x th STEMI patient receiving diagnostic cardiac catheterization. M odel three was done not adjust ing for zip code SES but adjust ed for all other potential confounders and provided data related to the independent effects of each variable: age category, gender, ethnicity, year of hospitalization, hour of arrival, source of admission, type of payer, and the following comorbidities: hypertension (HTN), diabetes mellitus type 2 (DM), stroke (STRK), hyperlipidemia (HLP), obesity, smoking history (SMK),

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48 depression (DEP), end stage renal disease (ESRD), chronic kidney disease (CKD), congestive heart failure (CHF), chronic obstructive pulmonary disease (COPD) and chronic alcohol abuse (OH). Model 3 : Log [p x /(1 p x )]= 0 + 1 dementia + 2 age category + 3 gender + 4 ethnicity + 5 year of admission + 6 hour of arrival + 7 source of admission + 8 payer + 9 HTN + 1 0 DM + 1 1 STRK + 12 HLP + 1 3 obesity + 1 4 SMK + 15 OH + 1 6 DEP + 1 7 ESRD + 18 CKD + 19 CHF + 2 0 COPD where p x is the probabi lity of the x th STEMI patient receiving diagnostic cardiac catheterization. 3.4. 3 2 Secondary Research Question Models 3.4. 3 .2.1 Secondary question #1 model s To address the first secondary question, model s four to six w ere run to examine any differences in the use of PCI for STEMI patients who underwent diagnostic cardiac catheterization with and without a diagnosis of dementia Model 4 : Logit=Log (p x /(1 p x 1 dementia

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49 where p x is the probability of the x th cardiac catheterized STEMI patient receiv ing P CI M odel five was done adjust ing for all potential confounders and provides data related to the independent effects of each variable: age category, gender, ethnicity, zip code socio economic status (SES), year of hospitalization, hour of arrival, so urce of admission, type of payer, and the following comorbidities: hypertension (HTN), diabetes mellitus type 2 (DM), stroke (STRK), hyperlipidemia (HLP), obesity, smoking history (SMK), depression (DEP), end stage renal disease (ESRD), chronic kidney dise ase (CKD), congestive heart failure (CHF), chronic obstructive pulmonary disease (COPD) and chronic alcohol abuse (OH). Model 5 : Log [p x /(1 p x )]= 0 + 1 dementia + 2 age category + 3 gender + 4 ethnicity + 5 SES + 6 year of admission + 7 hour of arrival + 8 source of admission + 9 payer + 1 0 HTN + 1 1 DM + 1 2 STRK + 1 3 HLP + 1 4 obesity + 1 5 SMK + 16 OH + 1 7 DEP + 1 8 ESRD + 19 CKD + 2 0 CHF + 2 1 COPD where p x is the probability of the x th cardiac catheterized STEMI patient receiving PCI.

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50 M odel six adjust ed for all other potential confounders except zip code SES and provided data related to the independent effects of each variable: age category, gender, ethnicity, year of hospitalization, hour of arrival, source of admission, type of payer, and the following comorbidities: hypertension (HTN), diabetes mellitus type 2 (DM), stroke (STRK), hyperlipidemia (HLP), obesity, smoking history (SMK), depression (DEP), end stage renal disease (ESRD), chronic kidney disease (CKD), congestive heart failure (CHF), chronic obstructive pulmonary disease (COPD) and chronic alcohol abuse (OH). Model six : Log [p x /(1 p x )]= 0 + 1 dementia + 2 age category + 3 gender + 4 ethnicity + 5 year of admission + 6 hour of arrival + 7 source of admission + 8 payer + 9 HTN + 1 0 DM + 1 1 S TRK + 12 HLP + 1 3 obesity + 1 4 SMK + 15 OH + 1 6 DEP + 1 7 ESRD + 18 CKD + 19 CHF + 2 0 COPD where p x is the probability of the x th cardiac catheterized STEMI patient receiving PCI. 3.4. 3 .2.2 Secondary question #2 models To address the second secondary ques tion model seven was run to examine any disparity in the use of CABG for STEMI patients who underwent

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51 diagnostic cardiac catheterization with and without a diagnosis of dementia as follows: Model 7 : Logit=Log (p x /(1 p x 1 dementia where p x is the pr obability of the x th cardiac catheterized STEMI patient receiving CABG. M odel eight was done adjust ing for all potential confounders and provided data regarding the independent effects of each variable: age category, gender, ethnicity, socio economic stat us (SES), year of hospitalization, hour of arrival, source of admission, type of payer, and the following comorbidities: hypertension (HTN), diabetes mellitus type 2 (DM), stroke (STRK), hyperlipidemia (HLP), obesity, smoking history (SMK), depression (DEP ), end stage renal disease (ESRD), chronic kidney disease (CKD), congestive heart failure (CHF), chronic obstructive pulmonary disease (COPD) and chronic alcohol abuse (OH). Model 8 : Log [p x /(1 p x )]= 0 + 1 dementia + 2 age category + 3 gender + 4 ethnic ity + 5 SES + 6 year of admission + 7 hour of arrival + 8 source of admission +

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52 9 payer + 1 0 HTN + 1 1 DM + 1 2 STRK + 1 3 HLP + 1 4 obesity + 1 5 SMK + 16 OH + 1 7 DEP + 1 8 ESRD + 19 CKD + 2 0 CHF + 2 1 COPD where p x is the probability of the x th cardiac cathete rized STEMI patient receiving CABG. M odel nine did not adjust for zip code SES but it did adjust for all other potential confounders and provided data regarding the independent effects of each variable: age category, gender, ethnicity, year of hospitaliza tion, hour of arrival, source of admission, type of payer, and the following comorbidities: hypertension (HTN), diabetes mellitus type 2 (DM), stroke (STRK), hyperlipidemia (HLP), obesity, smoking history (SMK), depression (DEP), end stage renal disease (E SRD), chronic kidney disease (CKD), congestive heart failure (CHF), chronic obstructive pulmonary disease (COPD) and chronic alcohol abuse (OH). Model 9 : Log [p x /(1 p x )]= 0 + 1 dementia + 2 age category + 3 gender + 4 ethnicity + 5 year of admission + 6 hour of arrival + 7 source of admission + 8 payer + 9 HTN + 1 0 DM + 1 1 STRK + 12 HLP + 1 3 obesity + 1 4 SMK + 15 OH + 1 6 DEP + 1 7 ESRD + 18 CKD + 19 CHF + 2 0 COPD

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53 where p x is the probability of the x th cardiac catheterized STEMI patient receiving CABG 3.4. 3 .2.3 Secondary question #3 models In order t o determine if there was a difference between the days to procedure for either PCI or CABG, for STEMI patients with and without dementia models ten to fifteen were run The variable days to procedure was d ichotomized as performed within 24 hours or else. Model 10 : Logit=Log (p x /(1 p x 1 dementia where p x is the probability of x th days to PCI for cardiac catheterized STEMI patient. M odel eleven was done adjust ing for all potential confounders and provided data regarding the independent effects of each variable: age category, gen der, ethnicity, socio economic status (SES), year of hospitalization, hour of arrival, source of admission, type of payer, and the following comorbidities: hypertension (HTN), diabetes mellitus type 2 (DM), stroke (STRK), hyperlipidemia (HLP), obesity, smo king history (SMK), depression

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54 (DEP), end stage renal disease (ESRD), chronic kidney disease (CKD), congestive heart failure (CHF), chronic obstructive pulmonary disease (COPD) and chronic alcohol abuse (OH). Model 11 : Log [p x /(1 p x )]= 0 + 1 dementia + 2 age category + 3 gender + 4 ethnicity + 5 SES + 6 year of admission + 7 hour of arrival + 8 source of admission + 9 payer + 1 0 HTN + 1 1 DM + 1 2 STRK + 1 3 HLP + 1 4 obesity + 1 5 SMK + 16 OH + 1 7 DEP + 1 8 ESRD + 19 CKD + 2 0 CHF + 2 1 COPD where p x is the pr obability of x th days to PCI for cardiac catheterized STEMI patient. M odel twelve did not adjust for zip code SES but it did adjust for all other potential confounders and provided data regarding the independent effects of each variable: age category, gen der, ethnicity, year of hospitalization, hour of arrival, source of admission, type of payer, and the following comorbidities: hypertension (HTN), diabetes mellitus type 2 (DM), stroke (STRK), hyperlipidemia (HLP), obesity, smoking history (SMK), depressio n (DEP), end stage renal disease (ESRD), chronic kidney disease (CKD), congestive heart failure (CHF), chronic obstructive pulmonary disease (COPD) and chronic alcohol abuse (OH).

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55 Model 12 : Log [p x /(1 p x )]= 0 + 1 dementia + 2 age category + 3 gender + 4 ethnicity + 5 year of admission + 6 hour of arrival + 7 source of admission + 8 payer + 9 HTN + 1 0 DM + 1 1 STRK + 12 HLP + 1 3 obesity + 1 4 SMK + 15 OH + 1 6 DEP + 1 7 ESRD + 18 CKD + 19 CHF + 2 0 COPD where p x is the probability of x th days to PCI for cardi ac catheterized STEMI patient. Model thirteen is based on model ten but here the probability of days to CABG is being measured. Model 13 : Logit=Log (p x /(1 p x 1 dementia where p x is the probability of x th days to CABG for cardiac catheterized STEMI patient. M odel fourteen was done adjust ing for all potential confounders and provided data regarding the independent effects of each variable: age category, gender, ethnicity, zip code socio economic status (SES), year of hospitalization, hour of arrival, source of admission, type of payer, and the

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56 following comorbidities: hypertension (HTN), diabetes mellitus type 2 (DM), stroke (STRK), hyperlipidemia (HLP), obesity, smoking history (SMK), depression (DEP), end stage renal disease (ESRD), chronic kidney disease (CKD), congestive heart failure (CHF), chronic obstructive pulmonary disease (COPD) and chronic alcohol abuse (OH). Model 14 : Log [p x /(1 p x )]= 0 + 1 d ementia + 2 age category + 3 gender + 4 ethnicity + 5 SES + 6 year of admission + 7 hour of arrival + 8 source of admission + 9 payer + 1 0 HTN + 1 1 DM + 1 2 STRK + 1 3 HLP + 1 4 obesity + 1 5 SMK + 16 OH + 1 7 DEP + 1 8 ESRD + 19 CKD + 2 0 CHF + 2 1 COPD where p x is the probability of x th days to CABG for cardiac catheterized STEMI patient. M odel fifteen did not adjust for zip code SES but it did adjust for all other potential confounders and provided data regarding independent effects of each variable: age cat egory, gender, ethnicity, year of hospitalization, hour of arrival, source of admission, type of payer, and the following comorbidities: hypertension (HTN), diabetes mellitus type 2 (DM), stroke (STRK), hyperlipidemia (HLP), obesity, smoking history (SMK), depression (DEP), end stage renal disease (ESRD), chronic kidney disease (CKD),

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57 congestive heart failure (CHF), chronic obstructive pulmonary disease (COPD) and chronic alcohol abuse (OH). Model 15 : Log [p x /(1 p x )]= 0 + 1 dementia + 2 age category + 3 gender + 4 ethnicity + 5 year of admission + 6 hour of arrival + 7 source of admission + 8 payer + 9 HTN + 1 0 DM + 1 1 STRK + 12 HLP + 1 3 obesity + 1 4 SMK + 15 OH + 1 6 DEP + 1 7 ESRD + 18 CKD + 19 CHF + 2 0 COPD where p x is the probability of x th days to CA BG for cardiac catheterized STEMI patient. 3.4.3.2.4 Secondary question #4 models To address the last secondary question, model s sixteen though eighteen were run to identify if having dementia affects the length of hospital sta y for nal hazards regression model was chosen because it is able to explain the effect of several risk factors on time until discharge from hospital ( 82 ) A comparison of hospitalization length of stay between patients with dementia and pati ents without dementia was performed as follows:

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58 Model 16 : H(t) = H 0 (t) x exp( 1 dementia ) H 0 (t) is the baseline hazard at time t, representing the hazard for a person without dementia To explain the effect of comorbidity on time (discharge from hospital), the following two models were executed. Model 17 adjusts for the zip code socio economic status proxy variable (SES) and model 18 does not adjust for the zip code socio economic status proxy. Model 17 : H(t) = H 0 (t) x exp( 1 dementia + 2 age category + 3 gender + 4 ethnicity + 5 SES + 6 year of admission + 7 hour of arrival + 8 source of admission + 9 payer + 1 0 HTN + 1 1 DM + 1 2 STRK + 1 3 HLP + 1 4 obesity + 1 5 SMK + 16 OH + 1 7 DEP + 1 8 ESRD + 19 CKD + 2 0 CHF + 2 1 COPD ) H 0 (t) is the baseline hazard at time t, representing the hazard for a person with the value 0 for all the predictor variables. Model 18 : H(t) = H 0 (t) x exp( 1 dementia + 2 age category + 3 gender + 4 ethnicity + 5 year of admission + 6 hour of arrival + 7 source of admission + 8 payer +

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59 9 H TN + 1 0 DM + 1 1 STRK + 12 HLP + 1 3 obesity + 1 4 SMK + 15 OH + 1 6 DEP + 1 7 ESRD + 18 CKD + 19 CHF + 2 0 COPD) 3.4. 3.3 Sensitivity a nalysis for definition of dementia A sensitivity analysis was conducted to determine if it is appropriate or not to use the br oad definitio n of dementia, as used in model 2, compared to the This modeling was done to determ ine how dependent the definitions were. A ll those in the cohort with dementia were first identified ( model 2 ) then those with a (model 19 ) and finally a third model with 0 ) M odel 19 was done using logistic regression to compare dementia as main exposure and diagnostic card iac catheterization as outcome for those patients with a diagnosis of dementia And m odel 2 0 compared non as main exposure and diagnostic cardiac catheterization as outcome. Model 19 : Log [p x /(1 p x )]= 0 + 1 dementia + 2 age category + 3 gender + 4 ethnicity + 5 SES + 6 year of admission + 7 hour of arrival + 8 source of admission +

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60 9 payer + 1 0 HTN + 1 1 DM + 1 2 STRK + 1 3 HLP + 1 4 obesity + 1 5 SMK + 16 OH + 1 7 DEP + 1 8 ESRD + 19 CKD + 2 0 CHF + 2 1 COPD where p x is t he probability of x th STEMI Alzheimer dement ia patient receiving diagnostic cardiac catheterization Model 2 0 : Log [p x /(1 p x )]= 0 + 1 dementia + 2 age category + 3 gender + 4 ethnicity + 5 SES + 6 year of admission + 7 hour of arrival + 8 so urce of admission + 9 payer + 1 0 HTN + 1 1 DM + 1 2 STRK + 1 3 HLP + 1 4 obesity + 1 5 SMK + 16 OH + 1 7 DEP + 1 8 ESRD + 19 CKD + 2 0 CHF + 2 1 COPD where p x is the probability of x th STEMI non demented patient receiving diagnostic cardiac catheteriza tion

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61 CHAPTER 4 RESULTS 4.0 Descriptive Statistics 4.1 Characteristics of the Cohort The Florida hospital inpatient surveillance system database for the years 2006 and 2007 contained data for 13,148 STEMI patient s over 65 years of age for the years 2006 and 2007 After restricting the cohort to only those seen at high volume PCI facilities, 8,331 STEMI patients were eligible for analysis. Table 4 1 describes the characteristics of the cohort in detail. There were 7. 3 % (n=605) of patients with a diagnosis of dementia and of these, disease Most patients were early senior white males ( n=2060). The majority of patients 85.4% (n=7112) were admitted through the emergency department and 79.4% (n=6615) were coded as eme rgencies. There were no differences in distribution by time or day of the week admitted to the hospital

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62 T able 4 1 Baseline Characteristics of Elderly STEMI Patients in Florida during 2006 2007. Total cohort %(N=8,331) Patients without Dementia %(N=7 726) Patients with Dementia %(N=605) P Value for difference Age Category 65 74 75 84 85+ 45.71% (3808) 37.03% (3085) 17.26% (1438) 48.40% (3739) 36.76% (2840) 14.85% (1147) 11.40% ( 69) 40.50%( 245) 48.10% ( 291) P<0.0001 Gender Men Wome n 56.73% (4726) 43.27% (3605) 58.02% (4483) 41.98% (3243) 40.17% ( 243) 59.83% ( 362) P<0.0001 Ethnicity White non Hispanic Black non Hispanic Hispanic & Others 83.38% (6946) 4.65% ( 387) 11.98% ( 998) 83.57% (6457) 4.44% ( 343) 11.99 % ( 926) 80.83% ( 489 ) 7.27% ( 44) 11.90% ( 72 ) P=0.0061 Payer Medicare Self Pay/Charity Other 89.86% (7486) 1.03% ( 86) 9.11% ( 759) 89.50% (6915) 1.09% ( 84) 9.41% ( 727) 94.38% ( 571) 0.33% ( 2) 5.29% ( 32) P=0.0005 Rece ived Diagnostic Cardiac Catheterization 77.24% (6435) 79.63% (6152) 46.78% ( 283) P<0.0001 Received PCI 67.16% (5595) 69.29% (5353) 40.00% ( 242) P<0.0001 Received CABG 9.33% ( 777) 9.77% ( 755) 3.64% ( 22) P<0.0001 Length of Hospital Stay* 5. 99 ( 5.90) 5.98 ( 5.93) 6.09 ( 5.55) P=0.0384 Risk Factors Hypertension Diabetes Mellitus Stroke Hyperlipidemia Obesity Smoking Alcohol abuse Depression Chronic Kidney Disease End Stage Renal Disease Congestive Heart Failure C hronic O bstructive P ulmona ry D isease 67.72% (5642) 29.08% (2423) 4.89% ( 407) 56.28% (4689) 6.51% ( 542) 12.86% (1071) 0.54% ( 45) 5. 40% ( 450 ) 14.38% (1198) 1.42% ( 118) 29.77% (2480) 21.2 1 % (176 7 ) 67.87% (5244) 29.21% (2257) 4.71% ( 364) 57.33% (4429) 6.76% ( 522) 13. 47% (1041) 0.54% ( 42) 4.72% ( 365) 13.85% (1070) 1.40% ( 108) 28.86% (2230) 21.14% (1633) 65.79% ( 398) 27.44% ( 166) 7.11% ( 43) 42.98% ( 260) 3.31% ( 20) 4.96% ( 30) 0.50% ( 3) 14.05% ( 85) 21.16% ( 128) 1.65% ( 10) 41.32% ( 250) 22. 15% ( 134) P=0.2898 P=0.3546 P=0.0085 P<0.0001 P=0.0009 P<0.0001 P=0.8774 P<0.0001 P<0.0001 P=0.6092 P<0.0001 P=0.5575 *Continuous data are mean (SD)

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63 4.1.1 Age The average age of the sample was 76.30 years (SD 7.85; 95% CI SD 7.73 7.97) (Table 4 1) Figure 4 1shows the age distribution of cohort. For practical comparisons, the cohort was categorized into three age groups commonly used in the literature: early seniors (65 74 years old) mid seniors (75 84 years) and seniors over 85 years of age. Most of the sample were in the early senior category 45.7% (n=3808) and the least number of subjects were over the age of 85, 17.3% (n=1438). M ales comprised most of the early seniors 66.8% (n=2544) while females the older senior grou p 61.5% (n=885). There w as a crossover effect at 78 years of age (Figure 4 2); 48.4 % (n=3739) of non demented patients were in the early senior category while 48.1% (n=291) of those with dement ia we re in the oldest old category over 85 year s of age

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64 Figure 4 1 Age distributi on of Elderly STEMI patients in Florida during 2006 2007. Figure 4 2 Age distribution of Elderly STEMI patients in Florida during 2006 2007 by Dementia Status Percent of STEMI patients is shown for each diagnostic category 0% 1% 2% 3% 4% 5% 6% Percent of STEMI Patients Age of STEMI Patients Age distribution of Elderly STEMI Patients in Florida during 2006 2007 Percent of STEMI Patients 0% 1% 2% 3% 4% 5% 6% 7% 8% 65 67 69 71 73 75 77 79 81 83 85 87 89 91 93 95 97 99 101 103 105 Percent of STEMI Patients Age of STEMI Patients Age distribution of Elderly STEMI Patients in Florida during 2006 2007 by Dementia Status Patients with dementia Patients without dementia

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65 4.1.2 Ethnicity The majority of t he cohort were white non Hispanic 83.4% (n=6946) (Table 4 2) followed by 12.0% (n=998) Hispanics/Other. Most of the non Hispanic whites and Hispanics/Other were males 56.4% (n=3917) and 61.82% (n=617) respectively. Blacks accounted for the minority of the cohort but were more evenly distributed by gender; black females accounted for 50.4% (n=195) of that sample. However in the Hispanic/other category there were 24% fewer females than males. Table 4 2 Ethnic Characteristics of Elderly STEMI Patients in Flor ida during 2006 2007. Ethnicity Males %(n=4726) Females %(n=3605) Early Senior %(n=3808) Mid Senior %(N= 3085) Older Senior %(N= 1438) White N on Hispanic 83.4%(6946) 82.9%(3917) 84.0%(3029) 80.7%(3074) 84.7%(2614) 87.5%(1258) Black N on Hispanic 4.6%(387 ) 4.1%(192) 5.4%(195) 5.7%( 217 ) 4.0%( 125 ) 3.1%( 45 ) Hispanic/ Others 12.0%(998) 13.1%(617) 10.6%(381) 13.6%( 517 ) 11.2%( 346 ) 9.4%( 135 ) Black non Hispanic s received the least number of interventions and had the lowest prevalence of depression, but ha d the highest prevalence of dementia, end stage renal disease, congestive heart failure and current or history of smoking than any other ethnic category (Figure 4 3)

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66 4.1.3 Comorbidity of the C ohort Over two thirds of the cohort was hypertensive (67.7% n=5642); demented patients were slightly less hypertensive 65. 8 % (n=398). When stratified by ethnicity Black /African American non Hispanic s had the highest prevalence of hypertension (80.1% n=310) Refer to Figure 4 3 for specific comorbidities of the cohort by ethnicity There were 2 423 coded diabetics in the cohort (29.1%), of these 29.2% ( n=2257) were non demented patients and 27.4% (n=166) were demented patients Forty five percent of Black / A frican American non Hispanics were diabetic (n=173) and 26.4% (n=102) had chronic kidney disease (CKD). Overall there were 14.4% (n=1198) of patients in the cohort with a diagnosis of CKD; demented patients had the highest prevalence of CKD, 21.2% (n=128). Only 1.4% (n=118) of patients in the cohort had end stage renal disease (ESRD), however demented patients had the highest prevalence (1.6% n=10) and when stratified by ethnicity, Blacks had the highest prevalence (5.7% n=22). Over half of the cohort was hyperlipidemic (56.3% n=4689) yet only 6.5% (n=542) of the cohort was obese. Non demented patients had the highest prevalence of hyperlipidemia, 57.3% (n=4429). White non Hispanics had the highest number of h yperlipidemics, 57.4% (n=3986).

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67 Twenty one per cent of the cohort (n=1767) were coded as having chronic obstructive pulmonary disease (COPD) and 21.6% (n= 1500) of whites carried the diagnosis Almost 13% (n=1071) of the cohort had a history of smoking or were current smokers, of these non demented pati ents smoked the most 13.5% (n=1041). When stratified by ethnicity, Black/African American non Hispanics smoke or smoked the most, 13.7% (n=53). Very few people in the cohort were chronic alcoholics, 0.5% (n=45). Only 4.9% (n=407) of the patients in the c ohort had a history of a stroke or had a current stroke ; however 7.1% (n=43) of demented patients and 5% (n=350) of White non Hispanics had the highest prevalence. There were 5.4% (n=450) patients in the cohort with a diagnosis of depression; 14% of dement ed patients were depressed compared to 4.7% of non demented patients and Hispanics/Other had the highest prevalence of depression from all other ethnic groups, 6.2% (n=62).

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68 *ESRD (End Stage Renal Disease), CKD (Chronic Kidney Disease), COPD (Chronic Obstructive Pulmonary Disease), CHF (Congestive Heart Failure), DM (Diabetes Mellitus), HLP (Hyperlipidemia), HTN (Hypertension). Figure 4 3 Prevalence of Comorbidities among STEMI patients by ethnicity. 4.1. 4 Source and D ays of Admissions The source of most admissions was through emergency room 85.4% (n=7112) and as referrals 13.9% (n=1155). There were no significant differences for source of admission by gender, age category, ethnicity or day of admission Dement ed patients were more likely to be admi tted on Friday 17.2% (n=104) but this was not significant when compared to non dement ed patients (Table 4 3) 0% 20% 40% 60% 80% 100% Current Alcohol Use ESRD* Stroke Depression Obesity Current Smoking CKD* COPD* DM* CHF* HLP* HTN* % STEMI Patients Prevalence of comorbidities among STEMI patients by ethnicity Hispanic/Other Black non Hispanic White non Hispanic N=998 N=387 N=6946

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69 Table 4 3 Day of Week of Hospital Admission for STEMI Patients with and without dementia in Florida during 2006 2007. Day of Admission Total co hort %(N=8,331) Patients without Dementia %(N=7726) Patients with Dementia %(N=605) P Value for difference Monday 15.1% (1257) 15.0% (1162) 15.7% (95) P=0.7344 Tuesday 14.1% (1176) 14.1% (1090) 14.2% (86) Wednesday 15.0% (1249) 15.1% (1167) 13.5% (82) Thursday 13.8% (1151) 13.8% (1069) 13.5% (82) Friday 15.0% (1252) 14.9% (1148) 17.2 % (104) Saturday 13.3% (1109) 13.4% (1034) 12.4% (75) Sunday 13.6% (1137) 13.7% (1056) 13.4% (81) 4.1. 5 Type of Admissions and Payer Most type of admissions were emergencies 79.4% (n=6615). There were no major differences in type of admission by payer, gender or dementia status. Payment distribution was allocated into three categories: Medicare payers, self pay or charity, and other means including commercial insur ance. Nearly everyone paid through Medicare 89.9% (n=7486); 9.1% (n=759) paid through other means and only 1.0% (n=86) were self pay.

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70 4.1. 6 Length of Hospital Stay The mean length of the hospital stay for survivors in the cohort was 6 .2 days (SD 5.9 ; 9 5% CI 6.05 6.35; p<0.0001 ) Table 4 4 shows detail data for this variable by dementia status. Females had slightly longer hospital stays than males (6.32 days vs. 6.07 days ). Most females (40.0% n=1261) stayed 4 7 days in the hospital while the majority of males (39.1% n=1667) stayed for 2 3 days p<0.0001. Table 4 4 Length of Hospital Stay for survivor STEMI Patients with and without dementia in Florida during 2006 2007. Length Total survivors %(N= 7422 ) Patients without Dementia %(N=6921 ) Patients wit h Dementia %(N= 501 ) P Value for difference Less or equal 1 day 2.9%(216) 2.9%(201) 3.0%(15) <0.0001 Within 2 3 days 36.0%(2671) 36.8%(2547) 24.7%(124) Within 4 7 days 36.5%(2708) 36.0%(2490) 43.5%(218) Within 8 1 4 days 17.6%(1309) 17.4%(1203) 21.2 %(106) Within 15 30 days 5.8%(433) 5.8%(401) 6.4%(32) Greater than 1 month 1.15%(85) 1.1%(79) 1.2%(6)

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71 4.2 Outcomes for Cardiovascular Interventions Figure 4 4 Percent of STEMI patients who received interventions in Florida during 2006 2007. Over t hree quarters of STEMI patients in the cohort received diagnostic card iac catheterization, 77.2% (n=6435) ; slightly more than two thirds, 67.2% (n=5595) underwent PCI and 9.3% (n=777) received CABG (Figure 4 4) When looking only at those who received cath eterizations, 73.8% (n=6150 p=<0.0001) received some form of intervention, either PCI or CABG. Sixty percent of the cohort (n= 4986 ) received PCI on the same day of admission and 5.4% (n=449) received CABG In general those in the older group, patients wit h dementia and females were less likely to receive any kind of intervention. Figures 4 4 to 4 11 show the distribution of interventions by different variables of interest. 77% 67% 9% 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% Diagnostic Catheterization PCI CABG % of STEMI Patients Who Received Intervention Intervention Percent of STEMI Patients Who Received Specific Interventions N=5595 N=6435 N=777

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72 Figure 4 5 Percent of STEMI patients who received interventions by dementia st at us Figure 4 6 Percent of STEMI patients who received interventions by gender. 47% 40% 4% 80% 69% 10% 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% Diagnostic Catheterization PCI CABG % of STEMI Patients Who Received Intervention Intervention Percent of STEMI Patients Who Received Specific Interventions by Dementia Status Demented Non Demented N=777 N=5595 N=6435 82% 70% 12% 71% 63% 6% 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% Diagnostic Catheterization PCI CABG % of STEMI Patients Who Received Intervention Intervention Percent of STEMI Patients Who Received Specific Interventions by Gender Males Females (N=6435) (N=5595) (N=777)

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73 Figure 4 7 Percent of STEMI patients who received interventions by age category. Overall the very old, those over the age of 85, received 30% fewer interventions ( diagno stic cardiac catheterization or PCI) than the early seniors (Figure 4 7) When stratifying th e age categories by dementia status the percent of STEMI patients who received catheterization or PCI was the same. 87% 76% 12% 78% 67% 10% 50% 45% 2% 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Diagnostic Catheterization PCI CABG % of STEMI Patients Who Received Intervention Age Category Percent of STEMI patients who received intervention by age category 65 74 75 84 85+ (N=6435) ( N=5595 ) (N=777)

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74 Figure 4 8 Percent of STEMI patients who re ceived diagnostic cardiac catheterizati on by age category and dementia status. Figure 4 9 Percent of STEMI patients who received PCI by age category and dementia status. 61% 61% 32% 87% 80% 55% 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% 65 74 75 84 85+ % of STEMI Patients Who Received diagnostic catheterization Age Category Percent of STEMI patients who received diagnsotic cardiac catheterization by age category and dementia status Dementia No Dementia ( N=3808 ) ( N=3085 ) ( N=1438 ) 52% 50% 29% 76% 68% 50% 0% 10% 20% 30% 40% 50% 60% 70% 80% 65 74 75 84 85+ % of STEMI Patients Who Received PCI Age Category Percent of STEMI patients who received PCI by age category and dementia status Dementia No Dementia ( N=3808 ) ( N=3085 ) ( N=1438 )

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75 Figure 4 10 Percent of STEMI patients who received CABG by age category and demen tia Figure 4 1 1 Percent of STEMI patients who received interventions by SES category. 7% 6% 1% 12% 10% 3% 0% 2% 4% 6% 8% 10% 12% 14% 65 74 75 84 85+ % of STEMI Patients Who Received CABG Age Category Percent of STEMI patients who received CABG by age category and dementia status Dementia No Dementia ( N=3808 ) ( N=3085 ) ( N=1438 ) 78% 69% 7% 76% 65% 10% 77% 67% 10% 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% Diagnostic Catheterization PCI CABG % of STEMI Patients Who Received Intervention Age Category Percent of STEMI patients who received intervention by SES category SES* < $7,790 ( N=5985 ) ( N=5215 ) ( N=702 )

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76 4.3 Comorbidities and Use of Interventions *Alcohol (Current Alcohol abuse ), ESRD (End Stage Renal Disease), DEP (Depression), CKD (Chronic Kidney Disease), Smoking ( Current Smoking), COPD (Chronic Obstructive Pulmonary Disease), CHF (Congestive Heart Failure), DM (Diabetes Mellitus), HLP (Hyperlipidemia), HTN (Hypertension). Figure 4 1 2 Prevalence of Comorbidities for STEMI patients in Florida by age category. 4.3. 1 Hypertension More than two thirds of the cohort was hypertensive 67.7% (n=5642). Table 4 5 provides a detail description of the hypertensive patients. Seven percent of the individuals with high blood pressure had dementia and 2.2% had a diagnosis of Alz subjects, only 5.4% had a stroke 6% were depressed 7.7% were obese 0% 10% 20% 30% 40% 50% 60% 70% 80% % of STEMI Patients with comorbidity Comorbidity Prevalence of Comorbidity among STEMI patients by Age Category 65 74 75 84 85+

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77 12% currently smoked or had a history of smoking 33.5% were diabetic and 62% were hyperlipidemic. Table 4 5 Characteristics of h ypertensive STEMI p atients in Florida d uring 2006 2007. Patients with Hypertension % (n=5642) Patients without Hypertension % (n= 2689 ) Chi square Probability Gender Men Women 54.50 % (3075) 45.50 % (2567) 61.40% (1651) 38.60% (1038) p<0.0001 Ethnicity White non Hispanic Black non Hispanic Hispanic & Others 82.17% (4636) 5.49% ( 310) 12.34% ( 696) 85.91% (2310) 2.86% ( 77) 11.23% ( 302) p<0.0001 Received Cardiac Catheterization 76.85% (4336) 78.06% (2099) p=0.2194 Received PCI 66.55% (3755) 68.43% (1840) p=0.0889 Received CABG 9.38% ( 529) 9.22% ( 248) p=0.8220 Other Medical Conditions Dementia Diabetes Mellitus Stroke H yperlipidemia Obesity Smoking Alcohol abuse Depression Chronic Kidney Disease End Stage Renal Disease Congestive Heart Failure COPD 7.05% ( 398) 2.23% ( 126) 33.55% (1893) 5.41% ( 305) 61.93% (3494) 7.71% ( 435) 12.00% ( 677) 0.41% ( 23) 5.99% ( 338) 17.81% (1005) 1.84% ( 104) 9.23% (1649) 21.64% (1221) 7.70% ( 207) 2.68% ( 72) 19.71% ( 530) 3.79% ( 102) 44.44% (1195) 3.98% ( 107) 14.65% ( 394) 0.82% ( 22) 4.17% ( 112) 7.18% ( 193) 0.52 ( 14) 30.90% ( 831) 20.30% ( 546) p=0.2898 p=0.2132 P<0.0001 P=0.0014 P<0.0001 P<0.0001 P=0.0007 P=0.0169 P=0.0006 P<0.0001 P<0.0001 P=0.1177 P=0.1630 4.3.2 Hyperlipidemia O ver half of the cohort was hyperlipidemic 56.3% (n=4689) Most were early and mid seniors (51.78% and 3 5.2% respectively) and 57.9% were males

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78 ( see figure 4 12 ) Of all the patients with high lipids, a total of 82% received cardiac catheterization (OR 1.85 95% CI 1.67 2.06) and 71.8 % received PCI (OR 1.61 95% CI 1.47 1.77). There was no significant diffe rence in receiving CABG for those with and without hyperlipidemia. Only 5.5% (OR 0.56 95% CI 0.47 0.66) of t he hyperlipidemics had dementia and 1.7% (OR 0.52 95% CI 0.39 Patients with hyperlipidemia were 1.5 times more likely to have diabetes (95% CI 1.33 1.61) two times as likely (OR 2.03 95% CI 1.85 2.23) to have hypert ension 1.9 times more likely to be obese (95% CI 1.58 2.31) than non hyperlipidemics and smoked 20% more than patients without high lipid s. However depression was not significant for these pati ents (OR 1.04 95% CI 0.86 1.27) and they were less likely to have chronic kidney disease ( OR 0.86 95% CI 0.76 0.97) end stage renal disease ( OR 0.44, 95% CI 0.30 0.64) congestive heart failure (OR 0.73, 95% CI 0.66 0.80) and less COPD (OR 0.81, 95% CI 0.73 0.90) 4.3.3 Diabet es Type 2 Over a quarter of the cohort was diabetic, 29.1% (n=2423) and of these 76.1% received cardiac catheterization; however diabetics were 0.78 times less likely to receiv e PCI than non diabetics (95% CI 0.70 0.86) but 1.4 times more likely to go through CABG (95% CI 1.19 1.62). Gender was not a significant factor for diabetes. Early seniors were 36% more diabetic than

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79 older seniors (49% vs. 13%). More Black non Hispanic/A frican American 44.7% (n=173) were diabetics than any of the other ethnic groups. Dementia was not a significant factor for having diabet es (OR 0.92, 95% CI 0.76 1.10) Two thirds of the diabetics had high lipids (OR 1.46 95% CI 1.33 1.61) ; they were 2. 1 times more likely to have hypertension (95% CI 1.84 2.30) ; 2.4 times more likely to be obese (95% CI 2.03 2.88) and much more likely to have end stage renal disease (OR 2.84, 95% CI 1.97 4.09) and chronic kidney disease (OR 2.07, 95% CI 1.83 2.35) Diabe tics were also 1.5 times more likely than non diabetics to have congestive heart failure. Nonetheless, they were less likely to smoke than non diabetics (OR 0.80, 95% CI 0.59 0.93). 4.3.4 Stroke Roughly 5% of the cohort (n=407) had had either current stro ke or history of stroke. F emales had 2% more history or current strokes than males 50.9% versus 49.1% respectively (OR 0.72, 95% CI 0.59 0.88) and mid seniors had more history or current strokes than seniors over 85 years of age 41.77% vs. 19.90% (p<0.0 09) Ethnicity was not a statistically significant factor for patients with or without a current stroke or medical history of one (p=0.3004).

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80 Patients with a history of or current stroke were 0.5 times less likely to have cardiac catheterizations than t hose without strokes (95% CI 0.42 0.63) and 0.4 times less likely to receive PCI (95% CI 0.37 0.55); however, they were more likely to receive CABG than those without a current stroke or history of one (OR 1.45, 95% CI 1.08 1.96). Patients with dement ia h ad had 2.4% more history or current strokes than non dement ed patients, 7.11% vs. 4.71% (OR 1.55, 95% CI 1.11 2.15 ). Seventy five percent of patients with a history of or current stroke had hypertension (OR 1.45, 95% CI 1.15 1.82) and w ere more likely to be depressed ( OR 1.48, 95% CI 1.01 2.16) although this was not statistically significant; these patients were more likely to have COPD (OR 1.59, 95% CI 1.28 1.98) chronic kidney disease (OR 1.80, 95% CI 1.41 2.29), and congestive heart failure (OR 1.98, 9 5% CI 1.62 2.42) than those without a current stroke or history of one 4.3.5 Smoking and Alcohol abuse Roughly one eighth ( 12.9% n=1071) of the sample currently smoked or had smoked Most smokers were in the early senior category (70.6% n=756) and wer e males (62.4% n=668) Blacks/African Americans non Hispanics were the ethnic group that smoked the most (13.7%). Eighty eight percent of smokers were catheterized, 77.6% received PCI and 11.5% went through CABG (Figure 4 13) Non dement ed patients smoke d much more than those

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81 with dement ia (13.5% vs 4.96%) and only 3.0% of the patients diagnosed Almost two thirds of smokers were hypertensive (63.21% n=677) and 60% (n=644) had hyperlipidemia (OR 1.20, 95% CI 1.05 1.37 ). Smokers were 5.5 times more likely than non smokers to use alcohol (95% CI 3.05 9.95) and 3.6 times more likely to have COPD than non smokers (95% CI 3.11 4.07). Figure 4 1 3 Percent of smoker and non smoker STEMI patients in Florida during 2006 2007 who received interventions. Alcohol ab users were 0.5 times less likely to be hypertensive than non alcohol drinkers (95% CI 0.28 0.89) and were more likely to be early seniors (68.9% n=31). All other associations with alcohol abuse were not statistically significant. 88% 78% 11% 76% 66% 9% 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Diagnostic Catheterization PCI CABG Percent of smoker and non smoker patients who received intervention Percent of smoker and non smoker STEMI patients who received interventions SMOKERS NON SMOKERS N=1071 N=7260

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82 4.3.6 Congestive Heart Failure Almost 30 % (n=2480) of the cohort had congestive heart failure ; most of these were in the mid senior category (41.3% n=1025) Compared to patients without CHF, these patients were less likely to receive diagnos tic cardiac catheteriz ation (OR 0.46, 95% CI 0.41 0.51) or receive PCI (OR 0.38 95% CI 0.34 0.42), but were more likely to have CABG (OR 1.58, 95% CI 1.35 1.84). Ten percent of those with CHF had dementia (OR 1.73, 95% CI 1.46 2.05) and were 1.5 times more 1.11 1.98). Over 7% of CHF patients had stro kes or had history of a stroke (OR 1.98, 95% CI 1.62 2.42) and more than a third were diabetic (35.5% n=2480) (OR 1.54, 95% CI 1.4 1.7). CHF patients were 0.7 times less like ly to be hyperlipidemic (95% CI 0.66 0.80) or smokers (95% CI 0.60 0.81) than non CHF patients but were 1.5 times more likely to be depressed (95% CI 1.27 1.87). Almost a third of CHF patients suffered from COPD, 31.8% (OR 2.32, 95% CI 2.08 2.59); they we re 2.9 times more likely to have early stage renal disease (95% CI 2.04 4.24) and 3.3 times more likely to have chronic kidney disease (95% CI 2.9 3.7) than non CHF patients. 4.3.7 E nd S tage Renal Disease and Chronic Kidney Disease Only 1.4% (n=118) of th e total cohort and 1.6% (n=10) of those with dementia had a diagnosis of end stage renal disease (ESRD) but of those

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83 diagnosed with ESRD, 8. 5 % had dementia (Figure 4 14) and 2.5 % were Patients with ESRD were less likely to rec eive diagnostic cardiac catheterization (OR 0.49, 95%CI 0.34, 0.71) or PCI (OR 0.59, 95% CI 0.41, 0.86) than those without it and 6% of the patients with ESRD received CABG (OR 0.6096, 95% CI 0.28, 1.31). Most of the ESRD patients were in the early senio r group (49.1%) and were white non Hispanic (69.49%). ESRD patients were 3.6 times more likely to have hypertension (95% CI 2.05, 6.28) 2.8 times more likely to have diabetes (95% CI 1.9 7, 4.09) and 2.9 times more likely to have CHF (95% CI 2.04, 4.24) t han patients without ESRD ; however they were 0.4 times less likely to have hyperlipidemia (95% CI 0.30, 0.64). *ESRD (End Stage Renal Disease), CKD (Chronic Kidney Disease). Figure 4 1 4 Prevalence of dementia among STEMI patients with ESRD* and CKD* wh o received interventions. 8% 11% 92% 89% 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% ESRD* CKD* % of STEMI patients Prevalence of dementia among STEMI patients with ESRD* and CKD* Dementia No Dementia

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84 Fourteen percent (n=1198) of the cohort had CKD Patients with CKD were less likely to receive diagnostic cardiac catheterization (OR 0.44 95% CI 0.38, 0.50) and PCI (OR 0.45, 95% CI 0.40, 0.51) but were 1.3 times more likely to go through CABG (95% CI 1.04, 1.55) than those without CKD. Most were males (61.5%) mid seniors (40.6%) and White non Hispanic (79%). Those diagnosed with CKD were 1.7 times more likely to have a diagnosis of dementia (95% CI 1.36, 2.05) and 1.9 times mor 1.35, 2.63) than those without CKD (Figure 4 14) Patients with CKD were 1.8 times more likely to have had strokes or a current stroke (95% CI 1.41, 2.29), more likely to be hypertensive (OR 2.8, 95% CI 2.38, 3.29) diabetic (OR 2.07 95%CI 1.83, 2.35 ), 1.5 times more likely to have COPD (95% CI 1.28, 1.70) and 3.3 times more likely to have CHF (95% CI 2.91, 3.74) than patients without CKD. Those with CKD were 0.9 times less likely to have hyperlipidemia (95% CI 0.76, 0.97) and 0.5 tim es less likely to be smokers (95% CI 0.44, 0.68). Patients with CKD were 16.6% more hyperlipidemic (53.0% vs.36.4%) and smoked 2% more than patients with ESRD (7.93% vs. 5.93%); however there were 10.3% more patients with ESRD that were diabetics than wer e there CKD patients with diabetes (53.4% vs. 43.1%). There were 2.1% more patients with ESRD that were obese than there were obese CKD patients (Figure 4 15)

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85 COPD (Chronic Obstructive Pulmonary Disease), DM (Diabetes), CHF (Congestive Heart Failure), HLP (Hyperlipidemia), HTN (Hypertension). Figure 4 1 5 Prevalence of common risk factors among STEMI patients with e nd stage renal disease (ESRD) or chronic kidney disease (CKD) in Florida during 2006 2007. 4.3. 8 Depression There were 450 patients diag nosed with depression in the cohort (5.40%) and m ost were women (64% n=288). Older seniors were less depressed than the younger seniors (21.6% vs. 38.7%) and Black/African American non Hispanics were the least depressed (2.7%) Two thirds of those diagnose d depressed received cardiac catheterization (OR 0.56, 95% CI 0.45 0.68) and 54.4 % received PCI (OR 0.56, 95% CI 0.47 0.68). Nineteen percent of depressed patients were demented (OR 3.30, 95% CI 2.56 4.24) 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% % of STEMI patients with risk factor Risk Factors for STEMI Patients Prevalence of common risk factors among STEMI Patients with end stage renal disease (ESRD) and chronic kidney disease (CKD) ESRD CKD

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86 and those depressed were 3.3 times more likely to than non depressed patients (95% CI 2.20 4.89). Three quarters of all depressed patients were hypertensive (OR 1.47, 95% CI 1.18 1.82) 33.3% had COPD (OR 1.9, 95% CI 1.58, 2.37) and depressed patients were 1.5 times more likely to have CHF than non depressed (95% CI 1.26, 1.87). Al though most had hyperlipidemia (57.3%) it was not statistically significant. A diagnosis of depression was 1.5 times more likely to be associated with CHF (95% CI 1.26 1.87) th a n non depressed. 4.3. 9 Obesity Only 6.5% (n=542) of the cohort was coded obese Of these, 12% smoked 16 % had CKD 23% COPD and 28% CHF but the associations were not statistically significant. However over 70% of the obese had hyperlipidemia (OR 1.9, 95% CI 1.58 2.31) and were 2.4 times more likely to be diabetic than non obese patients (95% CI 2.03 2.88) O ver 80% of the obese were hypertensive (OR 2.02, 95% CI 1.62 2.50). 4.4 Overview of Descriptive Statistics by Dementia The prevalence of dementia in the study was 7.3%. Mos t demented patients were White non Hispanic but Black/African American non Hispanics had the highest prevalence of dementia among all ethnic groups (11.4%). Almost 60% of all demented were females. As expected, most demented patients

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87 belonged to the 85 or older age category (48.1%) One third of demented patients had a diagnosis of AD. The highest percentage of demented patients arrived to the hospital in the afternoon hours (25.8%) while most non demented patients arrived to the hospital in the morning ( 25.6%). Ninety four percent of demented patients paid through Medicare. Only 46.8% of d emented patien ts received diagnostic cardiac catheterization, 40% received PCI and 3.6% received CABG (refer to figure 4 5). Only 37.5% of demented patients received P CI within the first 24 hours after arrival to the hospital compared to 61.7% of non demented who did receive PCI within a day ; 2.6% of demented patients received CABG within the first 24 hours while 5.6% of non demented patients received it on the same day of arrival. When comorbidities were stratified by dementia status, demented patients were 1.55 times more likely to have or have had a stroke than non dements (95% CI 1.11 2.15); over three times more likely to have depression (OR 3.25 95% CI 2.52 4.19 ); 1.67 times more likely to have chronic kidney disease (95% CI 1.36 2.05) and 1.7 times more likely to have congestive hear t failure (95% CI 1.46 2.05); h owever dement ed patients were 0.56 times less likely to have hyperlipidemia (OR 0.56 95% CI 0.47 0. 66); 0.47

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88 times less likely to be obese (OR 0.47 95% CI 0.30 0.74) and 0.33 times less likely to be smoke rs or had ever smoked (OR 0.33 95% CI 0.23 0.49). There were no statistically significant differences between demented and no demented patients in regards to hypertension (OR 0.9, 95% CI 0.76 1.08), diabetes (OR 0.92, 95% CI 0.76 1.10) ESRD (OR 1.2, 95% CI 0.62 2.27 ) alcohol abuse (OR 0.9, 95% CI 0.28 2.95) or COPD (OR 1.06, 95% CI 0.87 1.30) Refer to figure 4 16 for details of comorbidity for dem entia patients. *ESRD (End Stage Renal Disease), DEP (Depression), CKD (Chronic Kidney Disease), DM (Diabetes), CHF (Congestive Heart Failure), HLP (Hyperlipidemia), HTN (hypertension). Figure 4 1 6 Prevalence of c om mon risk factors for STEMI patients by dementia status 0% 10% 20% 30% 40% 50% 60% 70% 80% % of STEMI patients with risk factor Prevalence of common risk factors for STEMI patients by dementia status Dementia Patients Non demented Patients

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89 4.5 Overview of Descriptive Statistics by Gender Most of the cohort consisted of men, 56.7% (n=4726), yet most dements were women (60%, n=362) and 1.2% more women than men had an 3.05% vs. 1.86% (OR 0.60, 95% CI 0.45 0.80 ) Males were 1.9 times more likely than women to receive car diac catheterization (95% CI 1.6 9 2.08); 1.4 times more likely to be given PCI (95% CI 1.27 1.53) and 2.2 times more likely to go through CABG (95% CI 1.89 2.64) (Figure 4 6) Most men wer e in the early senior category and most women were in the mid senior years, 54% and 40% respectively (Figure 4 17) Most white non Hispanic and Hispanics were males (56.4% and 61.8%), while most Black non Hispanics/African Americans were women (50.4%). Figure 4 17 Age Distribution of STEMI Patients by Gender. 0% 10% 20% 30% 40% 50% 60% 65 74 years old 75 84 years old 85+ years old Percent of STEMI Patients Age Categories Age Distribution of Elderly STEMI Patients by Gender Males Females N=4726 N=360

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90 Males were less likely to have strokes (OR 0.72, 95% CI 0.59 0.88) hypertens ion (OR 0.75, 95% CI 0.68 0.83), depression (OR 0.41, 95% CI 0.33 0.50) CHF (OR 0.72, 95% CI 0.66 0.79) and COPD (OR 0.86, 95% CI 0.77 0.96) than women (Figure 4 18) ; but they were more likely to have hyperlipidemia (OR 1.12, 95% CI 1.02 1.22) and chronic kidney disease (OR 1.26, 95%CI 1.11 1.43). Males were 4.2 times more likely to drink alcohol than females (95% CI 1.8 6 9.34) and 1.3 times more likely to be smokers or have a history of smoking (95% CI 1.45 1.49). 4.6 Multivariate Logistic Regression Analysis 4.6.1 Main Research Question To address the main research question evaluating if there is a disparity in the use of cardiac catheterization for ST Myocardial Infarction patients with a diagnosis of dementia versus patients without a diagnosis of dementia after controlling for the following patient and hospital factors: age; gender; ethnicity; zip code SES; year of ho spital admission; hour of arrival at the emergency department; source of admission; principal payer and the following comorbidities: hypertension (HTN), diabetes mellitus type 2 (DM), stroke (STRK), hyperlipidemia (HLP), obesity, smoking history (SMK), dep ression (DEP), end stage renal disease (ESRD), chronic kidney disease (CKD), congestive heart failure (CHF), chronic obstructive pulmonary disease (COPD) and chronic alcohol abuse (OH) models one, two and three were run (T able 4 6 )

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91 M odel one addressed t he probability of receiving diagnostic cardiac catheterization among STEMI patients with and without dementia not adjusting for any other variables A total of 8,331 observations were read; of these 6,435 received diagnostic cardiac catheterization. Patie nts with a diagnosis of dementia were less likely to receive catheterization s than patients without dementia ( OR 0.22; 95% CI 0.19 0.27, p< 0.0001). Only 93.5% (n=7791) of the cohort had Florida zip code data and consequently had the proxy for zip code s ocio economic status (SES). From the available zip code SES data the mean income of the cohort was $35,086.30 (95% CI $30,865.5 $39,307.0 p<0.0001). Demented patients reported less income than non demented ($29,471.4 0 vs. $35,532.3 0 ). Model two adjust e d for all variables of interest T here were 7,791 observations read and of these 5,985 received diagnostic cardiac catheterization. After adjusting for all covariates, patients with dementia were less likely to receive catheterization s than patients withou t dementia (OR 0.41, 95% CI 0.34, 0.50; p<0.0001). M odel three did not adjust for zip code SES to see if there was a difference in reducing the cohort by 540 observations and/or adjust ing for this variable ; t here were 8,331 observations read and 6,435 of these received cardiac

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92 catheterization. The only affected variable by excluding zip code SES from model two was diabetes, which became statistically significant ( OR 0.87; 95% CI 0.77 0.99; p=0.0324 ); all other variables remain unaffected. Overall non deme nted patients were 2.4 times more likely to receive diagnostic cardiac catheterization than demented patients. Other conditions that reduced the odds of receiving cardiac catheterization were: being female; B lack non Hispanic ethnicity ; having a stroke or having history of a stroke ; d iagnos is of depression, CKD CHF, or COPD. In addition, i f a patient was younger had cardiovascular risk factors of hyperlipidemia, obesity and was a current smoker, they were more likely to receive diagnostic cardiac catheter ization than if they did not H owever, having hypertension and drinking alcohol did not impact the outcome, nor did zip code SES, year of admission, hour of arrival, sour ce of admission to the hospital, method of payment used or having ESRD

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93 Table 4 6 Results of Multivariate Logistic Regression for main research question modeling the probability of diagnostic cardiac catheterization. Model One (n=8331) Odds Ratio (95% CI) Diagnostic Cardiac Catheterization as Outcome Model Two (n=7791) Odds Ratio (9 5% CI) Diagnostic Cardiac Catheterization as Outcome Model Three (n=8831) Odds Ratio (95% CI) Diagnostic Cardiac Catheterization as Outcome Dementia 0.22 (0.19 0.27) 0.41 ( 0.34 0.50) 0.41 (0.34 0.50) Age Category 65 74 75 84 85+ 3.90 (3.31 4.58) 3.0 0 (2.59 3.48) 1.00 3.98 (3.40 4.6 6 ) 2.99 (2.59 3.45) 1.00 Gender Female Male 0.69 (0.61 0.77) 1.00 0.70 (0.62 0.78) 1.00 Ethnicity White non Hispanic Black non Hispanic Hispanic/Other 1.00 0.55 (0.43 0.71) 1.0 6 (0.8 8 1.2 8 ) 1.00 0.57 (0.44 0.7 3 ) 1. 06 (0.89 1. 04 ) Zip code SES* < $7750 1.02 (0.87 1.21) 0.91 (0.78 1.05) 1.00 Year 2006 2007 0.94 (0.84 1.05) 1.00 0.93 (0.83 1.04) 1.00 Hour of arrival to hospital Early Morning Morning Afternoon Night Unknown 0.83 (0.69 1 .00) 1.00 0.91 (0.77 1.0 8 ) 0.78 (0.66 0.93) 0.82 (0.59 1.15) 0.85 (0.71 1.02) 1.00 0.92 (0.78 1.08) 0.77 (0.66 0.91) 0.81 (0.59 1.11) Source of Admission Outside Hospital MD Ref Emergency Room MD Ref Other* 1.08 (0.53 2.2 2 ) 0.99 (0.50 1.96) 1.00 1.16 (0.59 2.30) 1.04 (0.54 2.0 1 ) 1.00 Pay Medicare Self Pay & Charity Other ** 1.2 1 (0.9 7 1.5 0 ) 1. 13 (0. 60 2.12 ) 1.00 1. 18 (0.9 6 1.4 5 ) 0.97 (0. 56 1.71 ) 1.00 Hypertension 1.0 2 (0.89 1.16) 0.99 (0.87 1.12) Diabetes Type 2 0.90 (0.79 1.03) 0.87 (0.77 0.9 9) Stroke 0.61 (0.48 0.77) 0.59 (0.47 0.75) Hyperlipidemia 1.51 (1.34 1.70) 1.51 ( 1.35 1.70) Ob esity 1.51 (1.15 1.99) 1.50 (1.15 1.95) Smoking 1.70 (1.38 2.11) 1.79 (1.45 2.21) Depression 0.71 (0.56 0.89) 0.72 (0.57 0.90) End Stage Renal Disease 0.87 (0.56 1.33) 0.86 (0.57 1.31) Chronic Kidney Disease 0.61 (0.52 0.71) 0.62 (0.53 0.72) Congestive Heart Failure 0.64 (0.57 0.73) 0.67 (0.59 0.75) COPD 0.71 (0.62 0.82) 0.70 (0.61 0.80) Chronic Alcohol abuse 1.14 (0.46 2.81) 1.03 (0.44 2.40) Zip Code Socio Economic Status *Other :Transfer from skilled nursing facility; court/law enforcement; information not available) * *Other ( any other method of payment: Medicaid,commercial ins urance; ensation CHAMPUS; VA; Other State/Local G ov ernment ; Other.)

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94 4.6.2 Secondary Research Questions 4.6.2.1 Secondary Question #1 Models four, five and six were run t o determine if there was a difference in PCI use between STEMI patients with and without dementia who underwent cardiac catheterization compared to those who did not receive PCI but did receive diagnostic cardiac catheterization Only PCI was measured as outcome for models 4 to 6; the models do not include patients who received CABG. Model four was run witho ut adjusting for any covariates m odel five adjusted for all covariates and model six adjuste d for all covariates except SES (Table 4 7). After diagnostic cardiac catheterization, f emales were 1.4 times more likely to receive PCI than males (95% CI 1.21 1.69; p <0.0001). Those patients that belonged to a Florida zip code in which the average per capita income was estimated to be less than $7,750 were 1.4 times more likely to receive PCI. Also those with ESRD were more likely to undergo PCI (OR 2.66; 95% CI 1.17 6.04). Patients who were diabetics, had strokes, presented CHF and COPD we re less likely to receive PCI When the proxy for zip code SES was eliminated for model six, ESRD was no longer statistically significant (OR 2.07; 95% CI 0.99 4.34; p=0531); nevertheless all other significa nt variables in model five were still significant in model six.

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95 Table 4 7 Results of Multivariate Logistic Regression for secondary research question #2 modeling the probability of receiving PCI for those patients that received diagnostic cardiac cathete rization. Model Four (n= 6435 ) Odds Ratio (95% CI) PCI as Outcome for those who receive catheterization Model Five (n= 5985 ) Odds Ratio (95% CI) PCI as Outcome for those who receive catheterization Model Six (n= 6435 ) Odds Ratio (95% CI) PCI as Outcome fo r those who receive catheterization Dementia 0.88 (0.63 1.24) 0.92 (0.64 1.32) 0.92 (0.64 1.31) Age Category 65 74 75 84 85+ 0.66 (0.49 0.89) 0.61 (0.45 0.81) 1.00 0.65 (0.49 0.87) 0.59 (0.44 0.78) 1.00 Gender Female Male 1.43 (1.21 1.69) 1.00 1 .48 (1.26 1.74) 1.00 Ethnicity White non Hispanic Black non Hispanic Hispanic/Other 1.00 0.96 (0.65 1.43) 0.92 (0.73 1.17) 1.00 0.98 (0.67 1.43) 1.00 (0.80 1.25) Zip code SES* < $7750 1.38 (1.10 1.74) 1.01 (0.83 1.23) 1.00 Year 2006 2007 0.99 (0.84 1.16) 1.00 0.97 (0.84 1.13) 1.00 Hour of arrival to hospital Early Morning Morning Afternoon Night Unknown 0.99 (0.77 1.28) 1.00 1.03 (0.83 1.30) 1.06 (0.84 1.35) 0.94 (0.60 1.46) 1.0 (0.78 1.28) 1.00 1.02 (0.82 1.27) 1.07 (0.85 1.34) 0.97 (0.64 1.48) Source of Admission Outside Hospital MD Ref Emergency Room MD Ref Other* 0.38 (0.11 1.33) 0.48 (0.15 1.60) 1.00 0.33 (0.09 1.12) 0.46 (0.14 1.51) 1.00 Pay Med icare Self Pay & Charity Other ** 0.997 (0.75 1.33) 0.95 (0.45 2.00) 1.00 1.0 (0.77 1.31) 0.99 (0.50 1.96) 1.00 Hypertension 0.93 (0.78 1.13) 0.93 (0.79 1.10) Diabetes Type 2 0.70 (0.59 0.83) 0.72 (0.61 0.85) Stroke 0.53 (0.38 0.72) 0.54 (0.40 0.7 4) Hyperlipidemia 1.16 (0.99 1.37) 1.18 (1.01 1.37) Obesity 0.82 (0.62 1.08) 0.78 (0.59 1.01) Smoking 1.28 (1.00 1.63) 1.23 (0.97 1.54) Depression 0.78 (0.56 1.08) 0.77 (0.56 1.06) End Stage Renal Disease 2.66 (1.17 6.04) 2.07 (0.99 4.34) Chroni c Kidney Disease 0.81 (0.64 1.02) 0.83 (0.67 1.04) Congestive Heart Failure 0.39 (0.33 0.47) 0.38 (0.33 0.45) COPD 0.69 (0.57 0.83) 0.69 (0.57 0.82) Chronic Alcohol abuse 1.16 (0.43 3.12) 1.26 (0.47 3.37) Zip Code Socio Economic Status *Other:Tr ansfer from skilled nursing facility; court/law enforcement; information not available) * *Other (any other method of payment: Medicaid,commercial ins urance; ensation CHAMPUS; VA; Other State/Local Gov ernment ; Other.)

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96 4.6.2.2 Secondary Questi on # 2 M odels seven, eight and nine run to ascertain if there was a disparity of CABG use between STEMI patients with and without dementia who underwent cardiac catheterization compared to those who did not receive CABG but did receive diagnostic cardiac ca theterization (Table 4 8) Model seven did not adjust for any covariates; model eight adjusted for all covariates and model nine adjusted for all covariates except zip code SES ; but this did not produce any statistically significant change Overall younge r patients are more likely to undergo CABG than older patients as well as patients with diabetes, strokes, obesity, CKD, CHF and COPD On the other hand females, those in the lower SES and with end stage renal disease were less likely to undergo CABG than those patients that were males and did not have the mentioned comorbidities For complete results see table 4 8.

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97 Table 4 8 Results of Multivariate Logistic Regression for secondary research question #3 modeling the probability of receiving CABG for tho se patients that received diagnostic cardiac catheterization. Model Seven (n= 6435 ) Odds Ratio (95% CI) CABG as Outcome for those who receive catheterization Model Eight (n= 5985 ) Odds Ratio (95% CI) CABG as Outcome for those who receive catheterization Model Nine (n= 6435 ) Odds Ratio (95% CI) CABG as Outcome for those who receive catheterization Dementia 0.64 (0.41 0.99) 0.74 (0.46 1.20) 0.74 (0.47 1.17) Age Category 65 74 75 84 85+ 3.21 (2.14 4.82) 2.83 (1.89 4.23) 1.00 3.18 (2.15 4.70) 2.85 (1. 93 4.20) 1.00 Gender Female Male 0.52 (0.43 0.63) 1.00 0.52 (0.43 0.62) 1.00 Ethnicity White non Hispanic Black non Hispanic Hispanic/Other 1.00 0.85 (0.55 1.32) 1.05 (0.81 1.36) 1.00 0.87 (0.58 1.32) 0.96 (0.75 1.21) Zip code SES* < $7750 0.59 (0.46 00.75) 0.92 (0.75 1.13) 1.00 Year 2006 2007 0.95 (0.80 1.12) 1.00 0.92 (0.79 1.08) 1.00 Hour of arrival to hospital Early Morning Morning Afternoon Night Unknown 1.01 (0.77 1.31) 1.00 0.96 (0.76 1.21) 0.74 (0. 57 0.96) 1.20 (0.75 1.92) 1.00 (0.77 1.92) 1.00 0.98 (0.79 1.22) 0.74 (0.58 0.95) 1.11 (0.71 1.73) Source of Admission Outside Hospital MD Ref Emergency Room MD Ref Other* 1.42 (0.47 4.34) 1.45 (0.51 4.17) 1.00 1.74 (0.58 5.22) 1.49 (0.52 4.23) 1.00 Pay Medicare Self Pay & Charity Other ** 0.93 (0.70 1.24) 1.22 (0.59 2.50) 1.00 0.91 (0.70 1.19) 0.98 (0.50 1.93) 1.00 Hypertension 1.05 (0.87 1.26) 1.02 (0.86 1.22) Diabetes Type 2 1.32 (1.10 1.58) 1.28 (1.08 1.52) Stroke 1.88 (1.33 2.65) 1.79 ( 1.29 2.49) Hyperlipidemia 0.92 (0.77 1.10) 0.89 (0.75 1.04) Ob esity 1.51 (1.15 1.99) 1.50 (1.15 1.96) Smoking 0.91 (0.71 1.16) 0.94 (0.75 1.18) Depression 1.16 (0.79 1.68) 1.18 (0.83 1.69) End Stage Renal Disease 0.37 (0.15 0.90) 0.34 (0.14 0.82) Chronic Kidney Disease 1.42 (1.11 1.82) 1.46 (1.16 1.84) Congestive Heart Failure 1.96 (1.63 2.36) 1.97 (1.66 2.34) COPD 1.39 (1.13 1.69) 1.38 (1.14 1.67) Chronic Alcohol abuse 1.06 (0.42 2.67) 0.99 (0.40 2.45) Zip Code Socio Economic Status * Other:Transfer from skilled nursing facility; court/law enforcement; information not available) * *Other (any other method of payment: Medicaid,commercial ins urance; ensation CHAMPUS; VA; Other State/Local Gov ernment ; Other.)

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98 4.6.2.3 Secondar y Question #3 Models ten through fifteen were run t o determine if there was a difference between the days to procedure (PCI or CABG) for STEMI patients with and without dementia (Tables 4 9, 4 10) M ode l s 10 12 evaluated same day PCI Model 10 calculated the probability of same day PCI for STEMI patients with and without dementia. Model 11 assessed the probability of same day PCI for those patients that received diagnostic cardiac catheterization with and without dementia M odel 12 is based on model ten bu t adjusts for all covariates of interest.

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99 Table 4 9 Results of Multivariate Logistic Regression models for secondary research question #3 modeling the probability of same day PCI for STEMI patients Model ten (n= 7791 ) Odds Ratio (95% CI) Same day PCI as Outcome Model Eleven (n= 6435 ) Odds Ratio (95% CI) Same day PCI as Outcome for those who receive catheterization Model Twelve (n= 7791 ) Odds Ratio (95% CI) Same day PCI as Outcome Dementia 0.34 (0.29 0.41) 0.93 (0.71 1.24) 0.53 (0.44 0.64) Age Category 65 74 75 84 85+ 2.25 (1.94 2.61) 1.87 (1.63 2.15) 1.00 Gender Female Male 0.97 (0.88 1.07) 1.00 Ethnicity White non Hispanic Black non Hispanic Hispanic/Other 1.00 0.66 (0.53 0.83) 0.98 (0.84 1.15) Zip code SES* < $7750 1.11 (0.96 1.28) 0.95 (0.84 1.07) Year 2006 2007 0.89 (0.81 0.99) 1.00 Hour of arrival to hospital Early Morning Morning Afternoon Night Unknown 0.85 (0.73 1.00) 1.00 0.95 (0.83 1.09) 0.79 (0.68 0.91) 0.83 (0.63 1.10) Sou rce of Admission Outside Hospital MD Ref Emergency Room MD Ref Other* 1.09 (0.60 1.98) 1.08 (0.61 1.89) 1.00 Pay Medicare Self Pay & Charity Other ** 1.03 (0.86 1.23) 1.03 (0.62 1.70) 1.00 Hypertension 0.94 (0.84 1.05) Diabetes Type 2 0.74 (0 .66 0.83) Stroke 0.54 (0.43 0.68) Hyperlipidemia 1.30 (1.18 1.44) Obesity 1.05 (0.86 1.29) Smoking 1.55 (1.32 1.82) Depression 0.70 (0.57 0.87) End Stage Renal Disease 1.39 (0.92 2.08) Chronic Kidney Disease 0.60 (0.52 0.69) Congestiv e Heart Failure 0.48 (0.43 0.53) COPD 0.66 (0.59 0.75) Chronic Alcohol abuse 1.16 (0.59 2.30) Zip Code Socio Economic Status *Other:Transfer from skilled nursing facility; court/law enforcement; information not available) * *Other (any other me thod of payment: Medicaid,commercial ins urance; ensation CHAMPUS; VA; Other State/Local Gov ernment ; Other.)

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100 Overall, if a patient had dementia they were less likely to receive PCI within the first twenty four hours than someone who d id not ha ve dementia ( OR 0.34, 95% CI 0.29 0.41) This was still statistically significant after adjusting for all covariates of interest. When potential confounders were adjusted being younger, hyperlipidemic and a smoker place d the patient at better odds of rec eiving same day PCI; while if the patient was Black/African Ameri can non Hispanic, hypertensive, had a stroke or had a history of stroke, depression, CKD, CHF and COPD they were less likely to receive same day PCI. M odel eleven was run for those who receiv e d diagnostic cardiac catheterization without adjusting for any covariates having dementia was not statistically significant for receiving same day PCI. To evaluate same day CABG, modes 13 15 were run Model 1 3 appraised the probability of same day CABG for STEMI patients with and without dementia compared to those STEMI patients with and without dementia who did not receive same day CABG Model 1 4 assessed the probability of same day CABG for those STEMI patients with and without dementia who received di agnostic cardiac catheterization compared to those STEMI patients with and without dementia who did not receive same day CABG a nd model 1 5 is based on model thirteen but adjusts for all covariates of interest; refer to table 4 10

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101 Table 4 10 Results of Multivariate Logistic Regression models for secondary research question #3 modeling the probability of same day CABG for STEMI patients. Model thirteen (n= 7791 ) Odds Ratio (95% CI) Same day CABG as Outcome Model fourteen (n= 6435 ) Odds Ratio (95% CI) Same day CABG as Outcome for those who receive catheterization Model fifteen (n= 7791 ) Odds Ratio (95% CI) Same day CABG as Outcome Dementia 0.4 5 (0.2 7 0.76) 0.871 (0.52 1.46) 0.69 (0.40 1.18) Age Category 65 74 75 84 85+ 3.50 (2.21 5.51) 2.94 (1.18 4.6 2) 1.00 Gender Female Male 0.50 (0.39 0.63) 1.00 Ethnicity White non Hispanic Black non Hispanic Hispanic/Other 1.00 0.82 (0.48 1.41) 1.17 (0.86 1.59) Zip code SES* < $7750 0.80 (0.59 1.07) 0.96 (0.74 1.24) 1.00 Year 2006 2007 1.05 (0.86 1.29) 1.00 Hour of arrival to hospital Early Morning Morning Afternoon Night Unknown 0.74 (0.53 1.03) 1.00 0.90 (0.69 1.19) 0.52 (0.37 0.73) 0.73 (0.41 1.27) Source of Admission Outside Hospital MD Ref Emergency Room MD Ref Other* 1.33 (0.38 4.63) 0.86 (0.26 2.83) 1.00 Pay Medicare Self Pay & Charity Other ** 1.13 (0.78 1.62) 1.27 (0.51 3.15) 1.00 Hypertension 1.01 (0.81 1.27) Diabetes Type 2 0. 98 (0.78 1.23) Stroke 1.60 (1.06 2.41) Hyperlipidemia 0.90 (0.73 1.11) Ob esity 1.38 (0.97 1.96) Smoking 0.84 (0.62 1.15) Depression 1.14 (0.72 1.79) End Stage Renal Disease 0.34 (0.08 1.44) Chronic Kidney Disease 0.79 (0.57 1.10) Cong estive Heart Failure 1.49 (1.18 1.87) COPD 1.38 (1.08 1.75) Chronic Alcohol abuse 0.60 (0.14 2.56) Zip Code Socio Economic Status *Other:Transfer from skilled nursing facility; court/law enforcement; information not available) * *Other (any oth er method of payment: Medicaid,commercial ins urance; ensation CHAMPUS; VA; Other State/Local Gov ernment ; Other.)

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102 Patients with dementia were much less likely to receive CABG within the first twenty four hours than someone who did not have dem entia (OR 0.45, 95% CI 0.27 0.76). However when potential confounders were adjusted for this effect was not statistically significant. Being younger, hyperlipidemic, having COPD or CHF placed the patient at better odds of receiving same day CABG; whereas if the patient was a female or was admitted at night, versus the morning, they were less likely to receive same day CABG. When model fourteen was run for those who received diagnostic cardiac catheterization without adjusting for any covariates, having dem entia was not statistically significant for receiving same day CABG. 4.6.2.4 Secondary Question #4 Models sixteen through nineteen were constructed to identify if having dementia affect ed the length of hospital stay for STEMI patients (Table 4 11) To b est evaluate this time dependent variable a Cox regression analysis was conducted only on STEMI patients with and without dementia who survived the hospital stay. Although Cox regression assumes that the hazards of the comparison groups are proportional, t his model fit s the data better than a logistic regression model. Model sixteen is unadjusted model seventeen

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103 adjusts for all covariates of interest and model eighteen adjusts for all variables except zip code SES In model 16 the hazard ratio assumed th at the exposure of STEMI patients to length of hospital stay is multiplicative of some underl ying hazard, in this case dementia The result showed that patients with dementia had longer length of hospital stay than patients without dementia (hazard ratio=0 .90, p= 0.0203) When all covariates of interest where added in model seventeen, the predictability of dementia became statistically insignificant (hazard ratio=1.0, p=0.9667) indicating that one of the covariates was highly correlated with the dementia fa ctor. However when the correlations were analyzed in the basic model 2 there were no strong correlations of any one variable with dementia After adjusting for all variables of interest in model 17, p atients 75 84 years of age and Black/African American non Hispanics had a significantly lower hazard of being released from the hospital on any day of their stay than those patients without dementia (Table 4 11); also those who arrived at night had significantly lower hazard of being discharged (hazard ratio =0.928, p=0.0352) compared to those that arrived in the morning hours. Comorbidities such as diabetes, current or history of stroke, hyperlipidemia, obesity, smoking, depression, chronic kidney disease, congestive heart

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104 failure, chronic obstructive pulmon ary disease and chronic alcohol ab users also had lower hazard of being released from the hospital than those without those conditions. However, patients with hyperlipidemia and current or history of smoking had significantly higher hazard of being discharg ed from the hospital than those without hyperlipidemia or positive smoking status When model eighteen was run without adjusting for SES, the re were no changes from model seventeen indicating that SES was not a confounder on the previously stated associati ons.

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105 Table 4 11 Results of Cox r egression analysis for secondary research question #4 modeling length of hospital stay for STEMI patients Model sixteen (n=7422) Hazard Ratio (p) for STEMI survivors Model seventeen (n= 7422 ) Hazard Ratio (p) for STEMI s urvivors Model eighteen (n= 7422 ) Hazard Ratio (p) for STEMI survivors Dementia 0.898 (p=0.0203) 0.998 (p=0.9667) 1.002 (p= 0.9608 ) Age Category 65 74 75 84 85+ 1.002(p=0.9601) 0.914 (p=0.0147) 1.00 0.994 (p=0. 8784 ) 0.905 (p=0. 0054 ) 1.00 Gender Femal e Male 0.993 (p=0.7672) 1.00 0.996 (p= 0. 8688) 1.00 Ethnicity White non Hispanic Black non Hispanic Hispanic/Other 1.00 0.877 (p=0.0229) 1.028 p=(0.4718) 1.00 0.873 (p=0.0161) 1.026 (p= 0. 4906) Zip code SES* < $7750 1.016 ( p= 0.6502) 1.036 (p=0.2566) 1.00 Year 2006 2007 0.995 (p=0.8211) 1.00 0.997 (p=0.8905) 1.00 Hour of arrival to hospital Early Morning Morning Afternoon Night Unknown 1.007 (p=0.8524) 1.00 0.991 ( p= 0.7839) 0.928 (p=0.0352) 1.018 (p=0.8092 1.007 (p=0 .8555) 1.00 0.986 (p=0.6784) 0.931 (p=0.0391) 1.054 (p=0.4424) Source of Admission Outside Hospital MD Ref Emergency Room MD Ref Other* 0.993 (p=0.9666) 1.029 (p=0.8426) 1.00 0.934 (p=0.6514) 1.028 (p=0.8424) 1.00 Pay Medicare Self Pay & Charity Othe r ** 0.967 (p=0.4455) 0.818(p=0.1043) 1.00 0.989 (p=0.7916) 0.860 (p=0.1818) 1.00 Hypertension 0.973 (p= 0. 3110) 0.986 (p=0.6015) Diabetes Type 2 0.914 (p=0.0012) 0.916 (p=0.0011) Stroke 0.683 (p<0.0001) 0.681 (p<0.0001) Hyperlipidemia 1.122 (p<0 .0001) 1.125 (p<0.0001) Obesity 0.894 (p=0.0201) 0.901 (p=0.0277) Smoking 1.110 (p=0.0054) 1.104 (p=0.0060) Depression 0.843 (p=0.0012) 0.840 (p=0.0007) End Stage Renal Disease 0.841 (p=0.1413) 0.834 (p=0.1186) Chronic Kidney Disease 0.728 (p<0.0 001) 0.717 (p <0.0001) Congestive Heart Failure 0.509 (p<0.0001) 0.506 (p<0.0001) COPD 0.809 (p<0.0001) 0.806 (p<0.0001) Chronic Alcohol abuse 0.697 (p=0.0242) 0.712 (p=0.0280) Zip Code Socio Economic Status **Other:Transfer from skilled nursing fa cility; court/law enforcement; information not available) ***Other (any other method of payment: Medicaid,commercial insurance;

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106 4.7 Sensitivity Analysis A sensitivity analysis was carr ied out to determine if it is appropriate or not to use the broad definition of dementia compared to the strict or more Table 4 12 compares the three models used. All models are based on 7,791 observations with p roxy data for SES modeling the probability of receiving diagnostic cardiac catheterization. General m odel two was used as the comparison since it used the broad definition of dementia. Model 19 used the same 7,991 observations as model two but the definit ion of dementia was restricted to only those that had looked at those patients that had The results obtained from all three models (refer to table 4 12) show ed tha t there w ere no statistically significant difference s between using the broad disease when testing diagnostic cardiac catheterization as the outcome However when exposure is limi diagnosis, the effect of dementia is slightly stronger (OR 0.38, 95% CI 0.28 0.52) compared to the effect for all demented patients (OR 0.41, 95% CI 0.34 0.50).

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107 Table 4 12 Results of sensitivity analysis evalua ting the broad definition of Model two (n=7791) Odds Ratio (95% CI) Diagnostic Cardiac Catheterization as Outcome Where Exposure is Dementia Model Nineteen (n=7791) Odds Ratio (95% CI) Diagnostic Cardiac Catheterization as Outcome Where Exposure Dementia AD Model twenty (n=7791) Odds Ratio (95% CI) Diagnostic Cardiac Catheterization as Outcome Where Exposure is Dementia non AD Dementia 0.41 (0.34 0.50) 0.38 (0.28 0.52) 0.44 (0.35 0.56) Age Category 65 74 75 84 85+ 3.90 (3.31 4.58) 3.0 0 (2.59 3.48) 1.00 4.30 (3.67 5.04) 3.20 (2.77 3.70) 1.00 3.81 (3.23 4.49) 2.96 (2.55 3.44) 1.00 Gender Female Male 0.69 (0.61 0.77) 1.00 0.68 (0. 60 0.76) 1.00 0.67 (0.59 0.76) 1.00 Ethnicity White non Hispanic Black non Hispanic Hispanic/Other 1.00 0.55 (0.43 0.71) 1.06 (0.88 1.28) 1.00 0.54 (0.42 0.69) 1.07 (0.88 1.29) 1.00 0.55 (0.43 0.71) 1.08 (0.89 1.31) Zip code SES* < $7750 1.02 (0.87 1.21) 0.91 (0.78 1.05) 1.00 1.00 (0.85 1.18) 0.89 (0.77 1.03) 1.00 1.02 (0.86 1.21) 0.92 (0.79 1.07) 1.00 Year 2006 2007 0.94 (0.84 1.05) 1.00 0.95 (0.84 1.06) 1.00 0.95 (0.84 1.07) 1.00 Hour of arrival to hospital Early Morning Morning Afternoon Night Unknown 0.83 (0.69 1.00) 1.00 0.91 (0.77 1.08) 0.78 (0.66 0.93) 0.82 (0.59 1.15) 0.82 (0.68 0.99) 1.00 0.90 (0.77 1.07) 0.79 (0.67 0.93) 0.82 (0.59 1.14) 0.83 (0.68 1.00) 1.00 0.93 (0.78 1.09) 0.80 (0.67 0.95) 0.81 (0.58 1.13) Source of Admission Outside Hospital MD Ref Emergency Room MD Ref Other** 1.08 (0.53 2.22) 0.99 (0.50 1.96) 1.00 1.11 (0.54 2.25) 0.98 (0.50 1.93) 1.00 1.04 (0.49 2.21) 0.94 (0.46 1.92) 1.00 Pay Medicare Self Pay & Charity Other *** 1.21 (0.97 1.50) 1.13 (0.60 2.12) 1.00 1.20 (0.97 1.50) 1.14 (0.61 2.14) 1.00 1.20 (0.96 1.49) 1.16 (0.61 2.21) 1.00 Hypertension 1.02 (0.89 1.16) 1.03 (0.90 1.17) 1.01 (0.88 1.15) Diabetes Type 2 0.90 (0.79 1.03) 0.90 (0.79 1.02) 0.89 (0.78 1.02) Stroke 0 .61 (0.48 0.77) 0.60 (0.47 0.76) 0.60 (0.47 0.77) Hyperlipidemia 1.51 (1.34 1.70) 1.52 (1.35 1.70) 1.47 (1.3 0 1.65) Ob esity 1.51 (1.15 1.99) 1.52 (1.16 2.00) 1.57 (1.18 2.07) Smoking 1.70 (1.38 2.11) 1.72 (1.39 2.12) 1.73 (1.39 2.14) Depression 0.71 (0 .56 0.89) 0.67 (0.53 0.84) 0.72 (0.57 0.92) End Stage Renal Disease 0.87 (0.56 1.33) 0.87 (0.56 1.33) 0.86 (0.56 1.32) Chronic Kidney Disease 0.61 (0.52 0.71) 0.61 (0.52 0.72) 0.60 (0.51 0.70) Congestive Heart Failure 0.64 (0.57 0.73) 0.64 (0.57 0.72) 0 .64 (0.57 0.73) COPD 0.71 (0.62 0.82) 0.70 (0.61 0.81) 0.69 (0.60 0.79) Chronic Alcohol abuse 1.14 (0.46 2.81) 1.14 (0.46 2.80) 1.62 (0.56 4.71) Zip Code Socio Economic Status **Other:Transfer from skilled nursing facility; court/law enforcement; info rmation not available) ***Other (any other method of payment: Medicaid,commercial insurance; patients with dementia; model 19 had 190 AD patients, and model 20 had 4 01 dementia non AD patients.

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108 CHAPTER 5 DISCUSSION 5.1 Findings R esults obtained indicate that demented STEMI patients are less likely to receive diagnostic cardiovascular catheterizations than non demented patients even after controlling for potential confounding factors This finding is consistent with th at from Sloan et al. (2004) ( 78 ) R esults from this study indicate that dement ed patients are 0.4 times less likely to receive diagnostic cardiac catheterization than non demented patients while Sloan et al. (2004) ( 78 ) estimated the risk ratio at 0.5 The 95% confidence intervals for both studies overlapped (0.34 0.50 vs 0.47 0.55). Models two and three also show ed that being female or Black/African American non Hispanic reduced the odds of receiving diagnostic cardiac catheterization compared to males and those White non Hispanic; the AHA and many studies in the literature support this result ( 3 7 66 8 3 )

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109 Black African American non Hispanics were 0.5 times less likely to receive diagnostic cardiac catheterization than White non Hispanics. Yet, the odds of receiving PCI or CABG for those Black African American non Hispanics that did receive diagnost ic cardiac catheterization became statistically insignificant once patient and hospital factors were taking into account. Nonetheless, when measuring the probability of receiving same day PCI, Blacks were 0.7 times less likely to have same day PCI than Whi tes. Similar results were obtained in earlier analysis done by Pathak and Strom (2008) ( 66 ) Ar riving to the hospital at night also seems to place patients at worse odds of receiving diagnostic cardiac catheterization The analysis also suggests that being admitted to the hospital at night places patients at worse odds to receive treatment (PCI or C ABG) within the first 24 hours than those who arrived in the morning. A rriving at night was also associated with hav ing longer hospital stay than patients who arrived in the morning Studies show that arriving at night or off hours are associated with high er in patient mortality and longer time to treatment ( 84 ) When the socio economic variable was not accounted for while evaluating the use of diagnostic cardiac catheterizations among STEMI patients the only variable affected was diabetes; however the effect was marginal giv en that the upper confidence interval was 0.99 E arlier studies showed that cultural

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110 factors are a stronger indication of diabetes outcomes ( 85 ) than SES but most current l iterature indicate that patients from lower SES have a much higher and disp roportionate prevalence of diabetes ( 86 88 ) Some studies suggest that measuring a combination of SES factors can be a more sensitive method to measure outcome disp arities. In this study SES was directly measured by the proxy of mean zip code income for each observation in the dataset and it was also indirectly measured by controlling for type of payment used in the hospital; however the type of payment used was not a statistically significant variable for any of the results obtained Regardless of accounting or not for SES, STEMI patients with comorbidities such as having a stroke or having history of a stroke, having diabetes, CKD, CHF COPD and a diagnosis of dep ression made them less likely to receive diag nostic cardiac catheterizations This may be partially explained by physical reasons; COPD or CHF patients may not be able to tolerate supine positions without undergoing general anesthesia and thus may be more likely to receive alternative reperfusion treatments and some patients with advanced chronic kidney disease may not tolerate the use of any contrast in diagnostic cardiac catheterization. The results of table 4 6 indicate that patients who were younger o bese, hyperlipidemi c smokers or having had history of being smokers were more

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111 likely to receive diagnostic cardiac catheterizations. However these characteristics were not statistically significant for receiving PCI after undergoing cardiac catheterizatio n. In contrast smokers who were catheterized were more likely to receive CABG than non smokers who did receive catheterization. This may be explained by the smoker paradox Studies have demonstrated tha t STEMI patients who smoke have better myocardial p erfusion than non smoker STEMI patients after undergoing myocardial re perfusion ( 89 ) The results obtained in this study suggest that smokers who were catheterized were more likely to rec eive CABG than PCI ; this difference could be dependent on the number of vessel damage the STEMI smokers presented compared to non smoker STEMI patients. After controlling for patient and hospital factors, those older than 85 years of age were less likely to receive diagnostic cardiac catheterization than younger patient s. Nonetheless f rom the 50% of patients over 85 years of age who did receive diagnostic cardiac catheterization, these were more likely to receive PCI than the younger cohorts who receive d diagnostic cardiac catheterization Since 2004, the American Heart Association Practice Guidelines for STEMI patients have indicated primary PCI as first line of treatment for STEMI patients (Class I for those younger than 75 years of age and Class IIa in STEMI patients older than 75 years ) ( 4 68 ) thus these results suggest that for the years 20 0 6 2007 the gui delines were met for half of the patients over 85 years of age living in Florida at the time of their

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112 STEMI Nevertheless, patients 65 74 years old were 3.2 times more likely to undergo CABG than those older than 85. Although there may be medical and/or an atomical reasons for this outcome, the ACC/AHA Practice Guidelines have suggested that this may be due to surgeons coming under public scrutiny with regards to mortality rates ( 4 ) There was no statistically significant difference in the use of PCI between non demented and demented patients who had already under gone diagnostic cardiac catheterizatio n. Individuals from lower income areas or those with end stage renal disease seem to receive more PCI than their counterparts after initial diagnostic catheterization A negative disparity in receiving PCI after initial catheteriz ation was observed in pati ents with a diagnosis of diabetes, stroke, congestive heart failure and COPD after adjustment for patient and hospital factors. Female patients were 0.7 times less likely to receive diagnostic cardiac catheterization than males after controlling for pote ntial confounders. Yet if they were catheterized, women were 40% more likely to receive PCI than men. Opposite results were reported by Hirakawa et al. (2006) ( 79 ) ; their study looked at the effect of emergency PCI on in hospital mortality in elderly patients with AMI an d found that female patients received fewer PCI s. Just like Sloan et al. ( 78 ) H irakawa et al. ( 79 ) looked at all AMI instead of just

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113 STEMI, therefore their results are less specific than those obtain in this study. R esults from this study suggest that there was still a disparity by gender for more aggressive therapy; females were 0.5 times less li kely than males to undergo CABG after receiving diagnostic catheterization and 0.5 times less likely to receive it within the first 24 hours after hospital admission than males Demented STEMI patients who underwent diagnostic cardiac catheterization wer e less likely to receive CABG than those non demented ; however the effect disappeared when covariates were added to the model. CABG results from this study contrasted with those of Sloan et al. (2004) who found a statistically significant difference betwee n demented and non demented patients even after adjustment. This may be attributable to several factors including the different potential confounding factors controlled for in both studies. Th e difference may also account to the fact that this study specif ically evaluated STEMI patients while Sloan e t al. evaluated acute myocardi al infarctions (AMI) in general.

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114 When evaluating the AHA guidelines for the timing of PCI, older patients were much less likely to receive same day PCI or same day CABG than younge r patients. This result is consistent with that obtained from Pathak & Strom (2008) ( 66 ) for the years 2001 2005 in Florida. However, it is important to note that patients with prior CABG, females and the elderly have a higher risk of mortality if the CABG is performed early after the STEMI which may explain this disparity. The AAC/AHA Guidelines fro m 2004 indicate that STEMI patients have an elevated mortality from CABG if performed in the first 3 to 7 days after the MI ( 4 ) After adjusting for all variables of interest, socio economic disparities were only statistically significant for those patients undergoing CABG. A study by Bernheim et al. (2007) ( 67 ) showed a trend towards lower SES groups receiving fewer quality of care measures, however they did not report measures for CABG. A Cox regression analysis was performed to evaluate the length of hos pital stay for STEMI patients with and without dementia. When patient factors were not added into the model, patients without dementia had significantly shorter length of hospital stay than patients with dementia. However when other factors were added into the model, this effect disappeared Further analysis is needed to determine if there is a n interaction effect of some comorbidities with dementia.

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115 In order to clarify if the dementia definition used in this study was appropriate or if a stricter definiti should have been used, a sensitivity analysis of the definition was conducted based on the main study model. The results obtained demonstrate that when exposure is limited onger than when the general definition is implemented. However, overall using the general definition did not statistically affect the outcome, in this case diagnostic cardiac catheterization. These results suggest that the disparity in outcomes for demente d patient s is dependent on the perception of medical personnel in the emergency department towards those with dementia

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116 5.2 S trengths and Limitations of the Study One of the main strengths of this study is that it is based on the comprehensive populat with little information bias However it does bring in some uncontrollable limitations. First, the dataset includes only patients admitted to high volume PCI Florida hospitals with a STEMI diagnosis, th erefore external validity is not applicable outside this strict definition. U nderreporting of risk factors is also expected given the nature of the medical emergency under study (STEMI) and the coding procedures used consequently some nondifferential m isclassification may exist that may bias results toward the null It is also impossible to determine how dementia was measured by the hospital staff. With this data temporality cannot be determined, whether the dementia code was written in the chart when t he patient was admitted to the hospital affecting directly the outcome dependent on the exposure; or if dementia was coded later during the hospitalization after interviewing the patient or the family further, in this case not having affected the outcome d irectly. The underlying severity of the coronary condition of each of these patients cannot be measured directly and as a result this study does not adjust for it nor does it account for previous cardiovascular procedures performed. Some

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117 patients with m ulti vessel disease or who had previous interventions may not have received PCI because it was not the optimal treatment while CAB G was. On the other hand patients with low left ventricular function, hemodinamically unstable or with high risk comorbiditie s may have had further indication s to wait until stabilization to proceed with CABG T his limitation was not accounted for when days to procedure was measured. It is measured as a dic hotomous variable, the procedure was either performed in the first 24 hours or it was not; the purpose was to capture the adherence to the ACC/AHA STEMI guidelines for PCI in STEMI patients. The use of average per capita income by zip code as proxy for so cio economic status is an imperfect surrogate for individual level data SES is an ecological variable therefore it only measures income per residential area; it is not a true estimate of the financial condition of the patients. A n other frequently used SES measure is the method of hospital payment which was a lso adjusted for in this study; however this measure is also limited and does not provide significant information given that most of the elderly population has Medicare. When comorbidities were adju ste d the potential for over adjustment may be present For example, d epression is a p r odromal symptom for dementia.

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118 Obesity, hypertension, hyperlipidemia, depression and diabetes are all components of the metabolic syndrome, thus adjustment as a group may ha ve yielded a different outcome. T here may be some unmeasured residual confounding by hospital level that was not accounted for in this study E ven though age was a variable that was adjusted for in the study, it is well known that on average females outlive males therefore some unmeasur ed effect may be left unaccounted for Last but certainly not least, the data used does not contain specific codes for treatment refusal from the patients their families or health care surrogates/pro xies which may influence the results in this study It is very common for very elderly patients in Florida to have resuscitate (DNR) forms, which specify for CPR to be withheld or withdrawn in case of a myocardial infarction ; they may have advance d directives, which specify their wishes upon a medical emergency; or they may have a living will in which they specify their healthcare wishes that may include to not receive therapy By Florida law, p atients with advanced dementia who do not have advance d directives or DNRs, their spouse or next in kin automatically acquire the legal authorized representative status and they may make the medical decisions for the demented patient

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119 O ther stud ies known ( 41 78 79 90 ) ha ve measured the effect of dementia on the use of PCI as a secondary outcome A similar study to the one presented here was done by Sloan et al. in 2004; they measured the cardiovascular outcomes of Medicare beneficiaries but the population in that study included all kinds of Acute Myocardial Infa rctions. This study uses a more specific approach in accordance with the ACC/AHA guidelines; PCI is specifically indicated for STEMI patients not non STEMI. Thus despite all the mentioned limitations, this is the first known study to date that has directly measured the effect of dementia on the use of diagnostic cardiac catheterization among STEMI patients in Florida

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120 5. 3 Future Research Further studies are needed to measure the impact of dementia on the quality of medical care received by dementia patien ts especially in emergency settings The need to include ways of measuring the legal aspect of the medical decisions for demented patients in epidemiological studies also requires further evaluation A closer look at treatment disparities for demented e thnic minorities and women is urgently needed in order t o adequately allocate resources and narrow the disparit ies Evaluating other exposures within different groups by ethnicity, gender or medical condition in this cohort may better explain some of the results. For example knowing which women were previously exposed to hormone replacement therapy and who were not may enhance the results obtained by explaining the contrasting results for women undergoing catheterization and PCI versus CABG for both dement ed and non demented female patients Enhancing the analysis performed in this study by perhaps including hospital level effects and geographical patterns in the statistical analysis may be able to determine trends that can help decrease the gap in treatm ent disparities in Florida An appraisal of medications and the temporality of the diagnostic

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121 codes received by these patients may also help to better understand the results Even though the AHA has helped improved the outcomes for STEMI patients in the l ast few years, it still does not have specific guidelines or algorithms for emergency personnel to follow when encountering elderly patients; therefore a national appraisal of disparities in treatment is urgently needed to not only narrow the gaps in treat ment for elderly patients but those with dement ia as well. 5.4 Conclusion This study provides evidence that dementia is a limiting factor for receiving diagnostic cardiac catheterization after a STEMI. Results from this research coincide with many report ed in the literature of outcomes research; w omen, the elderly and Black African American non Hispanics are still subject to disparities in this case diagnostic cardiac catheterization

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131 80. Petersen LA, Normand S LT, Druss BG, Resenheck Ra. Process of Care and Outcome after Acute Myocardial Infarction for Patients with Mental Illness in the VA Heal th Care System: Are There Disparities? HSR: Health Services Research. 2003 February 2003;38(1):41 63. 81. Landon BE, Schneider EC, Normand S LT, Hudson Scholle S, Pawlson L, Epstein AM. quality of Care in Medicaid Care and Commercial Health Plans. JAMA. 20 07;298(14):1674 81. 82. Smith T, Smith B. Survival Analysis And The Application Of Cox's Proportional Hazards Modeling Using SAS. In: SAS Institute Inc. C, NC, USA., editor. Proceedings of the Twenty Sixth Annual SAS Users Group International Conference; April 22 25, 2001; Long Beach Convention Center; Long Beach, California2001. 83. Pathak Barnett E, Strom JA. Percutaneous Coronary Intervention, Comorbidities, and Mortality among Emergency Department Admitted ST Elevation Myocardial Infarction Patients i n Florida. Journal of Interventional Cardiology. 2010;23(3):205 15. 84. Krth P, Zeymer U, Gitt A, Jnger C, Wienbergen H, Niedermeier F, et al. Influence of presentation at the weekend on treatment and outcome in ST elevation myocardial infarction in hosp itals with catheterization laboratories Clinical Research in Cardiology. 2008;97(10):742 7. 85. Stern MP, Rosenthal M, Haffner SM, Hazuda HP, Franco LJ. Sex Difference in the Effects of Sociocultural Status on Diabetes and Cardiovascular Risk Factors in M exican Americans the San Antonio Heart Study. American Journal of Epidemiology. 1984;120(6):834 51. 86. Smith J. Diabetes and the Rise of the SES Health Gradient. In: Research NBoE, editor. NBER Working Paper No 12905. Cambridge, MA NBER Program(s): AG HC HE 2007. 87. Everson SA, Maty SC, Lynch JW, Kaplan GA. Epidemiologic evidence for the relation between socioeconomic status and depression, obesity, and diabetes. Journal of Psychosomatic Research. 2002;53(4):891 5.

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133 APPENDICE S

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134 A ppendix 1. Summary of recommendations from the American College of Cardiology and the American Heart Association for the management of STEMI, pg.e104 ( 4 ) Figure 7. Major components of time delay between onset of symptoms from ST elevation MI and restoration of flow in the infarct artery. Plotted sequentially from left to right are shown the tim e for patients to recognize symptoms and seek medical attention, transportation to the hospital, in hospital decision making, and implementation of reperfusion strategy, in time for restoration of flow once the reperfusion strategy has been initiated. The time to initiate fibrinolytic therapy is the "door to needle" (D N) time; this is followed by the period of time required for pharmacologic restoration of flow. More time is required to move the patient to the catheterization laboratory for a percutaneous coronary interventional (PCI) procedure, referred to as the "door to balloon" (D B) time, but restoration of flow in the epicardial infarct artery occurs promptly after PCI. At the bottom are shown a variety of methods for speeding the time to reperfusion along with the goals for the time intervals for the various components of the time delay. Cath= catheterization; PCI = percutaneous coronary intervention; min = minutes; ECG = electrocardiogram; MI = myocardial infarction; Rx = therapy. *These bar graphs a re meant to be semiquantitative and not to scale. Modified with permission from Cannon et al. J Thromb Thrombol 1994;1:27 34 (180).

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135 A ppendix 2. App lying Classification of Recommendations and Level of Evidence pg.e87 ( 4 )

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136 A ppendix 3 ICD 9 CM Coding Use for Comorbity HYPERTENSION: 401.0 is malignant essential HTN, 401.1 is benign e ssential HTN and 401.9 = essential HTN unspecified 403 = Hypertensive chronic kidney disease 403.0= Malignant 403.01= Malignant 403.10 = Benign 403.11 = Benign 403.9 =Unspecified 403.90 =Unspecified 403.91 =Unspecified DIABETES: 250 Diabetes mel litus 250.0 Diabetes mellitus without mention of complication [0 3] Diabetes mellitus without mention of complication or manifestation classifiable to 250.1 250.9 Diabetes (mellitus) NOS 250.1 Diabetes with ketoacidosis [0 3] Diabetic: acidos is without mention of coma

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1 37 ketosis without mention of coma 250.2 Diabetes with hyperosmolarity [0 3] Hyperosmolar (nonketotic) coma 250.3 Diabetes with other coma [0 3] Diabetic coma (with ketoacidosis); Diabetic hypoglycemic coma Insulin coma NOS 2 50.4 Diabetes with renal manifestations [0 3] 250.5 Diabetes with ophthalmic manifestations [0 3] 250.6 Diabetes with neurological manifestations [0 3] 250.7 Diabetes with peripheral circulatory disorders [0 3] 250.8 Diabetes with other specified ma nifestations [0 3] Diabetic hypoglycemia NOS ; Hypoglycemic shock NOS 250.9 Diabetes with unspecified complication [0 3] STROKE: For Stroke codes: 430 Subarachnoid hemorrhage 431 Intracerebral hemorrhage 432.0 Nontraumatic extradural hemorrhage, Nont raumatic e pidural hemorrhage 432.1 Subdural hemorrhage, Subdural hematoma, nontraumatic 432.9 Unspecified intracranial hemorrhage, Intracranial hemorrhage NOS 433.0 433.01 Basilar artery

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138 433.1 433.10 Carotid artery 433.2 433.20 Vertebral artery 433.3 433.30 Multiple and bilateral 433.8 433.81 Other specified precerebral artery 433.9 433.91 Unspecified precerebral artery, Precerebral artery NOS 434.00 434.01 thrombotic 434.10 434.11 Cerebral embolism 434.91 is general or stroke in evol u tion, cerebrovascular accident 435.0 Basilar artery syndrome 435.1 Vertebral artery syndrome 435.2 Subclavian steal syndrome 435.3 Vertebrobasilar artery syndrome 435.8 Other specified transient cerebral ischemias 435.9 Unspecified transient ce rebral ischemia, progressive 436.0 apoplectic 997.02 Iatrogenic cerebrovascular infarction or hemorrhage Postoperative stroke V12.54 Transient ischemic attack (TIA), and cerebral infarction without residual deficits HYPERLIPIDEMIA:

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139 272.2 Hyperlipid emia is defined as high lipids, h ypercholesterolemia and hypercholesterolemia with hyperglycemia endogenous: 27 2 272.0 272.1 272.2 272.3 272.4 OBESITY: 278.00 re presents obesity and overweight SMOKER: 305.1 for tabacco use disorder a nd V15.82 for hx of tabacco use ALCOHOL ABUSE : 303.9 303 303.00 303.01 303.02 303.03 303.9 303.90 303.91 303.92 303.93 which stands fo r Chronic alcoholism/Dipsomania V 11.3 V79.1 V11.3 for alcoholism DEPRESSION: V79 300.4 Dysthymic disorder 311 depr ession NOS Major depresive disorder/recurrent episode : 296.2 296.20, 296.21 296.22, 296. 23, 296.24 296.25 296.26 296.3, 296.30 296.31, 296.32 296.33 296.34 296.35 296.36 Bipolar I disorder, most recent episode (or current) depressed

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140 296.5 296 .50 296.5, 296.52 296 .53 296.54 296.55 296.56 Chronic Kidney Disease (CKD): 403 Hypertensive chronic kidney disease [0 1] 403.0 Malignant 403.1 Benign 403.9 Unspecified 585 Chronic kidney disease (CKD): 585.1 Chronic kidney disease, Stage I 5 85.2 Chronic kidney disease, Stage II (mild) 585.3 Chronic kidney disease, Stage III (moderate) 585.4 Chronic kidney disease, Stage IV (severe) 585.5 Chronic kidney disease, Stage V 585.9 Chro nic kidney disease, unspecified End Stage Renal Disease ( ESRD): 585.6 End stage renal disease Chronic kidney disease, sta ge V requiring chronic dialysis Congestive Heart Failure (CHF): 402.0 402.00 402.01 402.1 402.11 402.9 402.90 402.91

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141 Hypertensive Heart Disease 404 Hypertensive heart and chronic kidney disease [0 3] 404.0 Malignant 404.1 Benign 404.9 Unspecified 428.0 Congestive heart failure, unspecified 428.1 Left heart failure (Acute edema of lung with hea rt disease NOS or heart failure Acute pulmonary edema with heart disease NOS or hear t failure Cardiac asthma Left ventricular failure) 428.9 Heart failure, unspecified Cardiac failure NOS, Heart failure NOS, Myocardial failure NOS, Weak heart COPD: Chronic Obstructive Pulmonary Disease: 490 Bronchitis not specified as acute or chronic 491 Chronic Bronchitis 491.0 491.1 491.2 Obstructive chronic bronchitis 491.20 Without exacerbation / Emphysema with chronic bronchitis 491.21 With (acute) exacerbation / Acute exacerbation of chronic obstructive pulmonary disease [COPD] Decompensa ted chronic obstructive pulmonary disease [COPD]

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142 Decompensated chronic obstructive pulmonary disease [COPD] with exacerbation 491.22 With acute bronchitis 492 Emphysema 492.0 492.8 493 Asthma 493.0 493.00 493.01 493.02 493.1 493.10 493.11 493.12 493.2 493.20 493.21 493.22 493.9 493.90 493.91 493.12 494 Bronchiectasis 494.0 494.1 495 Extrinsic Allergic alveolitis 495.0 495.1 495.2 495.3 495.4 495.5 495.6 495.7 495.8 495.9 496 Chronic Airway Obstruction, not elsewhere classified