Title: Survival in South Asian and White European patients after acute myocardial. 1. Diabetes Research Centre, University of Leicester, Leicester, UK

Transcription

1 Title: Survival in South Asian and White European patients after acute myocardial infarction: a UK historical cohort study Nitin N Gholap 1, Kamlesh Khunti 1, 4, Melanie J Davies 1,4, Danielle H Bodicoat 1 4, Iain B Squire 2,3 1. Diabetes Research Centre, University of Leicester, Leicester, UK 2. Department of Cardiovascular Sciences, University of Leicester, Leicester, UK 3. Leicester NIHR Biomedical Research Unit in Cardiovascular Disease, Glenfield Hospital, Leicester, UK 4. Leicester Clinical Trials unit, University of Leicester, Leicester Diabetes Centre, Leicester, UK Address for correspondence: Dr Nitin N Gholap Leicester Diabetes Centre Leicester General Hospital Leicester LE54PW ng94@le.ac.uk Tel: Keywords: myocardial infarction, survival, South Asian Word count:

2 ABSTRACT: Objective: To compare survival following acute myocardial infarction (AMI) in a large cohort of White European and South Asian patients from a contemporary multi-ethnic UK population. Methods: Retrospective, cohort study of 4111 (N=730, 17.8 % of South Asian ethnicity) consecutive patients, admitted to a tertiary coronary care centre in UK with AMI between October 2002 September The association of all- cause mortality with White European and South Asian ethnicity was assessed using Cox regression analysis. Results: Compared to White European, South Asian patients were on average younger (62.0 vs years, p < 0.005) and had higher prevalence of diabetes (39.7% vs. 16.1%, p < 0.005) and higher mean admission plasma glucose levels (10.1mmol/L vs. 8.5mmol/L, p< 0.005). During follow-up (median 912, range 1 to 2556, days), crude mortality rate was 22.5% in South Asian and 25.9% in White European patients (p=0.054). South Asian ethnicity did not show univarite (Hazard Ratio (HR) 0.85 ( ) or multivariate (HR, 1.04 (0.83, 1.31)) association with mortality. Findings were similar for mortality at 30 days and one year and in patients who survived to discharge. On interaction analysis, the association between admission glucose and overall mortality risk was weaker in South Asian compared with White European patients (HR 0.96 ( )). Conclusion: In this contemporary cohort, adjusted survival following AMI was similar for South Asian and White European patients in the UK, regardless of high prevalence of cardiovascular risk factors including diabetes in the South Asian population. 2

3 Key Questions: What is already known about this topic? Mortality related to coronary heart disease (CHD) is high in South Asian (SA) populations in the UK. It is unclear if this is due to high incidence of CHD or high case fatalities following manifest CHD, especially acute myocardial infarction (AMI). What does this study add? Regardless of high prevalence of cardiovascular risk factors including diabetes in the SA population, adjusted survival following AMI is similar for SA and White European (WE) patients in the UK. High CHD mortality in SA patients in the UK does not appear to be due to high case fatality following AMI. How might this impact on clinical practice? Addressing high prevalence of risk factors for CHD, especially diabetes through prevention, early detection and management is the key to tackle the premature CHD in SA population in the UK. 3

4 INTRODUCTION People of South Asian (SA) (countries of the Indian subcontinent, originating from India, Pakistan, Sri-Lanka, Bangladesh and Nepal) origin constitute important ethnic minority groups in many parts of the world outside South Asia. In the UK, SA population is the largest ethnic minority group, comprising over 4% of the total population (Census 2011). Many migrant SA populations show higher coronary heart disease (CHD) prevalence and mortality rates compared with native populations, a phenomenon demonstrated in several countries including Canada,[1] Singapore,[2] South Africa,[3] and the UK.[4-6] Further, in Canada,[7,8] and the UK,[4,5] CHD presents at younger mean age in migrant SA compared to indigenous populations. While CHD appears to be more prevalent in migrant SA compared to native populations, the influence of ethnicity on prognosis for patients with CHD is less clear. While some studies have suggested higher case-fatality rates following acute myocardial infarction (AMI) in migrant SA, compared to white European (WE), patients in the UK,[9,10] others from the UK[5,11-13] and Canada[8,14] have suggested similar[11,12,14,15] or better[5,8,13] adjusted survival for these ethnic groups in this setting. Abnormalities of glucose metabolism have strong associations with adverse prognosis for patients with CHD and are highly prevalent in SA populations. For patients with AMI, a prior diagnosis of diabetes is associated with increased risk of both mortality and morbidity.[16] Moreover, acutely elevated blood glucose, stress hyperglycaemia, is common among patients hospitalised after AMI and is also associated with adverse outcomes,[17,18] irrespective of previous diabetes status. Several studies have suggested the high prevalence of CHD, in particular AMI, in SA minority populations is due to greater prevalence of traditional CHD risk factors, in particular diabetes.[10,19] 4

5 The aim of the current analysis was to compare survival following AMI in a large cohort of WE and SA patients drawn from a multi-ethnic population in the UK, in the contemporary era of early coronary reperfusion and aggressive secondary prevention therapy. Our hypothesis was that, in the context of higher prevalence of classical cardiovascular risk factors, in particular abnormalities of glucose metabolism, case-fatality following AMI would be higher in SA patients. 5

6 METHODS We conducted a retrospective cohort study of consecutive patients admitted with AMI to the two coronary care units (CCU) of the University Hospitals of Leicester between 1 st October 2002 and 30 th September These CCU serve the multi-ethnic population of Leicestershire; where individuals of SA ethnic origin constitute a large ethnic minority group: 31.8% of the population living in the city of Leicester and 14% of the total Leicestershire population of approximately 1 million (Census 2011). Data were gathered as part of the hospital s mandatory participation in the Myocardial Ischaemia National Audit Programme (MINAP). Established in 1998, MINAP is a national registry of patients admitted with acute coronary syndrome (ACS), and since 2002 all acute NHS hospitals in England and Wales have participated.[20] Data collection for MINAP has approval from the Patient Information Advisory Group, a committee appointed by the English Secretary of State for Health under Section 60 of the English Health and Social Care Act (2001), to use patient and physician identifiable information essential to the project, specifically the unique NHS number, without individual patient consent ( The current project was approved by the local research ethics committee. The dataset contains routine care information including demographic and clinical data, prior medical history, type of AMI (ST elevation (STEMI), or non ST elevation AMI (NSTEMI), biochemical tests, prior, in-hospital and discharge therapies, and reperfusion and revascularisation during the index admission.[20] Furthermore these data include self-reported coding for ethnicity, for which local coverage is thorough. Patients were categorised as STEMI or non NSTEMI according to the discharge diagnosis recorded in the MINAP database. 6

7 Diagnosis and classification of AMI was made according to the joint ESC/ACCF/AHA/WHF definition,[21] and in each case verified prior to submission to the national MINAP database. For patients with multiple admissions during the study period (n=412), we considered only the first event. Patients with ethnicity other than WE and SA were excluded from these analyses. Patients were categorised as having a diagnosis of diabetes on the basis of self-reported diagnosis or prescribed medication at the time of admission. SA or WE ethnicity was selfreported by the patient. Admission blood glucose was taken as the first recorded measurement after admission. Significant hyperglycaemia was defined as plasma glucose >10.0 mmol/l.[(22] During the period of study, primary percutaneous coronary intervention (PCI) gradually replaced thrombolysis as the preferred mode of revascularisation for STEMI. Patients with NSTEMI were initially stabilised with medical therapies and coronary angiography considered thereafter. Patients with persistently elevated blood glucose levels >11.0 mmol/l on admission were administered intravenous, sliding scale insulin for the first hours. Information on mortality is returned to the hospital on an ongoing basis via record linkage to the UK Office of National Statistics. The pre-defined primary outcome measure was all cause mortality, stratified by SA or WE ethnicity, over the entire follow-up period. We also considered all-cause mortality during the index admission, at 30-days and at 1-year. We compared mortality in SA and WE patients in the whole cohort and also in the subgroup of patients surviving to discharge from the index event. Survival was measured from the date of first admission for AMI (between 1 st October 2002 and 30 th September 2008) until date of death or the end of follow-up (censored at 30 th September 2009), whichever was earlier, providing a minimum of one year follow-up for survivors. Statistical analysis 7

8 Baseline characteristics between ethnic groups were examined using independent two-sample t-tests for continuous variables and chi-squared tests for categorical variables. Data are presented as differences in means and proportions. The association of ethnicity with mortality in the entire cohort, and predictors of mortality in SA and WE ethnic subgroups, were determined using Cox proportional hazards analysis. Missing data were imputed in the Cox analyses. Missing medical history and medication variables were assumed to be no. All other variables were subject to multiple imputation with continuous variables imputed using predictive mean matching and binary variables using logistic regression, the predictive variables for the imputation were ethnicity, age, gender and year of admission, and 25 imputations were used. We initially assessed the univariate strength of association with mortality for potentially relevant clinical and demographic variables (Table 2). We conducted multivariate analyses to assess the association between ethnicity and mortality after adjustment for potential confounding factors. Year of admission was included in multivariate analysis to adjust for temporal changes in the management of acute coronary artery disease. Covariates showing univariate association with mortality at p<0.10 (Table 2) were included in forward stepwise multivariate analysis. For computational reasons, forward selection was performed on the complete data but effect estimates are based on the multiply imputed data. In addition, prior diabetes, heart rate and systolic blood pressure at admission, inpatient therapies (loop diuretic, reperfusion therapy) and discharge medication (aspirin, beta blocker, angiotensin converting enzyme inhibitors (ACEI) and angiotensin receptor blockers (ARB) and statin), were included in the models on the basis of their potential relevance to survival. A p-value of <0.05 (2 sided) was considered to indicate statistical significance in all analyses. 8

9 We also determined the univariate and multivariate predictors of mortality in SA and WE patients considered separately. Individual multivariate models were constructed for SA and WE subgroups, entering component variables derived from the final multivariate model for the entire cohort. For the multivariate analyses, landmark analyses were conducted as a secondary analyses with follow-up time split into the following intervals: 0-30 days, 30 days 1 year, 1 3 year, and 3 years. To limit the number of statistical tests, landmark analyses were only performed by ethnic group and not for the cohort as a whole. To assess whether either measure of dysglycaemia (antecedent diabetes or admission plasma glucose), showed differential influence on mortality in SA or WE groups, we conducted multivariate analyses including the interaction term ethnicity*diabetes or ethnicity*glucose, entered individually. The assumption of proportional hazards for the Cox analyses was checked by hazard and log-minus-log graphs. Data are presented as hazard ratio (HR) and 95% confidence intervals (CI). All analyses were carried out using Stata Version

10 RESULTS Between 1 st October 2002 and 30 th September 2008, 4188 admissions with discharge diagnosis of AMI were recorded. After exclusion from analysis of 77 (1.9%) patients with recorded ethnicity other than SA or WE, the final cohort comprised 4111 individuals; 730 (17.8%) SA and 3381 (82.2%) WE. Median follow-up time was 912 (range 1 to 2556) days. For the 3792 (92.2%) patients surviving to discharge from the index admission (675, 17.8% SA; 3117, 82.2% WE), median follow up was 1031 (range 1 to 2556) days. Demographic characteristics Table 1 shows baseline characteristics in the entire cohort and stratified by ethnicity. Presentation with STEMI (58.3%) was more common than NSTEMI (41.7%), with no ethnic differences in this regard (p=0.71). Compared with WE patients, SA patients were on average five years younger (62.0 vs 67.3 years, p<0.005), and slightly more likely to be male (73.2% vs 69.6%, p=0.06). Compared with WE, SA patients had higher prevalence of prior hypertension (p<0.05) and heart failure (p=0.03), lower prevalence of smoking (p<0.05) and prior peripheral vascular disease (p<0.05), lower total cholesterol (p<0.05) and egfr (p=0.02), and were more likely to be prescribed cardiovascular pharmacological treatment prior to admission. At discharge, rates of prescription of secondary prevention treatments were similar, apart from slightly greater use of ACEI/ARB in SA patients (p=0.02). Rates of coronary 10

11 reperfusion therapy during the index admission were similar between the two ethnic groups (p=0.31). For the variables with missing data (Table 1), values were missing at random and there were no statistically significant ethnic difference in proportions of missing values. Antecedent diabetes and admission hyperglycaemia: association with ethnicity Antecedent diabetes was approximately 3 times more prevalent in SA compared with WE patients (39.7% vs 16.1 %, p<0.005). Similarly, mean random plasma glucose was higher in SA, compared with WE, patients (10.1 ± 5.6 mmol/l vs 8.5 ± 3.8 mmol/l, p<0.005) (Table 1). Furthermore, the prevalence of significant hyperglycaemia at admission was also higher in SA compared with WE patients (37.5 % vs 20.5%, p <0.005). For patients with antecedent diabetes, SA patients had higher mean admission glucose levels (12.9 vs 11.6 mmol/l, p=0.02), and greater prevalence of significant hyperglycaemia (63.6% vs 54.6%, p=0.03) compared with their WE counterparts. Similarly, among patients previously not know to have diabetes, significant hyperglycaemia was more prevalent in SA compared with WE (19.6% vs 13.8%, p=0.001). Mortality A total of 1041 (25.3%) patients died during follow up (SA=164/730, 22.5%; WE=877/3381, 25.9%). Crude mortality rates for SA and WE patients were similar at all periods (in-hospital 7.5% vs 7.8%, p=0.879; 30-days 10.0% vs 9.9%, p=0.946; 1-year 15.2% vs 16.0%, p=0.322; entire follow up 22.5% vs 25.9%, p=0.054). A number of baseline demographic, biochemical and therapeutic variables showed univariate association with all-cause mortality over the entire period of follow up (Table 2). Prior diabetes showed univariate association with all-cause mortality, in the entire cohort, and in both SA and WE subgroups. For the entire study population, each 1.0 mmol/l increase in admission glucose 11

12 was associated with an approximately 6.0% increase in mortality risk. The apparent strength of this association was higher in WE compared with SA patients (9.0% vs 3.0% respectively). For other clinical variables, the pattern of univariate association with mortality risk was similar in SA and WE patients, and in keeping with findings in the entire cohort. For the entire cohort, survival improved over the period of observation (Table 1). This trend was less apparent for SA patients, likely due to small numbers of SA patients in each year (data not shown). After covariate adjustment, older age, lower admission systolic blood pressure and higher heart rate, lower egfr, loop diuretic use and STEMI (compared with NSTEMI) retained independent association with mortality risk in the whole cohort, with similar patterns of association in each ethnic subgroup (Table 3). Conversely, coronary reperfusion and discharge prescription of aspirin, beta-blocker and statin were each associated with lower mortality (Table 3). After covariate adjustment, history of diabetes was not associated with higher mortality risk. In contrast, admission blood glucose retained independent association with this end point; each 1 mmol/l increase was associated with approximately 3% increased risk, the association being of similar magnitude in SA and WE subgroups. SA ethnicity showed neither univariate (0.85 (0.72, 1.01)) (Table 2), nor multivariate (1.04 (0.83, 1.31)) (Table 3) association with the risk of the primary outcome of mortality over the entire follow-up period. Similar findings were seen for mortality risk at other time points, both on univariate analysis (HR 30 days 1.01 (0.78, 1.30); one year 0.90 (0.74, 1.11)) and after covariate adjustment (HR 30 days, 1.25 (0.85, 1.84); one year, 1.21 (0.91, 1.61)). Post-discharge mortality Of patients surviving to discharge, there was a trend to lower overall mortality in SA (111/675, 16.4%) compared with WE (615/3117, 19.7%) patients (p=0.05). After covariate adjustment, 12

13 post-discharge mortality risk was similar in SA and WE patients at all time points (HR 30 days 1.17 (0.73, 1.89); one year, 0.88 (0.66, 1.160); entire follow-up 0.82 (0.67, 1.00)). No statistically significant interaction between ethnicity and antecedent diabetes was seen over the entire follow-up period (HR 1.02 (0.65, 1.60)), suggesting that the post-ami mortality risk associated with diabetes diagnosis is similar irrespective of SA or WE ethnicity. In contrast, we did observe an interaction between ethnicity and admission glucose, with the association between admission glucose and mortality risk being lower in SA patients (30 day HR 0.94 ( ); 1 year HR 0.97 ( ); all follow up HR 0.96 ( )) Figure 1 shows that for a given concentration of admission glucose, mortality risk over the entire follow-up period appears to be greater in WE compared to SA patients, the magnitude of the difference increasing with increasing blood glucose. We conducted similar analyses for patients surviving to discharge, including an interaction term between ethnicity*diabetes and ethnicity*glucose in the multivariate model. No statistically significant interactions were observed, suggesting that in patients surviving to discharge mortality risk in relation to antecedent diabetes or admission plasma glucose is similar in SA and WE. 13

14 DISCUSSION To our knowledge the current report, one of the largest contemporary study of prognosis after AMI in SA and WE patients in the UK, is the first to consider, in a multi-ethnic population, the association with mortality after AMI of two measures of dysglycaemia, antecedent diabetes and admission plasma glucose concentration. Our study has four clinically relevant findings. First, following AMI, adjusted survival is similar for SA and WE patients in the UK. Second, in both ethnic groups, after covariate adjustment, prior diabetes does not show independent association with mortality risk up to 1 year after AMI. Third, following similar covariate adjustment, blood glucose at admission with AMI shows graded association with subsequent mortality risk, both in the short, and in the medium, term. Fourth, admission blood glucose showed more powerful association with mortality risk in WE, compared with SA, patients. Previous studies in this area have provided conflicting results. While early studies showed worse[9,10] prognosis in SA patients, more recent studies suggested similar[11,12,15] or better[5,8,13] prognosis in SA compared with WE patients. Many of the earlier studies have one or more important limitations, including small sample size, short length of follow-up or statistical analysis failing to consider potential confounders. Our analysis addresses these issues and suggests that following AMI, survival is similar for SA and WE patients in the UK. Our findings are generally in line with those of recently published studies from Canada[8] and the UK.[13] In the Canadian study, 30-day mortality was similar in SA and WE patients admitted with AMI in the period 1994 to 2003.[8] Furthermore, in patients who survived to 30 days, longer term mortality risk, over a median of 3.2 years, was 35% lower in SA compared 14

15 to WE patients.[13] Our study suggests that mortality following AMI is not higher in SA compared to WE patients in the UK on a background of higher CHD incidence in SA patients. This observation is broadly in keeping with data from a recent comprehensive metaanalysis,[13] in which adjusted mortality after ACS was lower for SA in comparison with WE at 30 day (HR 0.85 (0.77, 0.94) and one year (HR 0.83 (0.78, 0.89) of follow up. Our findings are consistent with results in other presentation of CHD including out of hospital cardiac arrest,[24] angina pectoris,[25] heart failure,[26] and a mixed cohort of patients undergoing PCI,[12] where no ethnic differences in mortality were seen for SA and WE groups. We observed similar patterns of management of AMI in SA and WE patients in the UK, in keeping with those from other cohorts of ACS from the UK.[12,13] We observed no association between ethnicity and diabetes on mortality after AMI. This is in contrast to the findings of a recent study from a large population from MINAP,[13] which indicated diabetes to be more strongly associated with adverse outcome in SA, compared to WE patients. A number of factors are likely to be relevant to this difference. The much larger sample size in the earlier study[13] is likely to be relevant, however, other important differences exist. In the present study, individual patient ethnicity was self reported, rather than being assigned at a hospital level.[13] Other differences in methodology, such as differences in covariate adjustment, may also contribute to the observed differences in the interaction between ethnicity and diabetes seen in our study and the recent MINAP report.[13] We observed strong, independent association between increasing plasma glucose at admission with AMI and subsequent mortality risk in both ethnic groups. This is in line with previous reports from our group in patients with STEMI,[17] and also in the current mixed cohort of STEMI and NSTEMI.[27] In keeping with the greater prevalence of diabetes in SA patients, rates of hyperglycaemia were higher in this ethnic group. This association appeared stronger 15

16 in WE, compared to SA, patients, and may represent higher prevalence of hitherto undiagnosed diabetes in WE compared to SA patients prior to the AMI event. The significance of this observation is unclear, and merits further investigation. However, while the influence on outcome after AMI of hyperglycaemia is controversial, successful lowering of elevated glucose after AMI has been associated with better outcome.[28] In this context, elevated glucose at the time of AMI may represent a particularly clinically relevant therapeutic target in SA patients. It has been debated whether high CHD mortality in SA people is due to high incidence of, or high case fatality following presentation with, CHD.[10,29] Our study, along with other recent reports [8,12,13,29] strengthens the evidence suggesting that prognosis following AMI is not worse in SA compared with WE groups, even after adjusting for important differences in these populations, including young age and high prevalence of metabolic risk factors in the SA groups. Our data, added to the recently published review of evidence[13] suggest that high overall CHD mortality in SA is most likely due to the high incidence of disease, rather than greater case fatality.[29] We suggest that the focus of the debate should shift towards how best to control the premature and high incidence of CHD in this ethnic population. The heightened CHD risk in SA population is mainly due to the higher burden of metabolic risk factors present at younger age, resulting from a complex interplay of multiple factors including gene-environment interaction and socio-cultural influence.[30] Therefore early detection and prevention (both primary and secondary) of CHD and its risk factors, should form the cornerstone of any approach seeking to improve the situation.[30] Equally, emphasis should also be placed on educating SA populations about their heightened CHD risk and empowering them to improve behaviour towards risk modification. Our report is subject to the limitations inherent in all observational cohort studies. Our results are from a single tertiary cardiology centre and include a relatively high proportion of STEMI 16

17 (58.4%), suggesting possible selection bias in our population. This issue is relevant to all registry-based studies, and is not directly relevant to our observations, as proportions of STEMI and NSTEMI were similar in SA and WE subgroups. Our dataset lacks information on body mass index, types of diabetes and glucose lowering therapies. It is likely that a proportion of our cohort had previously undiagnosed diabetes, which may contribute to the association between admission glucose and subsequent mortality risk. Furthermore, we do not have information on left ventricular ejection fraction, evidence of heart failure, angiographic findings and details of events, other than mortality, after the index admission. Finally, SA populations are heterogeneous, including sub-populations with varying demographic characteristics. Our study findings are based predominantly on Indian Gujarati patients living in Leicester city and may not be entirely applicable to other SA subgroups. In summary, adjusted survival following AMI is similar for SA and WE patients in the UK, in spite of differing background cardiovascular risk factor profile. Prior diabetes does not have independent association with risk of death after AMI, irrespective of SA and WE ethnicity. In contrast, admission glucose appears to have more powerful association with mortality risk in WE, compared with SA patients. High CHD mortality in SA patients in the UK does not appear to be related to increased case fatality after AMI. Table 1: Baseline characteristics stratified by ethnic origin Variable All (n=4111) White European South Asian P Value * Missing values 17

18 n=3381 (82.2%) n=730 (17.8%) Admission Demography Age (years) 66.4 (13.3) 67.3 (13.1) 62.0 (13.3) < Male (%) 1224 (70.2) 1028 (69.6) 196 (73.2) Prior disease & Risk factors (%) Prior diabetes diagnosis 835 (20.3) 545 (16.1) 290 (39.7) < Hypertension 2048 (50.3) 1649 (49.3) 399 (55.2) Coronary Heart Disease 491 (12.1) 406 (12.1) 85 (11.7) CVA 254 (6.3) 215 (6.4) 39 (5.4) PVD 154 (3.8) 144 (4.3) 10 (1.4) < Heart Failure 190 (4.7) 145 (4.3) 45 (6.2) Current/Ex Smoker 1366 (35.7) 1259 (39.9) 107 (16.0) < Prior therapies (%) Aspirin 2671 (65) 2176 (64.4) 495 (67.8) Beta blocker 990 (25.6) 796 (25.1) 194 (28.0) ACEI or ARB 1097 (28.3) 866 (27.2) 231 (33.3) Statins 1083 (28.0) 859 (27.0) 224 (32.3) Type of Infarction STEMI (%) 2397 (58.3) 1976 (58.4) 421(57.7) Physical Examination Heart Rate, beats/min (SD) 81.1 (24.3) 80.7 (24.4) 82.9 (23.9) SBP, mmhg (SD) (28.4) (28.2) (29.6) Biochemical Data (SD) Total CK (IU/L) Normal range < (1810) 1099 (1857) 1177 (1570) Creatinine (µmol/l) (63.8) (61.5) 117 (73.9) egfr ml/min 63.0 (22.2) 62.6 (22) 64.9 (23.5) Total Cholesterol (mmol/l) 5.1 (1.3) 5.2 (1.3) 4.9 (1.2) < Haemoglobin (g/l) 13.7 (1.9) 13.8 (1.9) 13.4 (1.9) Admission plasma glucose (mmol/l) 8.8 (4.2) 8.5 (3.8) 10.1 (5.6) < Admission plasma glucose categories (%) Admission plasma glucose >10.0 mmol/l 821 (23.5) 589 (20.5) 231 (37.2) < Admission plasma glucose >10.0 mmol/l 406 (14.6) 333 (13.8) 73 (19.6) and previously unknown diabetes In- Hospital therapies (%) Reperfusion therapy # 2414 (58.7) 1973 (58.4) 441 (60.4) Loop diuretics 1502( 37.4) 1239 (37.5) 263 (36.8) Discharge therapies (%) Aspirin 2701 (68.0) 2233 (68.6) 468 (66.0) Beta blocker 2513 (63.3) 2072 (63.6) 441 (62.2) ACEI or ARB 2493 (62.9) 2076 (63.8) 417 (59.8) Statin 2704 (67.7) 2230 (68.0) 474 (66.2) (%) * South Asian vs. White European any of angina/ myocardial infarction / percutaneous intervention (PCI)/ coronary artery bypass grafting (CABG) # thrombolysis or coronary intervention (PCI or CABG) or both CVA, Cerebrovascular accident; ACEI, angiotensin converting enzyme inhibitor; ARB, angiotensin receptor blocker; CK, Creatinine Kinase; egfr, estimated Glomerular filtration 18

19 rate calculated by Modification of Diet in Renal Disease (MDRD) equation (23); nstemi, non-st elevation myocardial infarction; PVD, Peripheral Vascular Disease; SBP, Systolic blood pressure; STEMI, ST elevation myocardial infarction; 19

20 Table 2: Association with all-cause mortality stratified by South Asian or White European ethnicity: Univariate Cox regression analysis All cause mortality over the entire follow-up period (Median 912 days) Whole Cohort White Europeans South Asian N=1041/4111(25.3%) N=877/3381 (25.9%) N=164/730 (22.5%) Hazard Ratio (95% CI) P-value Hazard Ratio (95% CI) P-value Hazard Ratio (95% CI) P-value Admission Demographics Ethnicity 0.85 (0.72, 1.01) (South Asian vs White Europeans) Gender (Female vs Male) 0.56 (0.49, 0.63) < (0.50, 0.66) < (0.34, 0.63) <0.001 Age (year) (1.08, 1.09) < (1.08, 1.09) < (1.07, 1.10) <0.001 SBP (mmhg) (0.99, 0.99) < (0.99, 0.99) < (0.99, 1.00) Heart Rate (beat/min) (1.01, 1.01) < (1.01, 1.01) < (1.01, 1.02) <0.001 Total Cholesterol (mmol/l) (0.74, 0.82) < (0.72, 0.82) < (0.70, 0.93) Admission plasma glucose (mmol/l) (1.04, 1.06) < (1.06, 1.09) < (1.01, 1.05) <0.001 egfr (ml/min) (0.96, 0.97) < (0.96, 0.96) < (0.96, 0.98) <0.001 NSTEMI vs STEMI 0.94 (0.83, 1.06) (0.80, 1.05) (0.79, 1.46) Year of Admission Oct 2002-Dec (Reference) 1 (Reference) 1 (Reference) (0.78, 1.08) (0.76, 1.09) (0.66, 1.59) (0.56, 0.87) (0.54, 0.87) (0.51, 1.53) (0.57, 0.90) (0.52, 0.87) (0.60, 1.69) (0.56, 0.83) < (0.54, 0.82) < (0.51, 1.42) (0.42, 0.69) < (0.41, 0.70) < (0.28, 1.08) Medical History (Yes vs No) Smoking 1.17 (1.03, 1.33) (1.05, 1.38) (0.42, 1.17) Prior Diabetes 1.65 (1.45, 1.89) < (1.47, 2.01) < (1.40, 2.58) <0.001 Prior CHD 1.11 (0.93, 1.33) (0.95, 1.39) (0.58, 1.51) Prior Hypertension 1.46 (1.29, 1.65) < (1.29, 1.68) < (1.08, 2.03) Pre -Admission Medication (Yes vs No) 20

21 Aspirin 0.91 (0.80, 1.03) (0.77, 1.02) (0.78, 1.51) Beta Blocker 1.45 (1.27, 1.66) < (1.29, 1.72) < (0.95, 1.83) Statin 1.17 (1.03, 1.34) (0.96, 1.29) (1.12, 2.12) ACEI or ARB 1.59 (1.40, 1.80) < (1.35, 1.79) < (1.35, 2.50) <0.001 Admission treatment (Yes vs No) Initial Reperfusion 0.47 (0.41, 0.53) < (0.42, 0.55) < (0.29, 0.55) <0.001 Loop Diuretic 4.00 (3.51, 4.56) < (1.22, 1.50) < (3.25, 6.38) <0.001 Discharge Medication (Yes vs No) Aspirin 0.38 (0.34, 0.43) < (0.33, 0.42) < (0.31, 0.58) <0.001 Beta Blocker 0.36 (0.32, 0.41) < (0.31, 0.41) < (0.27, 0.51) <0.001 Statin 0.31 (0.27, 0.35) < (0.26, 0.34) < (0.24, 0.45) <0.001 ACEI or ARB 0.41 (0.36, 0.46) < (0.35, 0.46) < (0.32, 0.59) <0.001 SBP=systolic blood pressure; egfr=estimated glomerular filtration rate; NSTEMI=Non-ST elevation acute myocardial infarction; STEMI= ST elevation acute myocardial infarction; CHD=coronary heart disease; ACEI=angiotensin converting enzyme inhibitor; ARB=angiotensin receptor blocker 21

22 Table 3: Association with all-cause mortality stratified by South Asian or White European ethnicity: Multivariate Cox regression analysis All cause mortality over the entire follow-up period (Median 912 days) Whole Cohort White Europeans South Asian N=1041/4111(25.3%) N=877/3381 (25.9%) N=164/730 (22.5%) Hazard Ratio (95% CI) P-value Hazard Ratio (95% CI) P-value Hazard Ratio (95% CI) P-value Admission demographics Ethnicity 1.09 (0.91, 1.30) (South Asian vs White Europeans) Age (year) 1.06 (1.06, 1.07) < (1.05, 1.07) < (1.05, 1.09) <0.001 Systolic blood pressure (mm Hg) 0.99 (0.99, 1.00) < (0.99, 1.00) < (0.99, 1.00) Heart Rate (beat/min) (1.00, 1.01) < (1.00, 1.01) < (1.00, 1.01) egfr (ml/min) (0.99, 1.00) < (0.99, 0.99) < (0.99, 1.01) Serum glucose (mmol/l) (1.02, 1.05) < (1.02, 1.05) < (0.99, 1.05) NSTEMI vs STEMI 0.57 (0.49, 0.65) < (0.48, 0.65) < (0.41, 0.80) <0.001 Medical History (Yes vs No) Prior diabetes 1.22 (1.05, 1.41) (1.04, 1.45) (0.84, 1.68) Pre-admission medications Beta blocker 1.14 (1.00, 1.31) (0.99, 1.33) (0.87, 1.77) Admission treatment (Yes vs No) Loop Diuretic Use 1.66 (1.44, 1.92) < (1.35, 1.85) < (1.55, 3.32) <0.001 Reperfusion 0.59 (0.51, 0.68) < (0.52, 0.71) < (0.33, 0.68) <0.001 Discharge medications (Yes vs No) Aspirin 0.72 (0.60, 0.86) < (0.56, 0.83) < (0.64, 1.87) Beta Blocker 0.65 (0.55, 0.77) < (0.54, 0.78) < (0.38, 0.96) ACEI or ARB 0.81 (0.67, 0.98) (0.68, 1.03) (0.39, 1.05) Statin 0.59 (0.49, 0.71) < (0.50, 0.74) < (0.32, 0.85)

23 SBP=Systolic Blood Pressure; egfr=estimated glomerular filtration rate; NSTEMI=Non-ST elevation acute myocardial infarction; STEMI= ST elevation acute myocardial infarction; CHD=coronary heart disease; ACEI=angiotensin converting enzyme inhibitor; ARB=angiotensin receptor blocker 23

24 ACKNOWLEDGEMENTS We acknowledge the support of the following institutes in this work: The Leicester NIHR Biomedical Research Unit in Cardiovascular Disease; the National Institute for Health Research, Collaboration for Leadership in Applied Health Research and Care - East Midlands (NIHR CLARHC East Midlands); and the Leicester-Loughborough NIHR Diet, Lifestyle & Physical Activity Biomedical Research Unit. CONTRIBUTORS NG, IS, KK and MJD conceived the idea of the study and were responsible for the design of the study. NG and DB were responsible for undertaking for the data analysis and produced the tables and graph. The initial draft of the manuscript was prepared by the NG, and then circulated repeatedly amongst all authors for critical revision. IS, was responsible for the acquisition of the data and NG, IS, KK, MJD and DB contributed to the interpretation of the results. FUNDING The work in this paper is part of the research portfolio supported by the Leicester NIHR Biomedical Research Unit in Cardiovascular Disease. NG was supported by the NIHR CLAHRC for LNR project PhD studentship. CONFLICTS OF INTEREST None COPYRIGHT 24

25 The Corresponding Author has the right to grant on behalf of all authors and does grant on behalf of all authors, an exclusive licence (or non-exclusive for UK Crown Employees) on a worldwide basis to the BMJ Publishing Group Ltd, and its Licensees to permit this article (if accepted) to be published in Heart and any other BMJPGL products and to exploit all subsidiary rights, as set out in our licence. REFERENCES 25

26 1. Anand SS, Yusuf S, Vuksan V, et al. Differences in risk factors, atherosclerosis, and cardiovascular disease between ethnic groups in Canada: the Study of Health Assessment and Risk in Ethnic groups (SHARE). Lancet 2000;356: Mak KH, Chia KS, Kark J, et al. Ethnic differences in acute myocardial infarction in Singapore. Eur Heart J 2003;24: Walker A. The epidemiology of ischaemic heart disease in the different ethnic populations in Johannesburg. S Afr Med J 1980;57: Bhopal R. What is the risk of coronary heart disease in South Asians? A review of UK research. Journal of Public Health 2000;22: Fischbacher C, Bhopal R, Povey C, et al. Record linked retrospective cohort study of 4.6 million people exploring ethnic variations in disease: myocardial infarction in South Asians. BMC Public Health 2007;7: Harding S, Rosato M, Teyhan A. Trends for coronary heart disease and stroke mortality among migrants in England and Wales, : slow declines notable for some groups. Heart 2008;94: Gupta M, Doobay AV, Singh N, et al. Risk factors, hospital management and outcomes after acute myocardial infarction in South Asian Canadians and matched control subjects. Can Med Assoc J 2002;166: Khan NA, Grubisic M, Hemmelgarn B, Humphries K, King KM, Quan H. Outcomes After Acute Myocardial Infarction in South Asian, Chinese, and White Patients / Clinical Perspective. Circulation 2010;122: Hughes L, Raval U, Raftery E. First myocardial infarctions in Asian and white men. Br Med J 1989;298:

27 10. Wilkinson P, Sayer J, Laji K, et al. Comparison of case fatality in south Asian and white patients after acute myocardial infarction: observational study. BMJ 1996;312: Mukhtar H, Littler W. Survival after acute myocardial infarction in Asian and white patients in Birmingham. Br Heart J 1995;73: Jones D, Rathod K, Sekhri N, et al. Case fatality rates for South Asian and Caucasian patients show no difference 2.5 years after percutaneous coronary intervention. Heart 2012;98: Zaman MJS, Philipson P, Chen R, et al. South Asians and coronary disease: is there discordance between effects on incidence and prognosis? Heart 2013;99: Raghavan R, Rahme E, Nedjar H, et al Long-term prognosis of south Asians following acute coronary syndromes. Can J Cardiol 2008;24: Liew R, Sulfi S, Ranjadayalan K, et al. Declining case fatality rates for acute myocardial infarction in South Asian and white patients in the past 15 years. Heart 2006;92: McGuire D, Emanuelsson H, Granger C, et al. Influence of diabetes mellitus on clinical outcomes across the spectrum of acute coronary syndromes. Findings from the GUSTO-IIb Study. Eur Heart J 2000;21: Squire I, Nelson C, Ng L, et al. Prognostic value of admission blood glucose concentration and diabetes diagnosis on survival after acute myocardial infarction: results from 4702 index cases in routine practice. Clin Sci 2010;118: Capes SE, Hunt D, Malmberg K, et al. Stress hyperglycaemia and increased risk of death after myocardial infarction in patients with and without diabetes: a systematic overview. Lancet 2000;355:

28 19. Joshi P, Islam S, Pais P, et al. Risk factors for early myocardial infarction in South Asians compared with individuals in other countries. JAMA: the journal of the American Medical Association 2007;297: Herrett E, Smeeth L, Walker L, et al. The myocardial ischaemia national audit project (MINAP). Heart 2010;96: Thygesen K, Alpert JS, White HD, Joint ESC/ACCF/AHA/WHF Task Force for the Redefinition of Myocardial Infarction. Universal definition of the myocardial infarction. Kardiol Pol 2008;66: Deedwania P, Kosiborod M, Barrett E, et al. Hyperglycemia and acute coronary syndrome: a scientific statement from the American Heart Association Diabetes Committee of the Council on Nutrition, Physical Activity, and Metabolism. Circulation 2008; 25;117: Levey A, Bosch J, Lewis J, et al. Modification of Diet in Renal Disease Study Group: A more accurate method to estimate glomerular filtration rate from serum creatinine: a new prediction equation. Ann Intern Med 1999;130: Shah AS, Bhopal R, Gadd S, et al. Out-of-hospital cardiac arrest in South Asian and white populations in London: database evaluation of characteristics and outcome. Heart 2010;96: Zaman MJ, Crook AM, Junghans C, et al. Ethnic differences in long-term improvement of angina following revascularization or medical management: a comparison between south Asians and white Europeans. Journal of Public Health 2009;31: Blackledge HM, Newton J, Squire IB. Prognosis for South Asian and white patients newly admitted to hospital with heart failure in the United Kingdom: historical cohort study. BMJ 2003;327:

29 27. Gholap NN, Mehta RL, Ng L, Davies MJ, Khunti K, Squire IB. Is admission blood glucose concentration a more powerful predictor of mortality after myocardial infarction than diabetes diagnosis? A retrospective cohort study. BMJ Open 2012;2:e doi: /bmjopen Malmberg K, Ryden L, Efendic S, et al. Randomized trial of insulin-glucose infusion followed by subcutaneous insulin treatment in diabetic patients with acute myocardial infarction (DIGAMI study): effects on mortality at 1 year. J Am Coll Cardiol.1995;26: Zaman MJ, Bhopal RS. New answers to three questions on the epidemic of coronary mortality in south Asians: Incidence or case fatality? Biology or environment? Will the next generation be affected? Heart 2013,99: Gholap N, Davies M, Patel K, et al. Type 2 diabetes and cardiovascular disease in South Asians. Primary Care Diabetes 2011;5: