Abstract
Aims
There are limited contemporary data on the presentation, management, and outcomes of acute coronary syndrome (ACS) admissions in India. We aimed to develop a prospective registry to address treatment and health systems gaps in the management of ACSs in Kerala, India.
Methods and results
We prospectively collected data on 25 748 consecutive ACS admissions from 2007 to 2009 in 125 hospitals in Kerala. We evaluated data on presentation, management, and in-hospital mortality and major adverse cardiovascular events (MACE). We created random-effects multivariate regression models to evaluate predictors of outcomes while accounting for confounders. Mean (SD) age at presentation was 60 (12) years and did not differ among ACS types [ST-segment myocardial infarction (STEMI) = 37%; non-STEMI = 31%; unstable angina = 32%]. In-hospital anti-platelet use was high (>90%). Thrombolytics were used in 41% of STEMI, 19% of non-STEMI, and 11% of unstable angina admissions. Percutaneous coronary intervention rates were marginally higher in STEMI admissions. Discharge medication rates were variable and generally suboptimal (<80%). In-hospital mortality and MACE rates were highest for STEMI (8.2 and 10.3%, respectively). After adjustment, STEMI diagnosis (vs. unstable angina) [odds ratio (OR) (95% confidence interval = 4.06 (2.36, 7.00)], symptom-to-door time >6 h [OR = 2.29 (1.73, 3.02)], and inappropriate use of thrombolysis [OR = 1.33 (0.92, 1.91)] were associated with higher risk of in-hospital mortality and door-to-needle time <30 min [OR = 0.44 (0.27, 0.72)] was associated with lower mortality. Similar trends were seen for risk of MACE.
Conclusion
These data represent the largest ACS registry in India and demonstrate opportunities for improving ACS care.
Keywords: Acute coronary syndrome, India, Registry, Outcomes
See page 83 for the editorial comment on this article (doi:10.1093/eurheartj/ehs328))
Introduction
Cardiovascular disease (CVD) is the leading cause of death in India and in the southern Indian state of Kerala,1 leading to premature death, disability, and financial catastrophe due to high out-of-pocket expenditures for acute cardiovascular care.2 Kerala has among the lowest infant mortality rate, highest literacy rate, and longest life expectancy among the Indian states and is thus considered to be further along the epidemiological transition than most other states in India.3–5 As such, there may be differences in the patient- and hospital-level characteristics in the presentation, management, and outcomes of CVD, including acute coronary syndrome (ACS), in Kerala that might precede the rest of India.
Rates of secondary CVD prevention are low in India and other middle-income countries6 but offer opportunities for substantial improvements in cardiovascular morbidity and mortality. Treatment of patients who experience ACS with aspirin and post-discharge treatment with aspirin, statin, and blood pressure lowering agents are cost-saving and cost-effective strategies, respectively, and are considered ‘best buys’ by the World Health Organization.7 Acute coronary syndrome quality improvement programmes have been deployed in the USA,8–10 Sweden,11 and China,12 among other countries. Published results of these programmes have demonstrated improvements in in-hospital and discharge process-of-care measures with associated improvements in outcomes.8–11 A contemporary ACS registry can provide the first step in determining which measures represent the best opportunities for improvement.
There are limited contemporary registry data from India on individuals who experience ACS. The two largest ACS registries in India to date, OASIS-2 (1028 patients; 1999–2000)13 and CREATE (20 937 patients; 2001–2005),14 collected data from a large number of hospitals throughout India that had previously participated in a robust clinical research network but with a limited number of centres in Kerala. Neither registry included the full spectrum of ACS: ST-segment myocardial infarction (STEMI), non-STEMI, and unstable angina. Updated registry data on all ACS types from centres that have not previously participated in clinical research may provide unique insights into ACS care in Kerala in order to improve secondary and tertiary preventive efforts.
The Cardiological Society of India—Kerala Chapter (CSI-K) developed a prospective ACS registry to evaluate contemporary trends in the presentation, management, and outcomes of ACS patients in a broad range of registered hospitals and providers in Kerala to evaluate the opportunities for data-driven continuous quality improvement. We present the initial findings on the presentation, management, and in-hospital outcomes of 25 748 ACS patients across 125 hospitals throughout Kerala.
Methods
Based on the local expert input, there were an estimated 300 acute care hospitals with intensive care units in Kerala in 2007, of which 185 hospitals admitted patients with ACSs. Representatives from these hospitals were invited to participate. One hundred and forty hospitals responded to this invitation, and 125 hospitals participated. Data from 25 748 consecutive ACS admissions were collected from 125 hospitals from May 2007 to May 2009. Patients were included if they were >18 years old and presented with chest pain and one or more of the following: (i) ST-segment elevation in two contiguous leads with or without reciprocal ST-segment depression, (ii) troponin or CK-MB elevation, or (iii) ST-segment depression or T-wave inversion in two contiguous leads with a history of coronary heart disease. Patients were captured in coronary care units.
Consent for in-hospital data collected was waived, based on the Common Rule. Trained medical personnel abstracted in-hospital data regarding patient demographics, education level, self-reported medical history, prior medications, anthropometry, vital signs, diagnostics, treatment, and outcomes from the medical record. Case report forms were completed in the presence of the treating physician. Data were supplemented by patient interviews, when necessary. Five regional coordinators (cardiologists) supervised 10 district-level-trained research coordinators, who visited each hospital each month to collect case report forms and resolve any outstanding questions. When questions arose, the regional coordinator met with the treating physician to achieve consensus. Data were entered into a central database for storage and subsequent analysis.
Statistical analysis
Continuous variables are presented in means (standard deviation) or median (inter-quartile range), when skewed in distribution. Categorical variables are presented as proportions. Comparisons by ACS type were made via analysis of variance for continuous variables and chi-square for categorical variables. A two-sided P value <0.05 defined statistical significance. Univariate and random-effects multivariate logistic regression to adjust standard errors for the clustering of patients within hospitals was performed to assess for predictors of in-hospital mortality and in-hospital major adverse cardiovascular events (or MACE, defined as death, re-infarction, stroke, heart failure, or cardiogenic shock). In addition to age and sex, we included covariates from the Global Registry of Acute Coronary Events (GRACE) Risk Model to serve as the basis of our investigation into potential pre- and in-hospital targets for intervention.15 Given our previous pilot work that led to improvements in symptom-to-door time and door-to-needle time,16 we modelled the impact of these variables on the outcomes. We chose to include inappropriate thrombolysis in our models based on the unexpectedly high rates of inappropriate thrombolysis. We used STATA v.11.0 (College Station, TX, USA) for our analyses.
The study was approved by the Institutional Ethics Committee of Sree Chithra Institute of Medical Sciences and Technology in Trivandrum and Westfort Hi-tech Hospital in Thrissur.
Role of the funding source
The study was funded by the CSI-K. Given the study investigators' roles in the CSI-K, the CSI-K participated in the study design, data collection, analysis, and writing of the manuscript.
Results
Hospital characteristics
Ten (8%) hospitals had an academic affiliation, 15 (12%) were government hospitals, 28 (22%) hospitals had on-site cardiac catheterization laboratories, 72 (58%) hospitals had staff cardiologists, and 74 (59%) were located in urban centres.
Demographics, medical history, and clinical presentation
The mean age of participants was 60.4 (12.1) years and more than three-quarters were men (Table 1). Patients were more likely to present with STEMI (37%) than with non-STEMI (31%), or unstable angina (32%, P < 0.001). Patients with STEMI (23%) and non-STEMI (26%) were less likely to have received any formal schooling than patients with unstable angina (12%, P < 0.001). Prior diabetes, stroke, and percutaneous coronary intervention/coronary artery bypass graft surgery (PCI/CABG) were more common in patients presenting with unstable angina compared with STEMI and non-STEMI patients, whereas prior hypertension, hypertension, and smoking were more common in STEMI and non-STEMI patients. ST-segment myocardial infarction patients (41%) were more likely to present >6 h from symptom onset than non-STEMI (36%) and unstable angina patients (39%, P < 0.001). Heart rate, systolic and diastolic blood pressure, body mass index, and fasting plasma glucose were similar across ACS types, but unstable angina patients were more likely to present with Killip class >1 and with serum creatinine >2 mg/dL.
Table 1.
Patient-level characteristics upon presentation, by acute coronary syndrome type
| Total | STEMI | Non-STEMI | Unstable angina | P value | ||
|---|---|---|---|---|---|---|
| N (%) | N | 25 748 | 9569 (37) | 7857 (31) | 8322 (32) | |
| Demographics | ||||||
| Sex (male), N (%) | 25 748 | 19 923 (77.4) | 7400 (77.3) | 5932 (75.5) | 6591 (79.2) | <0.001 |
| Age, years (SD) | 25 745 | 60.4 (12.1) | 60.4 (12.1) | 60.5 (11.9) | 60.5 (12.1) | 0.63 |
| Age strata | 25 745 | 0.70 | ||||
| <50 years, N (%) | 25 745 | 5718 (22.2) | 2147 (22.4) | 1742 (22.2) | 1829 (22.0) | |
| 51–70 years, N (%) | 25 745 | 14 715 (57.2) | 5477 (57.2) | 4506 (57.4) | 4732 (56.9) | |
| >70 years, N (%) | 25 745 | 3312 (20.6) | 1944 (20.3) | 1609 (20.5) | 1759 (21.1) | |
| Non-resident Indian, N (%) | 25 748 | 1716 (6.7) | 804 (8.4) | 490 (6.2) | 422 (5.1) | <0.001 |
| Education level | 14 117 | <0.001 | ||||
| No education, N (%) | 14 117 | 2781 (19.7) | 1187 (22.5) | 1015 (25.9) | 579 (11.8) | |
| Primary education (class 1–7), N (%) | 14 117 | 2818 (20.0) | 972 (18.4) | 840 (21.4) | 1006 (20.4) | |
| Secondary education (class 8–11), N (%) | 14 117 | 5748 (40.7) | 2146 (40.7) | 1365 (34.8) | 2237 (45.4) | |
| Secondary graduate and above (≥12), N (%) | 14 117 | 2770 (19.6) | 967 (18.3) | 701 (17.9) | 1102 (22.4) | |
| Occupation | 25 474 | <0.001 | ||||
| Unemployed, N (%) | 25 474 | 9762 (38.3) | 3782 (39.9) | 3004 (38.4) | 2976 (36.2) | |
| Manual labourer, N (%) | 25 474 | 6515 (25.5) | 2363 (24.9) | 1988 (25.4) | 2164 (26.3) | |
| Government, private, business, N (%) | 25 474 | 5810 (22.8) | 1977 (20.9) | 1812 (23.2) | 2021 (24.6) | |
| Homemaker, other, N (%) | 25 474 | 1577 (6.2) | 641 (6.8) | 520 (6.7) | 416 (5.1) | |
| Retired, N (%) | 25 474 | 1853 (7.3) | 717 (7.6) | 495 (6.3) | 641 (7.8) | |
| Key risk factors | ||||||
| History of diabetes, N (%) | 25 748 | 9683 (37.6) | 3314 (34.6) | 2981 (37.9) | 3388 (40.7) | <0.001 |
| History of hypertension, N (%) | 25 748 | 12 468 (48.4) | 5315 (55.5) | 3788 (48.2) | 3365 (40.4) | <0.001 |
| History of smoking, N (%) | 25 748 | 8867 (34.4) | 3376 (35.3) | 2980 (37.9) | 2511 (30.2) | <0.001 |
| History of myocardial infarction, N (%) | 25 748 | 3655 (14.2) | 1257 (13.1) | 1212 (15.4) | 1186 (14.3) | <0.001 |
| History of stroke, N (%) | 25 748 | 646 (2.5) | 212 (2.2) | 170 (2.2) | 264 (3.2) | <0.001 |
| History of PCI/CABG, N (%) | 25 748 | 73 (0.3) | 8 (0.1) | 10 (0.1) | 55 (0.7) | <0.001 |
| Clinical features on presentation | ||||||
| Symptom onset to presentation >6 h, N (%) | 25 527 | 9937 (28.9) | 3915 (41.2) | 2809 (36.1) | 3213 (39.0) | <0.001 |
| Heart rate, mean (SD) | 25 195 | 80.0 (19.5) | 79.5 (19.9) | 80.4 (20.0) | 80.5 (18.5) | 0.002 |
| Systolic blood pressure (mmHg), mean (SD) | 25 126 | 140.8 (30.0) | 138.9 (30.0) | 141.3 (29.2) | 142.7 (30.7) | <0.001 |
| Diastolic blood pressure (mmHg), mean (SD) | 25 123 | 86.6 (15.3) | 86.4 (15.8) | 86.6 (15.0) | 86.7 (14.9) | 0.38 |
| Body mass index (kg/m2) | 25 671 | 23.1 (3.6) | 23.1 (3.6) | 23.2 (3.6) | 23.0 (3.6) | 0.004 |
| Killip class >1, N (%) | 13 793 | 2996 (21.7) | 1048 (20.8) | 828 (19.1) | 1120 (25.5) | <0.001 |
| EF ≤ 30%, N (%) | 17 084 | 260 (1.5) | 103 (1.6) | 75 (1.6) | 82 (1.4) | <0.001 |
| Fasting blood glucose, mg/dL (IQR) | 20 863 | 115 (94, 156) | 115 (94, 156) | 112 (91, 152) | 116 (93, 158) | <0.001 |
| Creatinine >2 mg/dL, N (%) | 21 557 | 911 (4.20) | 319 (4.0) | 260 (4.2) | 332 (4.5) | 0.004 |
In-hospital and discharge diagnostics and management
Coronary angiography was performed in ∼20% of all patients with marginal statistical differences across ACS types (Table 2). Thrombolysis was used in 41% of STEMI patients, as well as 19% of non-STEMI and 11% of unstable angina patients, respectively. Inappropriate thrombolysis was more common in low volume (<500 vs. ≥500 ACS admissions during study period) (21.3 vs. 12.0%; P < 0.001), rural (24.3 vs. 13.9%, P < 0.001), and non-teaching hospitals (16.6 vs. 9.7%, P < 0.001; all unadjusted). Less than one-third of STEMI patients who received thrombolysis had door-to-needle times more than 30 min. Nearly half of STEMI patients received some form of reperfusion (thrombolysis, PCI, or CABG), while non-STEMI (27%) and unstable angina (21%) patients underwent reperfusion significantly less frequently. On the other hand, in-hospital aspirin and clopidogrel was given in >90% in all ACS types. Nitrates were the next commonly used class of medications in the hospital, while beta-blockers, statins, and heparin were used less commonly. A similar, but lower, trend was seen in post-discharge prescription medication rates (Table 3). Non-STEMI patients were most likely to receive aspirin, clopidogrel, beta-blockers, and statins.
Table 2.
In-hospital diagnostic evaluations and medical/surgical treatments, by acute coronary syndrome type
| Total | STEMI | Non-STEMI | Unstable angina | P value | ||
|---|---|---|---|---|---|---|
| N (%) | N | 25 748 | 9569 (37) | 7857 (31) | 8322 (32) | |
| Key investigations | ||||||
| Positive cardiac enzyme, N (%) | 25 748 | 14 845 (57.7) | 6988 (73.0) | 7857 (100) | 0 (0) | <0.001 |
| Coronary angiography, N (%) | 25 748 | 5011 (19.5) | 1875 (19.6) | 1458 (18.6) | 1678 (20.2) | 0.03 |
| In-hospital medical therapy | ||||||
| Thrombolysis, N (%) | 25 745 | 6359 (24.7) | 3964 (41.4) | 1479 (18.8) | 916 (11.0) | <0.001 |
| Door-to-needle time >30 min (STEMI only), N (%) | 7 630 | — | 2421 (31.7) | — | — | — |
| Aspirin, N (%) | 25 748 | 23 944 (93.0) | 9029 (94.4) | 7264 (92.5) | 7651 (91.9) | <0.001 |
| Clopidogrel, N (%) | 25 748 | 24 476 (95.1) | 9173 (95.9) | 7563 (94.9) | 7850 (94.3) | <0.001 |
| Beta-blockers, N (%) | 25 748 | 16 948 (65.8) | 5927 (61.9) | 5308 (67.6) | 5713 (68.7) | <0.001 |
| Statins, N (%) | 25 748 | 18 018 (70.0) | 6471 (67.6) | 5473 (69.7) | 6074 (73.0) | <0.001 |
| ACE-inhibitors/ARBs, N (%) | 25 748 | 7166 (27.8) | 3178 (33.2) | 1979 (25.2) | 2009 (24.1) | <0.001 |
| Nitrates, N (%) | 25 748 | 22 297 (86.6) | 8063 (84.3) | 6796 (86.5) | 7438 (89.4) | <0.001 |
| Calcium channel blockers, N (%) | 25 748 | 2917 (11.3) | 1022 (10.7) | 1065 (13.6) | 830 (10.0) | <0.001 |
| Any heparin, N (%) | 25 748 | 18 018 (70.0) | 6471 (67.6) | 5473 (69.7) | 6074 (73.0) | <0.001 |
| Glycoprotein IIb/IIIa inhibitors, N (%) | 25 748 | 759 (3.0) | 351 (3.7) | 260 (3.3) | 148 (1.8) | <0.001 |
|
| ||||||
| In-hospital reperfusion/other therapy | ||||||
| Percutaneous coronary intervention, N (%) | 25 748 | 3060 (11.9) | 1237 (12.9) | 915 (11.7) | 908 (10.9) | <0.001 |
| Coronary artery bypass graft surgery, N (%) | 25 748 | 347 (1.4) | 108 (1.1) | 96 (1.2) | 143 (1.7) | 0.001 |
| Reperfusion (thrombolysis, PCI, or CABG), N (%) | 25 748 | 8432 (32.8) | 4591 (48.0) | 2087 (26.6) | 1754 (21.1) | <0.001 |
| Temporary pacemaker, N (%) | 25 748 | 200 (0.8) | 88 (0.9) | 40 (0.5) | 72 (0.9) | 0.01 |
| Permanent pacemaker, N (%) | 25 748 | 102 (0.4) | 25 (0.3) | 15 (0.2) | 62 (0.8) | <0.001 |
Table 3.
Discharge medical therapy prescriptions, by acute coronary syndrome type
| Total | STEMI | Non-STEMI | Unstable angina | P value | ||
|---|---|---|---|---|---|---|
| N (%) | N | 25 748 | 9569 (37) | 7857 (31) | 8322 (32) | |
| Discharge medications | ||||||
| Aspirin, N (%) | 25 748 | 19 669 (76.4) | 7177 (75.0) | 6267 (79.8) | 6225 (74.8) | <0.001 |
| Clopidogrel, N (%) | 25 748 | 20 443 (79.4) | 7378 (77.1) | 6545 (83.3) | 6510 (78.2) | <0.001 |
| Beta-blockers, N (%) | 25 748 | 16 133 (62.7) | 5422 (56.7) | 5221 (66.5) | 5490 (66.0) | <0.001 |
| Statins, N (%) | 25 748 | 18057 (70.1) | 6603 (69.0) | 5696 (72.5) | 5758 (69.2) | <0.001 |
| ACE-inhibitors/ARBs, N (%) | 25 748 | 6553 (25.5) | 2809 (29.4) | 1790 (22.8) | 1954 (23.5) | <0.001 |
| Nitrates, N (%) | 25 748 | 19 323 (75.1) | 6642 (69.4) | 5965 (75.9) | 6716 (80.7) | <0.001 |
| Calcium channel blockers, N (%) | 25 748 | 2969 (11.5) | 938 (9.8) | 1015 (12.9) | 1016 (12.2) | <0.001 |
In-hospital outcomes and predictors of outcomes
The unadjusted in-hospital mortality rate was 8.2% in STEMI patients, compared with substantially lower rates in non-STEMI (1.8%) and unstable angina (0.9%) patients (Table 4). Non-fatal MACE such as stroke, re-infarction, heart failure, or cardiogenic shock were also more common in STEMI patients.
Table 4.
In-hospital event rates, by acute coronary syndrome type
| Total | STEMI | Non-STEMI | Unstable angina | P value | ||
|---|---|---|---|---|---|---|
| N | 25 748 | 9569 (37) | 7857 (31) | 8322 (32) | ||
| Unadjusted event rates in-hospital event rates | ||||||
| Death, N (%) | 25 748 | 998 (3.9) | 784 (8.2) | 138 (1.8) | 76 (0.9) | <0.001 |
| Re-infarction, N (%) | 25 748 | 115 (0.5) | 71 (0.7) | 13 (0.2) | 31 (0.4) | <0.001 |
| Stroke (any type), N (%) | 25 748 | 66 (0.3) | 37 (0.4) | 13 (0.2) | 16 (0.2) | 0.01 |
| Heart failure/cardiogenic shock, N (%) | 25 748 | 496 (1.9) | 258 (2.7) | 122 (1.6) | 116 (1.4) | <0.001 |
| Death, re-infarction, stroke, heart failure, or cardiogenic shock N (%) | 25 748 | 1470 (5.7) | 984 (10.3) | 262 (3.3) | 224 (2.7) | <0.001 |
Table 5 demonstrates the patient and process of care variables that are significantly associated with in-hospital mortality before and after adjustment. Patients presenting with STEMI had a higher risk of in-hospital death [odds ratio (OR) (95% confidence interval) = 4.06 (2.36, 7.00)] and in-hospital MACE [OR = 2.75 (1.81, 4.17)] than patients presenting with unstable angina, even after adjustment for potential confounders. There was no difference in the risk of-in-hospital death or in-hospital MACE between patients presenting with non-STEMI compared with patients presenting with unstable angina [in-hospital death OR = 0.92 (0.49, 1.72); in-hospital MACE OR = 0.99 (0.60, 1.61)]. Symptom-to-door time >6h was associated with both in-hospital mortality [OR = 2.29 (1.73, 3.02)], and in-hospital MACE [OR = 2.02 (1.61, 2.51)], even after adjustment. Door-to-needle time <30 min was associated with lower in-hospital mortality [OR = 0.44 (0.27, 0.72)] and in-hospital MACE [OR = 0.52 (0.36, 0.76)] in STEMI patients. Finally, inappropriate thrombolysis in the setting of non-STEMI or unstable angina was associated with increased risk of in-hospital mortality [OR = 1.33 (0.92, 1.91)] and in-hospital MACE [OR = 1.63 (1.19, 2.23)], though the estimate for in-hospital mortality was imprecise.
Table 5.
Unadjusted univariate and random-effects multivariate logistic regression model to evaluate predictors of in-hospital death and combined outcome of in-hospital death, re-infarction, stroke, heart failure, or cardiogenic shock, adjusted for within-centre clustering, GRACE risk score variables [age, heart rate, systolic blood pressure, serum creatinine, Killip class, cardiac enzyme (positive vs. negative), and ST segment deviation using ST-segment myocardial infarction or non-ST-segment myocardial infarction vs. unstable angina as reference]
| In-hospital death OR (95% CI) | In-hospital death, re-infarction, stroke, heart failure, or cardiogenic shock OR (95% CI) | |
|---|---|---|
| Unadjusted | ||
| Age (per year) | 1.00 (0.99, 1.00) | 1.00 (0.99, 1.00) |
| Heart rate (per b.p.m.) | 1.01 (1.01, 1.01) | 1.01 (1.01, 1.01) |
| Systolic blood pressure (per mmHg) | 1.00 (0.99, 1.00) | 0.99 (0.99, 0.99) |
| Serum creatinine (per mg/dL) | 1.11 (1.02, 1.20) | 1.09 (1.02, 1.17) |
| Killip class 1 (ref) vs. >1 | 2.08 (1.71, 2.51) | 2.27 (1.93, 2.66) |
| Positive cardiac enzyme | 3.12 (2.66, 3.65) | 2.07 (1.84, 2.34) |
| STEMI vs. unstable angina (ref) | 9.68 (7.64, 12.3) | 4.14 (3.57, 4.81) |
| Non-STEMI vs. unstable angina (ref) | 1.94 (1.46, 2.57) | 1.25 (1.04, 1.49) |
| Symptom to door >6 vs. <6 h (ref) | 2.69 (2.36, 3.06) | 2.28 (2.04, 2.54) |
| Door to needle <30 vs. >30 min (ref)a | 0.23 (0.17, 0.30) | 0.44 (0.36, 0.54) |
| Inappropriate thrombolysisb | 1.14 (0.98, 1.32) | 1.25 (1.09, 1.43) |
| Adjusted for age, sex, socioeconomic position (education), modified-GRACE risk score variablesb, and within-hospital clustering (random-effects model) | ||
| Age (per year) | 1.01 (1.00, 1.02) | 1.01 (1.00, 1.01) |
| Heart rate (per b.p.m.) | 1.01 (1.00, 1.01) | 1.01 (1.00, 1.01) |
| Systolic blood pressure (per mmHg) | 1.00 (0.99, 1.00) | 0.99 (0.99, 1.00) |
| Serum creatinine (per mg/dL) | 1.21 (1.09, 1.35) | 1.15 (1.04, 1.26) |
| Killip class 1 (ref) vs. >1 | 2.22 (1.70, 2.90) | 2.42 (1.95, 3.00) |
| Positive cardiac enzyme | 1.87 (1.18, 3.00) | 1.57 (1.07, 2.29) |
| STEMI vs. unstable angina (ref) | 4.06 (2.36, 7.00) | 2.75 (1.81, 4.17) |
| Non-STEMI vs. unstable angina (ref) | 0.92 (0.49, 1.72) | 0.99 (0.60, 1.61) |
| Symptom to door >6 vs. <6 h (ref) | 2.29 (1.73, 3.02) | 2.02 (1.61, 2.51) |
| Door to needle <30 vs. >30 min (ref)a | 0.44 (0.27, 0.72) | 0.52 (0.36, 0.76) |
| Inappropriate thrombolysisb | 1.33 (0.92, 1.91) | 1.63 (1.19, 2.23) |
Cardiac arrest at presentation was excluded since those data were not collected, and quality-of-care measures. aDoor-to-needle time analyses were restricted to STEMI patients.
bInappropriate thrombolysis analyses were restricted to non-STEMI/unstable angina patients.
Discussion
Summary of findings
The Kerala ACS Registry represents the largest, contemporary ACS registry in Kerala, and in India overall, to date. ST-segment myocardial infarction was the most common ACS admission diagnosis and had the highest in-hospital mortality and non-fatal event rates, compared with non-STEMI and unstable angina. ST-segment myocardial infarction patients were less likely to have any formal education and more likely to present >6 h after symptom onset. In-hospital medical therapy was relatively high overall for all groups, with anti-platelet therapy being the most common (>97%). Discharge prescription rates followed a similar, albeit lower, pattern. Reperfusion rates were highest for STEMI patients but occurred in less than half of STEMI patients and less commonly in non-STEMI and unstable angina patients. While PCI and CABG were performed relatively infrequently, inappropriate thrombolysis was relatively high for non-STEMI and unstable angina patients.
Patient-level variables such as STEMI diagnosis and delayed symptom-to-door time were associated with increased risk of mortality and MACE, the latter that may represent an opportunity for increased public awareness of seeking emergency care in the setting of symptoms consistent with ACS, as has been done on a pilot basis in Kerala.16 Process of care measures, such as reducing door-to-needle time and inappropriate thrombolysis, represent hospital-level targets for future quality improvement interventions.
Comparison with prior ACS registries
The Kerala ACS Registry had a similar proportion of men compared with prior Indian ACS registries13,14 but also had a higher proportion compared with the National Cardiovascular Data Registry/ACTION ACS Registry in the USA,17 Euro Heart Survey ACS II registry in Europe,18 Clinical Pathways in Acute Coronary Syndromes (CPACS) registry in China,12 and GRACE.19 Patients in the Kerala ACS Registry were older than literature from prior Indian ACS registries but were generally younger than other published registries. In-hospital medical therapy with aspirin and clopidogrel was high and similar to prior literature. Other medical therapy such as beta-blockers and statins were used more commonly than prior Indian data, whereas heparin, angiotensin-converting enzyme-inhibitors/angiotensin receptor blockers, and calcium channel blockers were used less commonly. Reasons for these differences in presentation are unclear but may be related to access to care, underlying differences in risk factors, availability of services, costs, and local practice patterns.
Angiography rates were lower than prior Indian data (20 vs. 23% in CREATE14), whereas PCI rates were higher (12 vs. 7.5% in CREATE14). Both angiography and PCI were substantially lower than rates in ACTION10,17 and Euro Heart Survey ACS I and II.18,19 Angiography and PCI rates were also lower than those reported from the ACCESS registry (58 and 35%, respectively), which included data on 11 731 patients from 134 hospitals from Latin America, Africa, and the Middle East20 but similar to CPACS hospitals in China.12 Thrombolysis in the setting of a STEMI diagnosis was lower in the Kerala ACS Registry than in CREATE14 as well as GRACE,19 while the inappropriate use of thrombolysis in non-STEMI (19%) and unstable angina (11%) patients was higher than data from CREATE (3.5% thrombolysis use in non-STEMI patients),14 GRACE (5.0% in non-STEMI patients and 4% in unstable angina patients),19 and ACCESS (2.5% in non-STEMI patients).20 Reasons for differences in management may include differential access to services (22% of Kerala ACS Registry hospitals had a cardiac catheterization laboratory), personnel (42% of Kerala ACS Registry hospitals did not have a staff cardiologist), and available resources to pay for services due to high-relative out-of-pocket costs for ACS care.2 Low-cost streptokinase was the predominant thrombolytic used (84.8%), so there appears little to no financial incentive for its use in non-STEMI/unstable angina patients.
In-hospital mortality rates for STEMI in the Kerala ACS Registry (8.2%) were higher than GRACE (7%),19 Euro Heart Survey ACS II (6%),21 and ACTION (4.3%)17 and similar to CREATE (8.6%),14 which included mortality over 30 days. On the other hand, in-hospital mortality rates for non-STEMI (1.8%) and unstable angina (0.9%) were generally lower in the Kerala ACS Registry than in prior registries, such as GRACE (6% non-STEMI; 3% unstable angina),19 Euro Heart Survey ACS II (3% non-STEMI),21 ACTION (3.9% non-STEMI),17 and CREATE (3.7% non-STEMI/unstable angina),14 though CREATE included longer follow-up to 30 days. The observed in-hospital mortality rates in the Kerala ACS Registry are generally similar to those expected from calculating average GRACE Risk Scores, ranging from 0.6 to 7% under plausible estimates of age, heart rate, systolic blood pressure, creatinine, Killip classification, ST segment deviation, and cardiac biomarkers in the Kerala ACS Registry (Supplement). Reasons differences in outcomes therefore appear likely to be driven more by the patient presenting characteristics than by differences in management, particularly given the similarities in terms of anti-platelet, heparin, beta-blocker, and statin use between the Kerala ACS Registry and GRACE.20
Implications for quality improvement
The predictors of in-hospital mortality and MACE have implications for local and regional ACS quality improvement efforts. These data support the importance of minimizing time between symptom onset and presentation to the hospital for emergency care, an important potential hurdle as India's emergency response system continues to develop. Appropriate in-hospital and discharge medical therapy are key targets with some areas of high performance (in-hospital anti-platelet use) and other areas of potential improvement (discharge beta-blocker use). The combination of anti-platelet, beta-blocker, and statin drugs should be prioritized over the relatively high in-hospital and discharge nitrate use, which may be used more frequently than prior literature because of higher rates of post-ACS angina, which is not well described in India. Fixed dose combination, or polypill, therapy may be a strategy to improve adherence22 and to lower out-of-pocket costs for medications, which represent a large burden of out-of-pocket costs for chronic disease care in India.23
Inappropriate thrombolytic use appears to represent an opportunity for improved process of care. Notably, stroke rates in these patients were not higher [0 (0%) and 1 (0.1%) strokes in unstable angina and non-STEMI patients receiving thrombolysis compared with 16 (0.2%) and 12 (0.2%) for those who did not receive thrombolysis, respectively], but in-hospital mortality and overall MACE rates were higher, highlighting the importance of this target for quality improvement. Inappropriate thrombolytic use was not associated with a difference in door-to-needle time compared with appropriate thrombolytic use, suggesting that speed of medical care delivery need not be an impediment to high-quality care. In fact, routine use of checklists to streamline appropriate evaluation and management of ACS patients is one potential solution that has been shown to increase quality without sacrificing throughput.10
Strengths and limitations
The primary strengths of our data are the large sample size and broad coverage of hospitals that care for ACS patients throughout Kerala. However, our study has several limitations. First, the data collected are observational, which limits our ability to evaluate causation, especially given the potential for reverse causation whereby individuals who are sicker may seek medical care at hospitals with higher event rates. Second, these data were geographically limited to the state of Kerala and so cannot represent all of India. Third, participation was voluntary, which further limits the representativeness of these data within Kerala; however, these data provide the largest state-level coverage of any ACS registry within India to date. Fourth, patient data were collected in the coronary care unit due to logistical considerations, which may have led to an underestimate in event rates, since patients who died in the casualty ward would not have been included in our analyses. Fifth, we used limited measures of socioeconomic position (education and occupation), which may provide only limited discrimination in terms of socioeconomic determinants of ACS presentation.
Sixth, we did not capture follow-up data to determine post-discharge event rates, adherence to medication and lifestyle recommendations, economic costs, and health-related quality-of-life changes, which are all important metrics for quality care. However, these data provide a key opportunity to develop, implement, and evaluate an ACS quality improvement using the infrastructure developed by the CSI-K, which is currently under active investigation.
Conclusions
These data represent the largest ACS registry in India to date, and demonstrate opportunities for improving the quality of ACS management by focusing on reducing symptom-to-door time, door-to-needle time, and inappropriate use of thrombolysis and increasing use of recommended drugs.
Authors’ contributions
Conception and design: P.P.M., R.M., S.H., M.N.K., G.Z., J.J., K.E., M.A., J.M., M.T., S.J., and D.P. Acquisition of data: P.P.M., R.M., S.H., M.N.K., G.Z., J.J., K.E., M.A., J.M., M.T., and S.J. Analysis and interpretation of data: P.P.M., M.D.H., and D.P. Drafting of manuscript: M.D.H. Critical revision of manuscript for important intellectual content: P.P.M., R.M., S.H., M.N.K., G.Z., J.J., K.E., M.A., J.M., M.T., S.J., and D.P. Statistical analysis: P.P.M., M.D.H., and D.P. Obtaining funding: P.P.M., and M.N.K. Administrative, technical, or material support: R.M., S.H., G.Z., J.J., K.E., M.A., J.M., M.T., and S.J. Supervision: P.P.M., M.N.K., and D.P.
Funding
This work was supported by the Cardiological Society of India-Kerala Chapter. M.D.H. was supported by a NIH training grant in cardiovascular epidemiology and prevention (5 T32 HL069771-08) and has received grant support (moderate) from Scientific Therapeutics Initiative unrelated to this project. D.P. receives partial salary support from a contract award (HHS N268200900026C) from NIH and a grant award (1D43HD065249) from NIH. The study was funded by the Cardiological Society of India—Kerala Chapter, who participated in the study design, data collection, analysis, and writing of the manuscript.
Conflict of interest: none declared.
Supplementary Material
Acknowledgements
P.P.M., M.D.H., and D.P. had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis. We thank Professors Sankar Sharma and K.R. Thankappan (Sree Chithra Tirunal Institute for Medical Sciences and Technology) for contributions as advisors in the conception and design of the study and review of the final manuscript for the Kerala ACS Registry. Neither received compensation for their work.
Appendix
The following investigators participated in this study: Dr Sivaprasad, Medical College Trivandrum; Dr Vijayaraghavan, Kerala Institute of Medical Science Trivandrum; Dr Rajalekshmi, SUT Hospital, Pattam; Dr Tiny Nair, PRS Hospital Trivandrum; Dr Bahuleyan, Anathapurai Hospital, Trivandrum; Dr Biju, Cosmo Hospital; Dr Haridas, PNM Hospital, Kattakada; Dr Madhu Sreedharan, NIMS Hosptial ; Dr Pradeep Kumar, Medical Mission Hospital, Karakonam; Dr Ramesh, S K Hospital ; Dr Pradeep , G G Hospital; Dr Abilash, Gokulam Medical College; Dr Anil Robby, Dr Damodaran Memorial Hospital Kollam; Dr Binu Ramesh, Upasana Hospital Q S Road, Kollam; Dr Kannan, S S M Hospital, Kollam; Dr Shyam, District Hosptial Kollam; Dr Thomas Mathew, Bishop Benziger Hospital, Kollam; Dr Balachandran, Dr Nairs Hospital, Residency Road, Kollam; Dr Viajakumar, Holy Cross Hosptial Kottiayam; Dr Rajan Joseph Manjooran, Pushpagiri Medical College ; Dr Phillipose John, Meenamthotham Hospital Ranni; Dr Jayarma Reddy, Marthoma Hospital, Main Road Pathanamthitta; Dr Rajan Joseph Manjooran, Centuary Hospital, Mulamkuzhi, chenganoor; Dr Abdul Khader, Medical College Hospital Gandhi Nagar; Dr Thomas George, Marian Medical Centre, Pala; Dr Krishna Kumar, Mandiram Hospital, Manganam; Dr Mathew V X, IHM Hospital, Bharananganam; Dr Antony Thomas, Mary Queen Hosptial, Kanjirapally; Dr Madhu/ Dr Anil Kumar, MGDM Hospital, Devagry; Dr Mathew K, MMT Hospital, Mundakayam; Dr Joy C D, Paret Mar Ivanious Hospital, Puthupally; Dr Rajesh Menon, Bharat Hospital Kottayam; Dr Jose Chacko, SH Medical Centre, Kottayam; Dr Phillipose John, Devamatha Hospital, Koothatukulam; Dr Anil Kumar, St. Thomas Hospital, Chettipuzha; Dr Dinesh, MUM Hospital, Monnipally; Dr Thomas Therian, High Range Hospital, Parakode; Dr Prabha S Gupta, Medical College Hospital, Alappuzha; Dr Hegde, Sahrudaya Hospital, Thathampilly; Dr Sajy Kuruttukulam, Medical Trust Hospital, Ernakulam; Dr Thankachan, Lourd's Hospital Vaduthala; Dr A K Abraham, Indiragandhi Cooperative Hospital, Ernakulam; Dr K A Chacko, Lakeshore Hospital, Ernakulam; Dr George Mathew, Lakshmi Hospital, Diwans Road; Dr Eapen Ponnuose, MOSCM Hospital, Ernakulam; Dr Sonnie, Devamatha Hospital, Koothatukulam; Dr Sonnie, San Joe Hospital Perumbavoor; Dr. Govindanunny, Jubilee Mission Hospital, Thrissur; Dr. Rajesh, Amala Medical College, Thrissur; Dr. Rajeev Zacariah, Thrissur Heart Hospital, Thrissur; Dr Iqbal, Aswini Hospital Thrissur; Dr. James K. J., Mother Hospital Olarikkara, Thrissur; Dr. Manikandan, Elite Mission Hospital, Thrissur; Dr Markose K P, San James Hospital, Chalakudy; Dr. Rajeev M R, Co-operative Hospital, Irinjalakuda; Dr T J L Victor, Paduva Hospital, Putheenpeedika; Dr Merly M V, St Antony's Mission Hospital, Pazhuvil; Dr Shojan Augstine, Co-operative Hospital, Thrissur; Dr Reji Roice, San Joseph Hospital, Choondal; Dr Joshy Thomas, Unity Hosptial, Kunnamkulam; Dr Saji Jose/Manikandan, Malangara Mission Hospital, Kunnamkulam; Dr Shaji P S/ Rajesh Krishnan, Shanti Nursing Home, Punnayoorkulam; Dr Madhu , Lal Memorial Hospital, Irinjalakuda; Dr. Rita (Sr), SH Hospital, Pulloor; Dr Sasikumar/Damodharan, Rajah Hospital, Guruvayoor; Dr. Varghese P. K., M I Hospital Engadiyur; Dr Jose Ukken, Modern Hospital, Kodungallur; Dr. Ullas, Daya Speciality Hospital, Thrissur; Dr. Joy P T, Okay Mission Hospital Kodungallur; Dr Jayagopal, Lakshmi Sudha Hospital Palakkad; Dr Jayakumar, Welcare Hosptial, Palakkad; Dr Ragnathan, Valuvanad Hospital, Ottapalam; Dr. Shanmughan , Aswini Hospital Ottapalam; Dr Muralidharan, Co operative Hospital Palakkad; Dr Gopal B, Vijaya Clinic Kunnathurmedu; Dr Kunjuvareed, Crescent Hospital, Vadekkanchery; Dr. Santhakumar, Sanjeevani Hospital Shoranur; Dr Krishnamoorthy, Paalana Hospital, Palakkad; Dr. Anil Saleem , AL-Shifa Hospital Perinthalmana; Dr. Rajeev, Moulana Hospital Perinthalmana; Dr. Somanathan, EMS Hospital Perinthalmana; Dr Mohammed javeed, Edappal Hospital, Edappal; Dr Narayanan, Sukuppuram Hospital Edappal. ; Dr Shajahan , Anugraha Hospital, Changarakulam; Dr Mohammed Nizar, Ansar Hospital, Perimpilavu; Dr Suresh Kumar, M K Haji Hosptial, Tirurgadi Malappuram; Dr Ibrahimkutty, C H Memorial Hospital, Valanchery; Dr. Kochuraghavan, AL-NOOR Hospital (Alukkas Hospital) Malappuram; Dr Nizar, Nizar Memorial Hospital, Valanchery; Dr Hussain, Triur Nursing Home, Triur; Dr. Ramadas, Ramadas Nursing Home Perinthalmana; Dr Asif Masood, Malabar Hospital, Manjery; Dr Joseph P C, Orchid Hosptial, Malappuram; Dr Joy , Prasanthi Hospital manjery; Dr Ali Abakar T P, New M M Hospital, Kuttipuram; Dr Ali Faizal, MIMS Hospital, Calicut; Dr Ashokan Nambiar, Baby Memorial Hospital, Calicut; Dr P K Ashokan, Fathima Hospital, Calicut; Dr Raganathan, Ceeyem Hospital, Vadakara; Dr Balakrishnan, P V S HOSPITAL Railway Road; Dr Mohammed Cholakkal, Iqaraa Hospital, Malamparaba; Dr Rajesh G, Co-operative Hospital, Vadakara; Dr Kuttiyalli, V V HOSPITAL Thamarassery; Dr Viajay Shankar , Co-operative Hosptial, Kozhikode; Dr Raveendran, Koyili Hospital, Kannur; Dr Manoj G, Co-operative Hospital, Thalassery; Dr Ramakrishnan, Teli Medical Centre, Thalassery; Dr Vijayakumar, Dhanalakshmi Hospital, Kannur; Dr Muralidharan T M, St Martin Dep Hospital, Cherukunnu; Dr John F John, Pariyaram Medical College; Dr Govind Krishnan, AKG Hospital, Kannur; Dr Krishnadas, Good Sheperd Hospital, Vythiri; Dr Ajay A R, Leo Hospital Wayanad; Dr Subash, Govt Hospital Wayanad; Dr John K M , M E S Hospital, Sulthan Bathery; Dr Subramanian K K, Victory Hospital, Sulthan Bathery.
References
- 1.New Delhi, India: Registrar General of India; 2009. Report on Causes of Death in India, 2001–2003. [Google Scholar]
- 2.Huffman MD, Rao KD, Pichon-Riviere A, Zhao D, Harikrishnan S, Ramaiya K, Ajay VS, Goenka S, Calcagno JI, Caporale JE, Niu S, Li Y, Liu J, Thankappan KR, Daivadanam M, van Esch J, Murphy A, Moran AE, Gaziano TA, Suhrcke M, Reddy KS, Leeder S, Prabhakaran D. A cross-sectional study of the microeconomic impact of cardiovascular disease hospitalization in four low- and middle-income countries. PloS One. 2011;6:e20821. doi: 10.1371/journal.pone.0020821. doi:10.1371/journal.pone.0020821. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.National Family Health Survey (NFHS-3) Kerala Report. Mumbai, India: International Institute for Population Sciences; 2006. [Google Scholar]
- 4.Government of Kerala. http://www.kerala.gov.in/index.php?option=com_content&view=article&id=2818&itemid=2263. (7 June 2011)
- 5.Thankappan KR, Sivasankaran S, Sarma PS, Mini G, Khader SA, Padmanabhan P, Vasan R. Prevalence-correlates-awareness-treatment and control of hypertension in Kumarakom, Kerala: baseline results of a community-based intervention program. Indian Heart J. 2006;58:28–33. [PubMed] [Google Scholar]
- 6.Mendis S, Abegunde D, Yusuf S, Ebrahim S, Shaper G, Ghannem H, Shengelia B. WHO study on prevention of recurrences of myocardial infarction and stroke (WHO-PREMISE) Bull World Health Organ. 2005;83:820–829. [PMC free article] [PubMed] [Google Scholar]
- 7.Geneva, Switzerland: World Health Organization; 2011. Global Status Report on Noncommunicable Diseases 2010. [Google Scholar]
- 8.Fonarow GC, Gawlinski A, Moughrabi S, Tillisch JH. Improved treatment of coronary heart disease by implementation of a cardiac hospitalization atherosclerosis management program (CHAMP) Am J Cardiol. 2001;87:819–822. doi: 10.1016/s0002-9149(00)01519-8. doi:10.1016/S0002-9149(00)01519-8. [DOI] [PubMed] [Google Scholar]
- 9.Eagle KA, Montoye CK, Riba AL, DeFranco AC, Parrish R, Skorcz S, Baker PL, Faul J, Jani SM, Chen B, Roychoudhury C, Elma MA, Mitchell KR, Mehta RH. Guideline-based standardized care is associated with substantially lower mortality in medicare patients with acute myocardial infarction: The American College of Cardiology's guidelines applied in practice (GAP) projects in Michigan. J Am Coll Cardiol. 2005;46:1242–1248. doi: 10.1016/j.jacc.2004.12.083. doi:10.1016/j.jacc.2004.12.083. [DOI] [PubMed] [Google Scholar]
- 10.Peterson ED, Roe MT, Mulgund J, DeLong ER, Lytle BL, Brindis RG, Smith SC, Jr, Pollack CV, Jr, Newby LK, Harrington RA, Gibler WB, Ohman EM. Association between hospital process performance and outcomes among patients with acute coronary syndromes. JAMA. 2006;295:1912–1920. doi: 10.1001/jama.295.16.1912. doi:10.1001/jama.295.16.1912. [DOI] [PubMed] [Google Scholar]
- 11.Jernberg T, Johanson P, Held C, Svennblad B, Lindback J, Wallentin L. Association between adoption of evidence-based treatment and survival for patients with ST-elevation myocardial infarction. JAMA. 2011;305:1677–1684. doi: 10.1001/jama.2011.522. doi:10.1001/jama.2011.522. [DOI] [PubMed] [Google Scholar]
- 12.Bi Y, Gao R, Patel A, Su S, Gao W, Hu D, Huang D, Kong L, Qi W, Wu Y, Yang Y, Turnbull F. Evidence-based medication use among chinese patients with acute coronary syndromes at the time of hospital discharge and 1 year after hospitalization: Results from the clinical pathways for acute coronary syndromes in China (CPACS) study. Am Heart J. 2009;157:509–516. doi: 10.1016/j.ahj.2008.09.026. doi:10.1016/j.ahj.2008.09.026. [DOI] [PubMed] [Google Scholar]
- 13.Prabhakaran D, Yusuf S, Mehta S, Pogue J, Avezum A, Budaj A, Cerumzynski L, Flather M, Fox K, Hunt D, Lisheng L, Keltai M, Parkhomenko A, Pais P, Reddy S, Ruda M, Hiquing T, Jun Z. Two-year outcomes in patients admitted with non-ST elevation acute coronary syndrome: results of the OASIS registry 1 and 2. Indian Heart J. 2005;57:217–225. [PubMed] [Google Scholar]
- 14.Xavier D, Pais P, Devereaux PJ, Xie C, Prabhakaran D, Reddy KS, Gupta R, Joshi P, Kerkar P, Thanikachalam S, Haridas KK, Jaison TM, Naik S, Maity AK, Yusuf S. Treatment and outcomes of acute coronary syndromes in India (CREATE): a prospective analysis of registry data. Lancet. 2008;371:1435–1442. doi: 10.1016/S0140-6736(08)60623-6. doi:10.1016/S0140-6736(08)60623-6. [DOI] [PubMed] [Google Scholar]
- 15.Granger CB, Goldberg RJ, Dabbous O, Pieper KS, Eagle KA, Cannon CP, Van De Werf F, Avezum A, Goodman SG, Flather MD, Fox KA. Predictors of hospital mortality in the global registry of acute coronary events. Arch Int Med. 2003;163:2345–2353. doi: 10.1001/archinte.163.19.2345. doi:10.1001/archinte.163.19.2345. [DOI] [PubMed] [Google Scholar]
- 16.Prabhakaran D, Jeemon P, Mohanan PP, Govindan U, Geevar Z, Chaturvedi V, Reddy KS. Management of acute coronary syndromes in secondary care settings in Kerala: Impact of a quality improvement programme. Natl Med J India. 2008;21:107–111. [PubMed] [Google Scholar]
- 17.Roe MT, Messenger JC, Weintraub WS, Cannon CP, Fonarow GC, Dai D, Chen AY, Klein LW, Masoudi FA, McKay C, Hewitt K, Brindis RG, Peterson ED, Rumsfeld JS. Treatments, trends, and outcomes of acute myocardial infarction and percutaneous coronary intervention. J Am Coll Cardiol. 2010;56:254–263. doi: 10.1016/j.jacc.2010.05.008. doi:10.1016/j.jacc.2010.05.008. [DOI] [PubMed] [Google Scholar]
- 18.Hasdai D, Behar S, Wallentin L, Danchin N, Gitt AK, Boersma E, Fioretti PM, Simoons ML, Battler A. A prospective survey of the characteristics, treatments and outcomes of patients with acute coronary syndromes in Europe and the Mediterranean basin; the Euro Heart Survey of Acute Coronary Syndromes (Euro Heart survey ACS) Eur Heart J. 2002;23:1190–1201. doi: 10.1053/euhj.2002.3193. doi:10.1053/euhj.2002.3193. [DOI] [PubMed] [Google Scholar]
- 19.Fox KA, Goodman SG, Klein W, Brieger D, Steg PG, Dabbous O, Avezum A. Management of acute coronary syndromes. Variations in practice and outcome; findings from the Global Registry of Acute Coronary Events (GRACE) Eur Heart J. 2002;23:1177–1189. doi: 10.1053/euhj.2001.3081. doi:10.1053/euhj.2001.3081. [DOI] [PubMed] [Google Scholar]
- 20.Investigators TA. Management of acute coronary syndromes in developing countries: acute coronary events-a multinational survey of current management strategies. Am Heart J. 2011;162:852–859. doi: 10.1016/j.ahj.2011.07.029. e822 doi:10.1016/j.ahj.2011.07.029. [DOI] [PubMed] [Google Scholar]
- 21.Mandelzweig L, Battler A, Boyko V, Bueno H, Danchin N, Filippatos G, Gitt A, Hasdai D, Hasin Y, Marrugat J, Van de Werf F, Wallentin L, Behar S. The second euro heart survey on acute coronary syndromes: characteristics, treatment, and outcome of patients with acs in europe and the mediterranean basin in 2004. Eur Heart J. 2006;27:2285–2293. doi: 10.1093/eurheartj/ehl196. doi:10.1093/eurheartj/ehl196. [DOI] [PubMed] [Google Scholar]
- 22.Yusuf S, Pais P, Afzal R, Xavier D, Teo K, Eikelboom J, Sigamani A, Mohan V, Gupta R, Thomas N. Effects of a polypill (polycap) on risk factors in middle-aged individuals without cardiovascular disease (TIPS): a phase II, double-blind, randomised trial. Lancet. 2009;373:1341–1351. doi: 10.1016/S0140-6736(09)60611-5. doi:10.1016/S0140-6736(09)60611-5. [DOI] [PubMed] [Google Scholar]
- 23.Mahal A, Karan A, Engelgau M. The Economic Implications of Non-communicable Disease for India. Washington, DC: World Bank; 2010. Health, nutrition, and population discussion paper. [Google Scholar]
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