Highlights/Clinical Perspectives
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Premature CAD in South Asians most commonly involves single vessel disease.
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Left anterior descending artery is the most commonly involved artery.
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No population specific angiographic features or risk factors are identified in South Asians.
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Data using advanced imaging modalities to describe plaque features is lacking.
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More research is needed regarding gender differences and risk stratification tools.
Individuals living in South Asia are known to have earlier onset of coronary artery disease (CAD) compared with individuals of other ethnicities. No clear population specific risk factors have been identified for premature CAD in South Asians and studies on angiographic characteristics and their relationship with risk factors are lacking. A systematic literature search was conducted across Pubmed/Medline, Embase, Scopus, CENTRAL, CINAHL, Global Index Medicus and ClinicalTrials.gov databases to retrieve studies related to angiographic characteristics and related risk factors for premature CAD in South Asians. Forty studies with a total of 18,863 patients were included. Sixteen studies divided patients into different age groups, and twenty-four studies included only 1 premature CAD group. There was significant discrepancy in the age cut-offs used to define premature CAD. A majority of studies indicated single vessel disease to be the most common pattern of vessel involvement in young South Asians and left anterior descending artery was the most commonly involved vessel, while older individuals had more multivessel disease than younger counterparts. Younger individuals had higher prevalence of risk factors, demonstrated across individual studies, such as tobacco use, family history, obesity and dyslipidemia; all nonspecific to South Asians. Current available literature does not identify any clear differences regarding angiographic characteristics or associated risk factors for premature CAD in South Asians compared with other ethnicities, however more research is needed using advanced coronary imaging modalities to describe the plaque characteristics. More research is also needed regarding gender differences and risk stratification tools in these patients.
Graphical abstract
Cardiovascular diseases (CVDs), including coronary artery disease (CAD), are a leading cause of mortality globally. In 2021, CVDs were responsible for approximately 19.4 million deaths, accounting for 29% of global mortality. Approximately 9 million of these deaths were attributed to ischemic heart disease. While global life expectancy has considerably increased over the last 40 years, the life expectancy gap between low and high Socio-Demographic Index (SDI) countries continues to expand, with a significant rise in the share of this disparity attributable to CVDs.
A family history of premature CAD is often characterized by symptomatic obstructive coronary lesions at age <55 years in men and <65 years in women, whereas a personal history of premature CAD is often defined as CAD in males <45 years and females <55 years, although no age cut-off is universally accepted. ,, Individuals living in South Asia (a region comprising countries like India, Pakistan, Bangladesh, Afghanistan, Nepal, Sri Lanka, Bhutan and Maldives), are known to have earlier onset of CAD compared with individuals of other ethnicities. The INTERHEART study which was conducted in 52 countries to assess for cardiovascular risk factors showed that the median age for first presentation of acute myocardial infarction (MI) in patients of South Asian ethnicity was 52 years (Interquartile range [IQR] 45 to 60), compared with 62 for Europeans, 63 for Chinese and 60 for Latin American ethnicity. The percent of patients that were under 40 at the time of first presentation of MI, was also highest in those of South Asian ethnicity—10.6%—compared with an overall prevalence of 6%. The North India ST-Segment Elevation Myocardial Infarction (NORIN-STEMI) Study which included 3,635 patients who presented with STEMI to 2 tertiary medical centers in North India reported the median age to be 55 years and 33% of patients were <50 years of age. , Despite a relatively favorable prognosis, CAD in younger individuals living in developing countries is associated with considerable morbidity, emotional distress, economic costs and greater loss of disability-adjusted life years (DALYs), due to its impact on individuals in their most productive years. A higher burden of atherosclerotic CVD has been shown not only in individuals native to South Asia, but also in individuals of South Asian ancestry in different parts of the world, including the United States, United Kingdom and Canada. While these individuals are like native South Asians in genetic and cultural factors, there could be differences related to socioeconomic and education status and healthcare literacy.
Current evidence indicates that the underlying mechanisms related to CVD in South Asians are similar to those observed in other racial or ethnic groups and any unique or population-specific biological or nonbiological risk factor has not been identified. The higher risk in South Asians has been attributed to a greater prevalence of established cardiovascular risk factors—including traditional risk factors like obesity, diabetes, hypertension, smoking and dyslipidemia. There is ongoing research to evaluate other potential risk factors among South Asians, including genetic and epigenetic risk factors as well as the role of lipoprotein(a) and dysfunctional HDL, but no such specific risk factor has been identified as yet. , With regards to angiographic characteristics, previous studies have shown that the majority of cases of premature CAD in South Asians are characterized by single vessel disease (SVD). , This pattern of single vessel involvement in premature CAD has also been demonstrated in other ethnicities. , Furthermore, some studies conducted on Americans of South-Asian ancestry suggested them to have a smaller coronary diameter and more severe coronary stenosis than Caucasians, although these studies were not just focused on younger individuals. , However, a study conducted on South Asians living in the UK showed no difference in coronary artery size compared to Caucasians that were matched using strict criteria. Large, high-quality studies on the angiographic characteristics and associated risk factors of premature CAD in South Asians are lacking. We attempted to perform a systematic review of the available literature on premature CAD in South Asians with a focus on angiographic characteristics and associated risk factors.
Methodology
Search strategy
This study has been conducted in accordance with the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) guidelines ( Supplemental Table 1 and 2 ). A comprehensive protocol for this review was registered with PROSPERO (The International Prospective Register of Systematic Reviews), ID CRD420250634372. This protocol served as a framework for all search and screening methods carried out during the review. An experienced medical librarian (MI), with input from the first author (SP) and senior author (NB), designed a search strategy for PubMed/Medline by refining search terms using benchmark articles. This approach incorporated both natural language keywords and controlled vocabulary (when available) to capture concepts of angiographic characteristics, premature CAD and South Asians ( Supplemental Table 3 ). The finalized PubMed/Medline strategy was subsequently adapted for use across other databases ( Supplemental Table 3 ). Comprehensive searches were conducted from each database’s inception through July 30th, 2024, in the following sources: PubMed/Medline (including Pre-Medline and Non-Medline), Embase (Elsevier), Scopus (Elsevier), Cochrane Central Register of Controlled Trials (CENTRAL; Wiley), Cumulative Index to Nursing and Allied Health Literature (CINAHL) Plus with Full Text (EBSCOhost), Global Index Medicus (IMEMR and IMSEAR; World Health Organization) and ClinicalTrials.gov. When available, filters were applied to limit results to English-language publications. Reference lists of the included studies were also reviewed to identify additional relevant sources. All retrieved records were deduplicated using Clarivate EndNote (version 21), following a previously published methodology.
Study selection and eligibility criteria
The following eligibility criteria were utilized to include studies in this review: (a) Randomized control trials (RCTs) or observational studies (b) studies evaluating angiographic characteristics of premature CAD among South Asians, with or without age-wise comparison, with at least 1 group of patients having age <50 for males or <60 years for females. Studies were considered for inclusion irrespective of geographic location, as well as patient characteristics such as age, gender, race, or existing comorbidities. Exclusion criteria included case reports, review articles, correspondence, editorials, book chapters and non-English publications. Two investigators (SP and JJ) independently assessed the preliminary studies for eligibility, with any discrepancies resolved through discussion or consultation with the senior author (NB).
Data extraction and quality assessment
Two investigators (SP and JJ) independently collected data from included studies. Information such as the first author, year of publication, sample size, baseline patient characteristics, and main results of the studies related to angiographic characteristics and associated risk factors were extracted in an Excel Spreadsheet by both investigators. They then cross-verified the data to ensure accuracy and correct any discrepancies. The risk of bias was analyzed for all the eligible studies by 1 of 2 researchers (SP, JJ) utilizing the Newcastle-Ottawa Scale (NOS) for nonrandomized studies ( Supplemental Table 4–5 ). A previously utilized variation of the NOS for cross sectional studies was used ( Supplemental Table 6 ).
Statistical methods
A meta-analysis using a random-effects model was conducted to account for potential heterogeneity across studies and to estimate odds ratios for each risk factor comparing premature CAD to nonpremature CAD. Study heterogeneity was assessed using the I² statistic, with values ≥50% indicating substantial heterogeneity. Funnel plots were used to assess potential publication bias, which was inferred from asymmetry. All hypothesis tests were two-sided, and p-values <0.05 were considered statistically significant. All analyses were performed in R version 4.2.2 (R Foundation for Statistical Computing) using the “meta” and “metasens” packages.
Results
Search results
The search yielded 6,668 records, with 2,326 duplicates removed prior to the screening process using automation tools. ( Figure 1 ). A total of 4,342 records were initially screened from which 4,122 were excluded. Of the 220 remaining citations, full-text review resulted in the exclusion of 183 citations due to poor quality data, duplicate data or failure to meet inclusion criteria. Three citations were identified through analysis of references cited in the included publications. The remaining 40 studies were included in our analysis, with a total of 18,863 patients ( Table 1 and Table 2 ).
Search strategy depicted using preferred reporting items for systematic reviews and meta-analyses (PRISMA) 2020 flow diagram for new systematic reviews.
Table 1
Baseline characteristics of studies characterizing patients based on age
| References | Enrolment | Prospective/Retrospective | Age limit (years) | Mean age (standard deviation SD) | Study country | Total | Female % | Diabetic % | Smoker % | Hyper-lipidemia % | Hyper-tension % | Family history of CAD | STEMI % | NSTEMI/UA |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Khan et al. | ACS (STEMI, NSTEMI, UA) | Prospective | <35, | 32.36 ± 3.38, | Pakistan | 103 | 13.59 | 11.7 | 41.7 | NR | 31.1 | 12.6 | 94.2 | 5.8 |
| >35 | 57.49 ± 10.9 | 103 | 22.33 | 33 | 33 | NR | 62.1 | 4.9 | 88.3 | 11.65 | ||||
| Batra et al. | STEMI (undergoing PCI) | Prospective | <40 | NR | Pakistan | 50 | 16 | 20 | 26 | 26 | 14 | 16 | 100 | 0 |
| >40 | NR | 365 | 32.1 | 35.6 | 30.4 | 25.8 | 59.7 | 4.9 | 100 | 0 | ||||
| Faisal et al. | ACS (STEMI, NSTEMI, UA) | Retrospective | <35 | 31.40 ± 3.79 | Pakistan | 552 | 16.1 | NR | NR | NR | NR | NR | NR | NR |
| >35 | 52.98 ± 8.65 | 716 | 21.2 | NR | NR | NR | NR | NR | NR | NR | ||||
| Murugan et al. | ACS | Retrospective | <40 | NR | India | 198 | 16.2 | 17 | 3 | 5 | 13 | 2.5 | 44.4 | 55.6 |
| >40 | NR | 226 | 17.9 | 21.5 | 4.0 | 6.3 | 17.0 | 3.6 | 43.5 | 56.5 | ||||
| Gupta et al. | AMI patients | Retrospective | <35 | 28.52 ± 4.18 | India | 102 | 2.9 | 5.9 | 68.6 | NR | 9.8 | 27.5 | 91.20 | 8.80 |
| >35 | 52.38 ± 9.65 | 104 | 13.5 | 21.2 | 61.5 | NR | 24.0 | 20.2 | 91.30 | 8.70 | ||||
| Kumar et al. | STEMI | Prospective | <40 | 36.5 ± 4.4 | Pakistan | 466 | 17.60% | 26.6% | 33% | NR | 40.8% | 8.2% | 100% | 0 |
| >40 | 57.7 ± 9.4 | 4220 | 21.6% | 36.4% | 24.7% | NR | 54.5% | 3.2% | 100% | 0 | ||||
| Kaul et al. | STEMI/ NSTEMI | Prospective | <40 | 34.5 | India | 104 | 2.8% | (3.8%) | 61.5% | 29.8% | 26.9% | 24.0% | NR | NR |
| >40 | 52.85 | 100 | NR | (18%) | (42%) | (33%) | (35%) | (25%) | NR | NR | ||||
| Sharma et al. | CAD (undergoing PCI) | Prospective | F < 45 | NR | India | 61 | 100% | 26.2 | 13.1 | NR | 37.7 | NR | 41.7 | 58.3 |
| F 45 to 60 | NR | 299 | 100% | 42.5 | 9.0 | NR | 59.9 | NR | 40.2 | 59.8 | ||||
| F > 60 | NR | 576 | 100% | 40.8 | 6.6 | NR | 68.9 | NR | 36.9 | 60.1 | ||||
| M < 40 | NR | 151 | 0 | 17.9 | 16.5 | NR | 23.8 | NR | 56.3 | 43.8 | ||||
| M 40 to 55 | NR | 939 | 0 | 34.0 | 20.3 | NR | 41.3 | NR | 48.7 | 51.3 | ||||
| M > 55 | NR | 2646 | 0 | 39.5 | 13.5 | NR | 58.8 | NR | 39.2 | 55.8 | ||||
| Sharma et al. | ACS (STEMI, NSTEMI, UA) | Cross sectional | <30 | NR | India | 47 | 10.6 | 14.89 | 23.4 | 12.7 | 8.52 | 19.14 | 91.48 | 8.51 |
| M 30 to 45, F 30 to 55 | NR | 183 | 22.41% | 14.76 | 59.01 | 18.03 | 9.28 | 3.28 | 69.94 | 30.05 | ||||
| Bhattacharjee et al. | ACS (STEMI, NSTEMI, UA) | Cross sectional | <45 | 36.65 ± 6.48 | India | 46 | 4.3% | 26.08 | 73.91 | 26.08 | 32.61 | 6.52 | 89.13 | 10.87 |
| >45 | 61.58 ± 8.27 | 45 | 20% | 42.22 | 46.67 | 46.67 | 68.89 | 2.22 | 71.11% | 28.89 | ||||
| Islam et al. | CAD (STEMI, NSTEMI, UA and chronic stable angina) | Cross sectional | <40 | 35.40 ± 4.20 | Bangla-desh | 60 | 21.70 | 18.30 | 63.30 | 85.00 | 41.70 | NR | NR | NR |
| >40 | 53.70 ± 7.30 | 60 | 25.70 | 36.70 | 40.00 | 73.30 | 65.00 | NR | NR | NR | ||||
| Saghir et al. | CAD undergoing angiography | Prospective | <40 | NR | Pakistan | 102 | 16 | 14 | 70 | NR | 34 | 30 | 63 | 37 |
| >40 | NR | 197 | 21 | 36 | 75 | NR | 42 | 26 | 53 | 47 | ||||
| Shah et al. | First episode of MI | Prospective | <40 | NR | Pakistan | 45 | 20 | 20 | NR | NR | 33.33 | NR | NR | NR |
| >40 | NR | 236 | 22.45 | 27.5 | NR | NR | 30.6 | NR | NR | NR | ||||
| Chaudhary et al. | CAD (STEMI, NSTEMI, UA and chronic stable angina) Undergoing coronary CCTA | Cross sectional | <40 | 34.71± 4.36 | India | 60 | 8 | 6.67 | 45 | 76.67 | 31.67 | NR | 0 | 33 |
| >40 | NR | 36 | 25 | 27.78 | 30.56 | 72.22 | 55.56 | NR | NR | NR | ||||
| Khan et al. | ACS (STEMI, NSTEMI, UA) | Prospective | <40 | 37.2 | Bangla-desh | 32 | 100 | 12.5 | 84.4 | 56.3 | 46.9 | 34.4 | NR | NR |
| >40 | 50.6 | 32 | 6.2 | 21.8 | 75.0 | 28.1 | 43.7 | 25 | NR | NR | ||||
| Prajapati et al. | ACS (STEMI, NSTEMI, UA) | Prospective | <40 | 34.69 ± 4.55 | India | 100 | 89 | 11 | 34 | 47 | 16 | 19 | 85 | 15 |
| >40 | 56.18 ± 8.72 | 100 | 11 | 19 | 45 | 47 | 32 | 9 | 81 | 19 |
ACS = acute coronary syndrome; CCTA = coronary computed tomography angiography; MI = myocardial infarction; NR = not reported; NSTEMI = non-ST- elevation myocardial infarction; PCI = percutaneous coronary intervention; STEMI = ST- elevation myocardial infarction; UA = unstable angina.
Table 2
Baseline characteristics of studies without age-based comparisons
| References | Study country | Enrolment | Prospective/Retrospective | Age limit | Mean age | Total | Female % | Diabetic % | Smoker % | Hyperlipidemia % | Hypertension % | Family history of CAD | STEMI % | NSTEMI/UA % |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Haque et al. | Bangladesh | ACS (STEMI, NSTEMI, UA) | Retrospective | <40 | NR | 64 | 17.2 | 15.62 | 64.06 | 59 | 55 | NR | 75 | 25 |
| Sinha et al. | India | STEMI | Prospective | <30 | 26.0 ± 3.9 | 1116 | 4.9 | 17.2 | 78.5 | 21.2 | 20.5 | 46.8 | 100 | 0 |
| Malik et al. | Bangladesh | STEMI | Cross sectional | <35 | 31.19 ± 3.81 | 266 | 5.3 | 16.9 | 77.4 | 70.3 | 21.4 | 47.4 | 100 | 0 |
| Ashida et al. | India | ACS (STEMI, NSTEMI, UA) | Ambidirectional cohort | <45 | 39.02 ± 5.6 | 224 | 20.1 | 29.9 | 25.9 | 57.6 | 15.2 | 16.5 | 53.1 | 46.9 |
| Mustafa et al. | Pakistan | ACS and chronic stable angina | Prospective | <40 | 36.4 ± 4.1 | 102 | 8.8 | 26.5 | 72.5 | 43.1 | 34.3 | 40.2 | 52.9 | 30.4 |
| Anjum et al. | Pakistan | ACS (STEMI, NSTEMI, UA) | Prospective | <35 | 31.4 ± 3.5 | 221 | 11.8 | 21.7 | 64.7 | NR | 25.3 | 14.5 | NR | NR |
| Joshi et al. | India | STEMI and NSTEMI | Retrospective | <30 | 27.63 ± 2.03 | 22 | 4.5 | 9 | 54.4 | 36.3 | 13.6 | 27.2 | 77.2 | 22.7 |
| Gopalakrishnan et al. | India | ACS and chronic stable angina | Ambidirectional cohort | <30 | 26.7 ± 3.29 | 159 | 8 | 4.4 | 63.5 | 88.3 | 8.8 | 29.6 | 81.8 | 6.9 |
| Dash et al. | India | STEMI | Prospective | 45 | 26.7 ± 3.29 | 198 | 6.5 | 21 | 63.5 | 28.5 | 16 | NR | NA | NA |
| Sajjanar et al. | India | ACS | Prospective | 40 | 36.23±3.89 | 133 | 24 | 30 | 37.5 | NR | 16.5 | 19.5 | 3.2 | 6.76 |
| Reddy et al. | India | ACS | Prospective | 45 | 38.1 ± 5.8 | 50 | 8 | 16 | 72 | NR | 12 | NR | 96 | 4 |
| Prakash et al. | India | ACS and chronic stable angina | Retrospective | 40 | 35.8 | 117 | 18.8 | 21.36 | 8.54 | 7.69 | 30.76 | 9.4 | 57.2 | 19.6 |
| Deora et al. | India | ACS (STEMI, NSTEMI, UA) | Retrospective | <40 | NR | 820 | 7.3 | 14 | 68.41 | 83.5 | 17 | 62 | 74.5 | 24.5 |
| Revaiah et al. | India | ACS | Prospective | 40 | 35.5 ± 4.7 | 182 | 3.8 | 15.9 | 56 | NR | 29.7 | 18.2 | 82 | 18 |
| Mukhopadhyay et al. | India | ACS | Prospective | 45 | 37.42 ± 5.18 | 100 | 18 | 43 | 71 | 44 | 41 | 23 | 66 | 34 |
| Jariwala et al. | India | ACS | Retrospective | 45 | 367 | 30.8 | 41.4 | 18.5 | 52.9 | 44.7 | 26.4 | 52.31 | 41.4 | |
| Singh et al. | India | STEMI | Prospective | 45 | 39 ± 6.3 | 130 | 3.2 | 16.8 | 37.6 | 14.4 | 16.8 | 6.4 | NA | NA |
| Khanna et al. | India | ACS | Observational | 40 | 172 | 17.4 | NR | NR | NR | NR | NR | 77.32 | 22.68 | |
| Dondapati et al. | India | ACS (STEMI, NSTEMI, UA) | Prospective | female 55, male 45 | 60 | 33.33 | 40 | 10 | 66.6 | 28.33 | 33.33 | 50 | 50 | |
| Halder et al. | India | ACS (STEMI, NSTEMI, UA) | Prospective | <40 | NR | 50 | 20 | 18 | 50 | NR | 34 | NR | NR | NR |
| Sanghamitra et al. | India | STEMI | Prospective | 40 | 35.12 ± 4.2 | 108 | 15.74 | 22.2 | 76.9 | NR | 18.5 | 13.9 | 100 | 0 |
| Kanher et al. | India | ACS (STEMI, NSTEMI, UA) | Prospective | 35 | 26.68 ± 4.04 | 365 | 30.7 | NR | 46.6 | NR | NR | NR | 34.5 | 65.5 |
| Chandra et al. | India | ACS (STEMI, NSTEMI, UA) | Prospective | 35 | NR | 40 | NR | 18.6 | 48.8 | NR | 4.7 | 14 | NR | NR |
| Khan et al. | Pakistan | ACS (STEMI, NSTEMI, UA) | Prospective | Male <45 | 38 ± 6 | 270 | 0 | 17.4 | 50.4 | 8.9 | 37.8 | 10 | 89.6 | 10.4 |
| Female <45 | 40 ± 5 | 65 | 100 | 35.4 | 6.2 | 10.8 | 58.5 | 4.6 | 78.5 | 21.6 |
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