Cardiovascular disease risk stratification in the Pakistani population with and without metabolic syndrome: A single centre cross-sectional study

巴基斯坦人群中代谢综合征患者与非代谢综合征患者的心血管疾病风险分层:一项单中心横断面研究

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Abstract

Existing atherosclerotic cardiovascular disease (ASCVD) risk stratification algorithms are predominantly validated only for Western populations, and do not include parameters of metabolic syndrome (MetS) which may increase the relative risk for cardiovascular disease in South Asians. This study aimed to compare the differences between 10-year ASCVD risk by the Framingham Risk Score (FRS), Pooled Cohort Risk Equations (PCE), and QRISK3 calculators in a cohort of apparently healthy Pakistani adults and stratify the ASCVD risk by MetS status.A cross-sectional study recruited 179 subjects between the ages of 40 to 74 years from the outpatient department of the Aga Khan University Hospital between May 2019 to November 2022. Anthropometry, demography, and blood samples were collected from each subject after informed consent. The IDF criteria were used to categorize subjects as MetS positive (n = 122) and MetS negative (n = 57). The mean age of study participants was 51.07±7.38 years. The average 10-year ASCVD risk (%) for our cohort was calculated to be 15.34 ± 11.60, 9.66 ± 10.87, and 17.02 ± 14.66 using the FRS algorithm, PCE calculator, and QRISK3 calculator respectively. MetS status did not show a statistically significant association with the risk categories determined by any of the calculators, although numerical ASCVD risk estimates were significantly higher in the MetS positive group for all calculators.Although ASCVD risk is a useful way to reduce CVD burden by identifying asymptomatic individuals at the highest risk of developing ASCVD, a high proportion of individuals with MetS may still be identified as low risk by the current risk stratification algorithms in South Asians. Powered validation studies with larger sample sizes and longitudinal follow-up are needed in South Asians to modify existing calculators to make them more applicable to South Asian populations.

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