970Comparison of lab-and non-lab based absolute cardiovascular disease risk scores in rural India. (2nd September 2021)

• Record Type: Journal Article
• Authors: Birhanu, Mulugeta Molla; Evans, Roger G.; Zengin, Ayse; Riddell, Michaela A; Kalyanram, Kartik; Kartik, Kamakshi; Suresh, Oduru; Thomas, Nihal; Srikanth, Velandai K.; Thrift, Amanda G.
• Is Part Of: International journal of epidemiology. Volume 50(2021)Supplement 1
• Publication Date: 2021-09-02
• Subjects: Epidemiology -- Periodicals; 614.4
• DOI: 10.1093/ije/dyab168.083
• Languages: English
• ISSNs: 0300-5771

Abstract

Abstract: Background: Over 75% of global cardiovascular (CVD) deaths occur in low-to-middle-income countries (LMICs) . In limited resource settings non-lab-based CVD risk algorithms could be as effective as lab-based algorithms in identifying high-risk groups. We aimed to compare the concordance between lab-and non-lab-based absolute CVD risk algorithms in a LMIC setting. Methods: The study was conducted in the Rishi Valley, Andhra Pradesh, India. Over 8, 000 participants were surveyed between 2012-2015. The 10-year absolute CVD risk score was computed and compared using lab-and-non-lab based Framingham and WHO algorithms. Results: In participants aged 35-74 years, absolute CVD risk score increased with age, and was greater in men than women, for all risk assessment tools. Using the Framingham lab-based algorithm, 15.6% were categorized as high-risk while 14.5% were at high-risk using the non-lab-based algorithm. The non-lab-based Framingham risk score had close agreement and strong correlation with the lab-based Framingham risk score in women (90%, Spearman's rho (rs )=0.81) and men (83%, rs =0.89). Similarly, the non-lab-based WHO risk score had close agreement and strong correlation with the lab-based WHO risk score in women (95%, rs =0.83) and men (92% rs =0.84). In both cases, agreement was better in women than men (P < 0.05 for a two-sample test of proportions). Conclusions: The effectiveness of non-lab-based Framingham and WHO algorithms are comparable to that of lab-based algorithms in discriminating high-and low-risk groups. However, the performance of non-lab-based risk score is better among women than men. Key messages: Non-lab-based CVD risk algorithms could be effective and resource-efficient in LMIC settings, particularly among women.