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.
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.
| Original language | English |
|---|---|
| Article number | 970 |
| Pages (from-to) | i32-i33 |
| Number of pages | 2 |
| Journal | International Journal of Epidemiology |
| Volume | 50 |
| Issue number | Supplement 1 |
| DOIs | |
| Publication status | Published - Sept 2021 |
| Event | IEA World Congress of Epidemiology 2021 - virtual Duration: 3 Sept 2021 → 6 Sept 2021 Conference number: 22nd https://academic.oup.com/ije/issue/50/Supplement_1 |
