ArticleQatar medical journal2021
Risk prediction models for atherosclerotic cardiovascular disease: A systematic assessment with particular reference to Qatar.
Article in Qatar medical journal, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Risk estimation of cardiovascular disease in Qatar's primary care settings: application of QRISK3 algorithm and sociodemographic predictors.BMC cardiovascular disorders · 2026Article
- Prediction models for incident stroke in the community: a systematic review and meta-analysis of predictive performance.European heart journal. Digital health · 2026Article
- 10-year cardiovascular disease risk and its predictors: a comparison between healthcare workers and the general public in Qatar.BMC public health · 2025Article
- Exploring the Current Tools in Cardiovascular Risk Assessment in the Middle East and the Need for Region-Specific Models - A Scoping Review.Therapeutics and clinical risk management · 2025Review
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4 authors.
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Abstract
backgroundAtherosclerotic cardiovascular disease (ASCVD) is a common disease in the State of Qatar and results in considerable morbidity, impairment of quality of life and mortality. The American College of Cardiology/American Heart Association Pooled Cohort Equations (PCE) is currently used in Qatar to identify those at high risk of ASCVD. However, it is unclear if this is the optimal ASCVD risk prediction model for use in Qatar's ethnically diverse population.
aimsThis systematic review aimed to identify, assess the methodological quality of and compare the properties of established ASCVD risk prediction models for the Qatari population.
methodsTwo reviewers performed head-to-head comparisons of established ASCVD risk calculators systematically. Studies were independently screened according to predefined eligibility criteria and critically appraised using Prediction Model Risk Of Bias Assessment Tool. Data were descriptively summarized and narratively synthesized with reporting of key statistical properties of the models.
resultsWe identified 20,487 studies, of which 41 studies met our eligibility criteria. We identified 16 unique risk prediction models. Overall, 50% (n = 8) of the risk prediction models were judged to be at low risk of bias. Only 13% of the studies (n = 2) were judged at low risk of bias for applicability, namely, PREDICT and QRISK3.Only the PREDICT risk calculator scored low risk in both domains.
conclusionsThere is no existing ASCVD risk calculator particularly well suited for use in Qatar's ethnically diverse population. Of the available models, PREDICT and QRISK3 appear most appropriate because of their inclusion of ethnicity. In the absence of a locally derived ASCVD for Qatar, there is merit in a formal head-to-head comparison between PCE, which is currently in use, and PREDICT and QRISK3.
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