ArticleGlobal heart2022
WHO Non-Lab-Based CVD Risk Assessment: A Reliable Measure in a North Indian Population.
Article in Global heart, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 2 of them syntheses that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
19 citing papers in PubMed, 2 syntheses or guidelines pooled it, 22 citations in OpenAlex.
- Long-term Cardiovascular and All-Cause Mortality following Elective Infrarenal Repair of the Abdominal Aortic Aneurysm: A Systematic Review and Meta-analysis.Journal of endovascular therapy : an official journal of the International Society of Endovascular Specialists · 2026Pooled it
- Discrimination and calibration performances of non-laboratory-based and laboratory-based cardiovascular risk predictions: a systematic review.Open heart · 2025Pooled it
- Comparing Non-Laboratory-Based and Laboratory-Based Cardiovascular Risk Predictions: Systematic Review and Meta-Analysis.Health science reports · 2026Review
- Prevalence of Cardiovascular Disease Risk Factors and NT pro-BNP for Cardiovascular Disease Risk Prediction among Older People Living with HIV in Almaty, Kazakhstan.Research square · 2026Article
- Congruity between WHO ISH laboratory and non-laboratory-based charts in an urban population in India: A cross-sectional community-based analytical study.Journal of family medicine and primary care · 2026Article
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- Prediction of cardiovascular disease risk in women and individuals with polycystic ovary syndrome using the American Heart Association PREVENT model: A long-term population-based cohort study.American journal of preventive cardiology · 2026Article
- Assessment of 10-year cardiovascular disease risk in Bangladesh: a comparative analysis of laboratory and non-laboratory-based WHO risk prediction models.BMJ public health · 2026Article
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- A multidimensional approach to assess cardiovascular disease risk combining biochemical, hematological, lipid ratios, atherosclerotic cardiovascular disease, and WHO/ISH 10-year risk estimators: a cross-sectional study.American journal of cardiovascular disease · 2025Article
- Comparison of Laboratory and Non-Laboratory-Based 2019 World Health Organization Cardiovascular Risk Charts in the Bhutanese Population.Asia-Pacific journal of public health · 2024Article
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- Estimation of 10-year cardiovascular risk among adult population in western Nepal using nonlaboratory-based WHO/ISH chart, 2023: A cross-sectional study.Health science reports · 2023Article
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- Gut macrobiotic and its metabolic pathways modulate cardiovascular disease.Frontiers in microbiology · 2023Review
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- "I Would Rather Die Drinking than take the Medicine": Role of Alcohol Use Disorder in Loss-to-follow-up of Tuberculosis Treatment in a Rural Area of Ballabgarh, Haryana.Indian journal of community medicine : official publication of Indian Association of Preventive & Social MedicineArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 2 institutions in 2 countries.
Funding
Abstract
Introduction: Timely, affordable, and sustained interventions reduce the risk of heart attack or Stroke in people with a high total risk of cardiovascular diseases (CVD). Risk prediction tools are available to estimate the cardiovascular risk using information on multiple variables. CVD risk charts prepared by the World Health Organization (WHO) has laboratory-based and non-laboratory-based charts with the latter meant for use in resource limited settings. We conducted a study to determine concordance between the laboratory- and non-laboratory risk charts and to estimate the prevalence of selected CVD risk factors in a rural Indian population. Methods: A community-based cross-sectional study was conducted in rural area of Ballabgarh in district Faridabad, Haryana. Sample of 1,018 participants aged 30-69 years was selected randomly from study area. Information on CVDs risk factors was obtained using WHO STEPS questionnaire, anthropometry and laboratory investigation. Risk distribution among the study participants was observed. Concordance between laboratory- and non-laboratory-based WHO CVD risk charts was determined using agreement analysis. Results: The mean age of the study participants was 43.9 (8.9) years and 55.6% participants were women. Among various CVD risk factors, hypertension (39.4%) was the major factor followed by overweight (34.1%) was found to be major factor, followed by current smoking (23.6%) and hypercholesterolemia (18.7%). The concordance between the two charts was 83.3% with kappa value of 0.64. Considering laboratory-based charts as the gold standard, the sensitivity and specificity of non-laboratory-based risk charts at 5% risk as cut-off was 86.5% and 90.3% respectively. Conclusion: The study shows a good agreement between the laboratory-based and non-laboratory-based risk charts. Thus non-laboratory-based risk charts are suitable for risk estimation of CVDs for use in resource limited settings like India.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.