ArticleJournal of family medicine and primary care2020
Estimation of cardiovascular risk in a rural population of Lucknow district using WHO/ISH risk prediction charts.
Article in Journal of family medicine and primary care, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.
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Who cites it
11 citing papers in PubMed, 1 synthesis or guideline pooled it, 17 citations in OpenAlex.
- 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
- Estimation of cardiovascular risk among adults using WHO cardiovascular disease (CVD) risk charts: A community-based cross-sectional study.Journal of family medicine and primary care · 2025Article
- Unveiling Cardiovascular Risk Among Older Adults in Eastern India: A Community-Based Cross-Sectional Study.Cureus · 2025Article
- 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
- Decoding the Lipid-Angiogram Link: Can Serum Lipid Profile Help Predict Your Clogged Arteries?Cureus · 2024Article
- Ten-year risk assessment for cardiovascular disease & associated factors among adult Indians (aged 40-69 yr): Insights from the National Noncommunicable Disease Monitoring Survey (NNMS).The Indian journal of medical research · 2024Article
- Prevalence of Traditional Risk Factors in First-Degree Relatives of Patients With Established Cardiovascular Disease.Cureus · 2023Article
- Assessment of cardiovascular risk using WHO CVD risk prediction chart with respect to hypertension status among Indian population: A secondary analysis of National Family Health Survey (2015-16).Journal of family medicine and primary care · 2022Article
- Recalibrating the Non-Communicable Diseases risk prediction tools for the rural population of Western India.BMC public health · 2022Article
- WHO Non-Lab-Based CVD Risk Assessment: A Reliable Measure in a North Indian Population.Global heart · 2022Article
Corrections and comments
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Authors and funding
5 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
contextCardiovascular diseases (CVDs) are the number one cause of death globally, with low- and middle-income countries being affected disproportionately. By 2020, it is projected that there will be 25 million deaths from CVD worldwide, 19 million of which would be from middle- and low-income countries.
aimsThe aim of this study was to estimate the 10-year risk of cardiovascular events among adults aged ≥40 years in a rural population of Lucknow district using the World Health Organization (WHO)/International Society of Hypertension (ISH) risk prediction charts for SEAR-D region. SETTINGS AND
designThis was a community based cross-sectional study, conducted from September 2017 to August 2018, in the rural areas of Lucknow district. METHODS AND MATERIAL: This study was conducted on 397 subjects aged ≥40 years. The two sets of the WHO/ISH risk prediction charts, with and without cholesterol, for WHO SEAR-D region were used in the study. STATISTICAL ANALYSIS USED: SPSS, version 23 was used for data analysis.
resultsUsing the risk assessment tools, with and without cholesterol, 78.5 and 76.8%, respectively, of the study population were in the 10-year cardiovascular risk category of <10% risk, while 11.2 and 10.4%, respectively, were in the category of ≥20% risk. Risk categories were found to be concordant in 86.3% of the population.
conclusionsThe WHO/ISH risk prediction charts can be used at low-cost resource setting as a tool to predict CVD risk among asymptomatic individuals, thus, helping in early detection and prevention of CVDs in resource-scarce settings.
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