ArticleGlobal heart2021
Developing Non-Laboratory Cardiovascular Risk Assessment Charts and Validating Laboratory and Non-Laboratory-Based Models.
Article in Global heart, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.
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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.
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Who cites it
9 citing papers in PubMed, 1 synthesis or guideline pooled it, 11 citations in OpenAlex.
- Discrimination and calibration performances of non-laboratory-based and laboratory-based cardiovascular risk predictions: a systematic review.Open heart · 2025Pooled it
- Systematic review and meta-analysis of cardiovascular disease risk among hypertensive patients in Africa.International journal of cardiology. Cardiovascular risk and prevention · 2026Review
- Clinical profile and short-term outcomes of acute myocardial infarction patients.Bioinformation · 2026Article
- Prediction of cardiovascular risk: validation of a non-laboratory and a laboratory-based score in a Brazilian community-based cohort of the PURE study.Lancet regional health. Americas · 2025Article
- Patterns among factors associated with myocardial infarction: chi-squared automatic interaction detection tree and binary logit model.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
- The Role of Visualization in Estimating Cardiovascular Disease Risk: Scoping Review.JMIR public health and surveillance · 2024Article
- First Iranian guidelines for the diagnosis, management, and treatment of hyperlipidemia in adults.Journal of research in medical sciences : the official journal of Isfahan University of Medical Sciences · 2024Article
- Ethnicity affects the risk factors of acute myocardial infarction and should be considered in educational programs.Frontiers in cardiovascular medicine · 2022Article
Corrections and comments
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Authors and funding
8 authors at 7 institutions in 8 countries.
Funding
Abstract
Background: Developing simplified risk assessment model based on non-laboratory risk factors that could determine cardiovascular risk as accurately as laboratory-based one can be valuable, particularly in developing countries where there are limited resources. Objective: To develop a simplified non-laboratory cardiovascular disease risk assessment chart based on previously reported laboratory-based chart and evaluate internal and external validation, and recalibration of both risk models to assess the performance of risk scoring tools in other population. Methods: A 10-year non-laboratory-based risk prediction chart was developed for fatal and non-fatal CVD using Cox Proportional Hazard regression. Data from the Isfahan Cohort Study (ICS), a population-based study among 6504 adults aged ≥ 35 years, followed-up for at least ten years was used for the non-laboratory-based model derivation. Participants were followed up until the occurrence of CVD events. Tehran Lipid and Glucose Study (TLGS) data was used to evaluate the external validity of both non-laboratory and laboratory risk assessment models in other populations rather than one used in the model derivation. Results: The discrimination and calibration analysis of the non-laboratory model showed the following values of Harrell's C: 0.73 (95% CI 0.71-0.74), and Nam-D'Agostino χ Conclusions: Our simplified risk assessment model based on non-laboratory risk factors could determine cardiovascular risk as accurately as laboratory-based one. This approach can provide simple risk assessment tool where laboratory testing is unavailable, inconvenient, and costly.
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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.