ArticleThe British journal of general practice : the journal of the Royal College of General Practitioners2005
The accuracy of the Framingham risk-score in different socioeconomic groups: a prospective study.
Article in The British journal of general practice : the journal of the Royal College of General Practitioners, 2005. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 81 papers, 3 of them syntheses that pooled it.
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Who cites it
81 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Future promise, current clinical ambiguity: a systematic review of machine learning algorithm outputs predicting risk of cardiovascular disease.Open heart · 2026Pooled it
- A systematic review of reasons for and against asking patients about their socioeconomic contexts.International journal for equity in health · 2019Pooled it
- Accuracy and impact of risk assessment in the primary prevention of cardiovascular disease: a systematic review.Heart (British Cardiac Society) · 2006Pooled it
- Development and validation of multicentre study on novel Artificial Intelligence-based Cardiovascular Risk Score (AICVD).Family medicine and community health · 2024Trial
- Sex-specific associations of social determinants of health and genetic risk factors with atherosclerotic cardiovascular diseases incidence in the general population.American journal of preventive cardiology · 2026Article
- Prediction of Risk of Cardiovascular Events in Patients With Stable Angina Using Artificial Intelligence: A Systematic Review.Cardiology research · 2026Review
- First Comparative Evaluation of TyG-ABSI Versus Traditional TyG-Related Indices for Cardiovascular Disease and Mortality Prediction in Hypertensive Patients: TyG-ABSI Versus Traditional TyG-Related Indices.Journal of clinical hypertension (Greenwich, Conn.) · 2026Article
- Diversity and Representation in Cardiovascular Research: Evidence Gaps, Emerging Models, and Policy Implications.International journal of environmental research and public health · 2026Review
- MOSCARD - Multimodal Opportunistic Screening for Cardiovascular Adverse events with Causal Reasoning and De-confounding.Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention · 2026Article
- Association between social risk profile, cardiovascular risk factors control, and future cardiovascular risk.BMC public health · 2025Article
- Mitigating Bias in Opportunistic Screening for MACE with Causal Reasoning.IEEE transactions on artificial intelligence · 2025Article
- Evaluation of the hypercholesterolemia care cascade and compliance with NCEP-ATP III guidelines in Iran based on the WHO STEPS survey.Lipids in health and disease · 2025Article
- Identification of cardiac wall motion abnormalities in diverse populations by deep learning of the electrocardiogram.NPJ digital medicine · 2025Article
- Zero End-Digit Preference in Blood Pressure and Implications for Cardiovascular Disease Risk Prediction-A Study in New Zealand.Journal of clinical medicine · 2024Article
- Body composition estimates from bioelectrical impedance and its association with cardiovascular risk.African journal of primary health care & family medicine · 2024Article
- Optimizing Cardiovascular Health: A Comprehensive Review of Risk Assessment Strategies for Primary Prevention.Cureus · 2024Review
- DeepBiomarker2: Prediction of Alcohol and Substance Use Disorder Risk in Post-Traumatic Stress Disorder Patients Using Electronic Medical Records and Multiple Social Determinants of Health.Journal of personalized medicine · 2024Article
- Association between deep neural network-derived electrocardiographic-age and incident stroke.Frontiers in cardiovascular medicine · 2024Article
- Cardiovascular comorbidities in psoriatic arthritis: state of the art.Therapeutic advances in musculoskeletal disease · 2024Review
- Machine Learning in Cardiovascular Risk Prediction and Precision Preventive Approaches.Current atherosclerosis reports · 2023Review
21 more citing papers are in PubMed but not listed here.
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6 authors.
Funding
Abstract
backgroundThe primary prevention of cardiovascular disease involves using the Framingham risk score to identify high risk patients and then prescribe preventive treatments.
aimTo examine the performance of the Framingham risk score in different socioeconomic groups in a population with high rates of cardiovascular disease. DESIGN OF STUDY: A prospective study.
settingWest of Scotland.
methodThe observed 10-year cardiovascular disease and coronary heart disease mortality rates in 5626 men and 6678 women free from cardiovascular disease from the Renfrew/Paisley Study were compared with predicted rates, stratified by socioeconomic class and by area deprivation score.
resultsThe ratio of predicted to observed cardiovascular mortality rate in the 12 304 men and women with complete risk factor information was 0.56 (95% confidence interval [CI] = 0.52 to 0.60), a relative underestimation of 44%. Cardiovascular disease mortality was underestimated by 48% in manual participants (predicted over observed = 0.52, 95% CI = 0.48 to 0.56) compared to 31% in the non-manual participants (predicted over observed = 0.69, 95% CI = 0.60 to 0.81, P = 0.0005). Underestimation was also worse in participants from deprived areas (P = 0.0017). Only 4.8% of individuals had a 10-year cardiovascular risk of >40% (equivalent to >30% 10-year coronary risk), and 81% of deaths occurred in the rest. If the Framingham score had been recalibrated for manual and non-manual members of this population, an additional 3611 individuals mainly from manual social classes would have reached the treatment threshold.
conclusionCurrently recommended risk scoring methods underestimate risk in socioeconomically deprived individuals. The likely consequence is that preventive treatments are less available to the most needy.
Indexed as
Identifiers
16281999PMC1570792What OpenQuestion holds
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.