ArticleNature medicine2024
Development and validation of a new algorithm for improved cardiovascular risk prediction.
Article in Nature medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 74 papers, 7 of them syntheses that pooled it.
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Who cites it
74 citing papers in PubMed, 7 syntheses or guidelines pooled it.
- Coronary Artery Disease in Masters Athletes: A Systematic Review.Sports medicine (Auckland, N.Z.) · 2026Pooled it
- Characteristics of Cardiovascular Disease Prediction Models Considering Mental Disorders: A Systematic Review.Journal of the American Heart Association · 2026Pooled it
- Community-based prediction models of cardiovascular events, acute exacerbations and all-cause mortality in individuals with chronic obstructive pulmonary disease: a systematic review and meta-analysis on behalf of the International Cardiovascular and Respiratory Alliance.BMJ open respiratory research · 2026Pooled it
- Female infertility and long-term cardiovascular risk: a systematic review and meta-analysis.Endocrine · 2026Pooled it
- Methods to assess atherosclerotic cardiovascular risk in chronic respiratory diseases: a systematic review.European respiratory review : an official journal of the European Respiratory Society · 2025Pooled it
- Opportunities and Challenges of Cardiovascular Disease Risk Prediction for Primary Prevention Using Machine Learning and Electronic Health Records: A Systematic Review.Reviews in cardiovascular medicine · 2025Pooled it
- Chronic Obstructive Pulmonary Disease and the Management of Cardiopulmonary Risk in the UK: A Systematic Literature Review and Modified Delphi Study.International journal of chronic obstructive pulmonary disease · 2025Pooled it
- Is MASLD an independent risk factor for micro- and macrovascular complications of diabetes? A critical reappraisal and future directions.Diabetologia · 2026Review
- A multicentre evaluation of cardiovascular risk prediction tools in people living with HIV across England (ECARTH study).HIV medicine · 2026Observational
- A Facial Foundation Model for Clinical Biomarker Prediction and Real-World Mobile Deployment.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Dyslipidaemias in cancer patients.European heart journal · 2026Review
- Integration of lipidomic and polygenic risk scores within contemporary clinical cardiovascular risk assessment pathways: a multi-cohort development and validation study.EClinicalMedicine · 2026Article
- Performance of cardiovascular disease risk prediction tools in chronic obstructive pulmonary disease.Annals of the American Thoracic Society · 2026Article
- Article
- Quantifying the Predictive Power of Social Determinants of Health in Cardiovascular Disease and Type 2 Diabetes Progression Using XGBoost: Retrospective Cohort Study.JMIR medical informatics · 2026Article
- Developing and validating the CE-MACE model to predict 1-year major adverse cardiovascular events post-COPD exacerbation using routine healthcare data.The European respiratory journal · 2026Article
- Dyslipidaemia and cardiovascular risk - Key considerations in South Asians.Clinical medicine (London, England) · 2026Review
- Implementation of risk prediction and stratification approaches for ageing populations in Australian healthcare: a systematic review.The Lancet regional health. Western Pacific · 2026Review
- Estimating 5-year absolute risk of cardiovascular disease using routinely collected electronic medical records from Australian general practices.Heart (British Cardiac Society) · 2026Article
- Machine-learning-based cardiovascular mortality prediction using a cumulative PMScientific reports · 2026Observational
14 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
QRISK algorithms use data from millions of people to help clinicians identify individuals at high risk of cardiovascular disease (CVD). Here, we derive and externally validate a new algorithm, which we have named QR4, that incorporates novel risk factors to estimate 10-year CVD risk separately for men and women. Health data from 9.98 million and 6.79 million adults from the United Kingdom were used for derivation and validation of the algorithm, respectively. Cause-specific Cox models were used to develop models to predict CVD risk, and the performance of QR4 was compared with version 3 of QRISK, Systematic Coronary Risk Evaluation 2 (SCORE2) and atherosclerotic cardiovascular disease (ASCVD) risk scores. We identified seven novel risk factors in models for both men and women (brain cancer, lung cancer, Down syndrome, blood cancer, chronic obstructive pulmonary disease, oral cancer and learning disability) and two additional novel risk factors in women (pre-eclampsia and postnatal depression). On external validation, QR4 had a higher C statistic than QRISK3 in both women (0.835 (95% confidence interval (CI), 0.833-0.837) and 0.831 (95% CI, 0.829-0.832) for QR4 and QRISK3, respectively) and men (0.814 (95% CI, 0.812-0.816) and 0.812 (95% CI, 0.810-0.814) for QR4 and QRISK3, respectively). QR4 was also more accurate than the ASCVD and SCORE2 risk scores in both men and women. The QR4 risk score identifies new risk groups and provides superior CVD risk prediction in the United Kingdom compared with other international scoring systems for CVD risk.
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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.