Objective: To evaluate the performance of the QRISK2-2011 score for predicting the 10 year risk of cardiovascular disease in an independent UK cohort of patients from general practice and to compare it with earlier versions of the model and a National Institute for Health and Clinical Excellence version of the Framingham equation.
Design: Prospective cohort study to validate a cardiovascular risk score with routinely collected data between June 1994 and June 2008.
Setting: 364 practices from the United Kingdom contributing to The Health Improvement Network (THIN) database.
Participants: Two million patients aged 30 to 84 years (11.8 million person years) with 93,564 cardiovascular events.
Main Outcome Measure: First diagnosis of cardiovascular disease (myocardial infarction, angina, coronary heart disease, stroke, and transient ischaemic attack) recorded in general practice records.
Results: Results from this independent and external validation of QRISK2-2011 indicate good performance data when compared with the NICE version of the Framingham equation. QRISK2-2011 had better ability to identify those at high risk of developing cardiovascular disease than did the NICE Framingham equation. QRISK2-2011 is well calibrated, with reasonable agreement between observed and predicted outcomes, whereas the NICE Framingham equation seems to consistently over-predict risk in men by about 5% and shows poor calibration in women.
Conclusions: QRISK2-2011 seems to be a useful model, with good discriminative and calibration properties when compared with the NICE version of the Framingham equation. Furthermore, based on current high risk thresholds, concerns exist on the clinical usefulness of the NICE version of the Framingham equation for identifying women at high risk of developing cardiovascular disease. At current thresholds the NICE version of the Framingham equation has no clinical benefit in either men or women.
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http://dx.doi.org/10.1136/bmj.e4181 | DOI Listing |
Circ Genom Precis Med
January 2025
Division of Cardiology, Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Boston. (S.M.U., K.P., B.T., A.C.F., P.N.).
Background: Earlier identification of high coronary artery disease (CAD) risk individuals may enable more effective prevention strategies. However, existing 10-year risk frameworks are ineffective at earlier identification. We sought to understand how the variable importance of genomic and clinical factors across life stages may significantly improve lifelong CAD event prediction.
View Article and Find Full Text PDFEBioMedicine
January 2025
Department of Endocrinology, University of Groningen, University Medical Center Groningen, Groningen, Netherlands.
Background: Coronary artery disease (CAD) comprises one of the leading causes of morbidity and mortality both in the European population and globally. All established clinical risk stratification scores and models require blood lipids and physical measurements. The latest reports of the European Commission suggest that attracting health professionals to collect these data can be challenging, both from a logistic and cost perspective, which limits the usefulness of established models and makes them unsuitable for population-wide screening in resource-limited settings, i.
View Article and Find Full Text PDFJ Am Heart Assoc
December 2024
Ambulatory Healthcare Services Abu Dhabi United Arab Emirates.
Background: Cardiovascular disease risk assessment is a key tool in primary prevention. The ADRS (Abu Dhabi Risk Study) is a retrospective cohort study aiming to develop 10-year risk prediction equations for coronary artery disease (CAD), stroke, and atherosclerotic cardiovascular disease (ASCVD), and validate international risk equations.
Methods And Results: The 8699 participants were examined in the Abu Dhabi cardiovascular screening program from 2011 to 2013 with a subsequent average follow-up of 9.
West Afr J Med
November 2024
Department of Medicine, University of Jos/Jos University Teaching Hospital, Jos. Email:
Introduction/background: Assessing cardiovascular disease (CVD) risk is necessary in preventive cardiology. Studies have imputed CVD risk factors in algorithms to predict ASCVD. These various scores were derived from risk equations acquired from other populations.
View Article and Find Full Text PDFWest Afr J Med
November 2024
Department of Medicine, University of Jos/Jos University Teaching Hospital, Jos. Email:
Introduction/background: Assessing cardiovascular disease (CVD) risk is necessary in preventive cardiology. Studies have imputed CVD risk factors in algorithms to predict ASCVD. These various scores were derived from risk equations acquired from other populations.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!