A new cardiovascular risk prediction algorithm.
By Tarun Sai LomteApr 23 2024Reviewed by Lily Ramsey, LLM In a recent study published in Nature Medicine , researchers introduced a new cardiovascular risk prediction algorithm.
Notably, recent studies have highlighted conditions linked to high CVD risk, such as cancer, down syndrome, and learning disability, among others, that these tools do not capture. Subjects with preexisting CVD, those missing deprivation data, and those taking statins were excluded. Participants were followed up until the diagnosis of CVD, death, or the end of the study.
Established risk factors from SCORE2, ASCVD, and QRISK3, as well as new candidate variables from the literature, were included as predictor variables. Cause-specific Cox models estimated the 10-year CVD risk, accounting for non-CVD mortality as a competing risk for males and females. Besides, three additional models were developed.
The cohorts were generally similar, except that the QResearch cohorts had more complete data on body mass index , cholesterol, smoking, and ethnicity than the CPRD cohort. Within the derivation cohort, there were 202,424 cases of incident CVD.
Blood Brain Cancer Covid-19 Disability Down Syndrome Heart Heart Disease Learning Disability Medicine Mortality Myocardial Infarction Stroke Syndrome
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