Predictive value of traditional risk factors for cardiovascular disease in older people: A systematic review
Publication year
2020Source
Preventive Medicine, 132, (2020), article 105986ISSN
Publication type
Article / Letter to editor
Display more detailsDisplay less details
Organization
Neurology
Journal title
Preventive Medicine
Volume
vol. 132
Subject
Radboudumc 3: Disorders of movement DCMN: Donders Center for Medical Neuroscience; Neurology - Radboud University Medical CenterAbstract
With increasing age, associations between traditional risk factors (TRFs) and cardiovascular disease (CVD) shift. It is unknown which mid-life risk factors remain relevant predictors for CVD in older people. We systematically searched PubMed and EMBASE on August 16th 2019 for studies assessing predictive ability of >1 of fourteen TRFs for fatal and non-fatal CVD, in the general population aged 60+. We included 12 studies, comprising 11 unique cohorts. TRF were evaluated in 2 to 11 cohorts, and retained in 0-70% of the cohorts: age (70%), diabetes (64%), male sex (57%), systolic blood pressure (SBP) (50%), smoking (36%), high-density lipoprotein cholesterol (HDL) (33%), left ventricular hypertrophy (LVH) (33%), total cholesterol (22%), diastolic blood pressure (20%), antihypertensive medication use (AHM) (20%), body mass index (BMI) (0%), hypertension (0%), low-density lipoprotein cholesterol (0%). In studies with low to moderate risk of bias, systolic blood pressure (SBP) (80%), smoking (80%) and HDL cholesterol (60%) were more often retained. Model performance was moderate with C-statistics ranging from 0.61 to 0.77. Compared to middle-aged adults, in people aged 60+ different risk factors predict CVD and current prediction models perform only moderate at best. According to most studies, age, sex and diabetes seem valuable predictors of CVD in old-age. SBP, HDL cholesterol and smoking may also have predictive value. Other blood pressure and cholesterol related variables, BMI, and LVH seem of very limited or no additional value. Without competing risk analysis, predictors are overestimated.
This item appears in the following Collection(s)
- Academic publications [246205]
- Electronic publications [133828]
- Faculty of Medical Sciences [93266]
- Open Access publications [107310]
Upload full text
Use your RU credentials (u/z-number and password) to log in with SURFconext to upload a file for processing by the repository team.