HealthDay News — Cardiovascular disease (CVD) risk assessment tools that do not include severe mental illness as a predictor could be substantially underestimating CVD risk, according to a study published online Sept. 18 in PLOS ONE.
Ruth Cunningham, MBChB, PhD, from University of Otago Wellington in New Zealand, and colleagues used data on prior specialist mental health treatment from the PREDICT study to identify people with severe mental illness. From the 495,388 primary care patients aged 30 to 74 years without prior CVD participating in the study, a subset of 28,734 people with a history of recent contact with specialist mental health services were included.
The researchers found that patients with a history of recent contact with specialist mental health services had a higher observed rate of CVD events vs those without such a history. Among patients with a mental health services history, the PREDICT equations underestimated the CVD risk (mean observed:predicted risk ratio of 1.29 in men and 1.64 in women). However, the PREDICT algorithm performed well for those without mental illness.
“All CVD risk prediction equations should be updated to include mental illness indicators,” the authors write.