-
- Academic Editor
-
-
-
†These authors contributed equally.
Background: Early identification of individuals at a high risk of
cardiovascular disease (CVD) is crucial. This study aimed to construct a nomogram
for CVD risk prediction in the general population. Methods: This
retrospective study analyzed the data between January 2012 and September 2020 at
the Physical Examination Center of the Second Affiliated Hospital of Nanjing
Medical University (randomized 7:3 to the training and validation cohorts). The
outcome was the occurrence of CVD events, which were defined as sudden cardiac
death or any death related to myocardial infarction, acute exacerbation of heart
failure, or stroke. The least absolute shrinkage and selection operator (LASSO)
method and multivariate logistic regression were applied to screen the
significant variables related to CVD. Results: Among the 537 patients,
54 had CVD (10.1%). The median cardiac myosin-binding protein-C (cMyBP-C) level
in the CVD group was higher than in the no-CVD group (42.25 pg/mL VS 25.00 pg/mL,
p = 0.001). After LASSO selection and multivariable analysis, cMyBP-C
(Odds ratio [OR] = 1.004, 95% CI [CI, confidence interval]: 1.000–1.008, p = 0.035), age (OR = 1.023, 95%
CI: 0.999–1.048, p = 0.062), diastolic blood pressure (OR = 1.025, 95%
CI: 0.995–1.058, p = 0.103), cigarettes per day (OR = 1.066, 95% CI:
1.021–1.113, p = 0.003), and family history of CVD (OR = 2.219, 95%
CI: 1.003–4.893, p = 0.047) were associated with future CVD events
(p