학술논문

Incorporation of natriuretic peptides with clinical risk scores to predict heart failure among individuals with dysglycaemia.
Document Type
article
Source
European Journal of Heart Failure. 24(1)
Subject
Biomarkers
Diabetes
Heart failure
Pre-diabetes
Risk prediction
Risk stratification
Adult
Cohort Studies
Glucose Metabolism Disorders
Heart Failure
Humans
Natriuretic Peptides
Risk Assessment
Risk Factors
Language
Abstract
AIMS: To evaluate the performance of the WATCH-DM risk score, a clinical risk score for heart failure (HF), in patients with dysglycaemia and in combination with natriuretic peptides (NPs). METHODS AND RESULTS: Adults with diabetes/pre-diabetes free of HF at baseline from four cohort studies (ARIC, CHS, FHS, and MESA) were included. The machine learning- [WATCH-DM(ml)] and integer-based [WATCH-DM(i)] scores were used to estimate the 5-year risk of incident HF. Discrimination was assessed by Harrells concordance index (C-index) and calibration by the Greenwood-Nam-DAgostino (GND) statistic. Improvement in model performance with the addition of NP levels was assessed by C-index and continuous net reclassification improvement (NRI). Of the 8938 participants included, 3554 (39.8%) had diabetes and 432 (4.8%) developed HF within 5 years. The WATCH-DM(ml) and WATCH-DM(i) scores demonstrated high discrimination for predicting HF risk among individuals with dysglycaemia (C-indices = 0.80 and 0.71, respectively), with no evidence of miscalibration (GND P ≥0.10). The C-index of elevated NP levels alone for predicting incident HF among individuals with dysglycaemia was significantly higher among participants with low/intermediate (