Development and validation of a risk prediction model in patients with adult congenital heart disease
Abstract
Aims: To develop and validate a clinically useful risk prediction tool for patients with adult congenital heart disease (ACHD). Methods and results: A risk model was developed in a prospective cohort of 602 patients with moderate/complex ACHD who routinely visited the outpatient clinic of a tertiary care centre in the Netherlands (2011-2013).
This model was externally validated in a retrospective cohort of 402 ACHD patients (Czech Republic, 2004-2013). The primary endpoint was the 4-year risk of death, heart failure, or arrhythmia, which occurred in 135 of 602 patients (22%).
Model development was performed using multivariable logistic regression. Model performance was assessed with C-statistics and calibration plots.
Of the 14 variables that were selected by an expert panel, the final prediction model included age (OR 1.02, 95% CI 1.00-1.03, p = 0.031), congenital diagnosis (OR 1.52, 95% CI 1.03-2.23, p = 0.034), NYHA class (OR 1.74, 95% CI 1.07-2.84, p = 0.026), cardiac medication (OR 2.27, 95% CI 1.56-3.31, p < 0.001), re-intervention (OR 1.41, 95% CI 0.99-2.01, p = 0.060), BMI (OR 1.03, 95% CI 0.99-1.07, p = 0.123), and NT-proBNP (OR 1.63, 95% CI 1.45-1.84, p < 0.001). Calibration-in-the-large was suboptimal, reflected by a lower observed event rate in the validation cohort (17%) than predicted (36%), likely explained by heterogeneity and different treatment strategies.
The externally validated C-statistic was 0.78 (95% CI 0.72-0.83), indicating good discriminative ability. Conclusion: The proposed ACHD risk score combines six readily available clinical characteristics and NT-proBNP.
This tool is easy to use and can aid in distinguishing high-and low-risk patients, which could further streamline counselling, location of care, and treatment in ACHD. (c) 2018 Elsevier B.V. All rights reserved.