Journal
EUROPEAN HEART JOURNAL-QUALITY OF CARE AND CLINICAL OUTCOMES
Volume 8, Issue 1, Pages 70-78Publisher
OXFORD UNIV PRESS
DOI: 10.1093/ehjqcco/qcaa090
Keywords
Adult congenital heart disease; Prediction model; External validation; NTproBNP; Prognosis; Cohort study; Biobank
Categories
Funding
- Harvard Catalyst | The Harvard Clinical and Translational Science Center (National Center for Research Resources)
- Harvard Catalyst | The Harvard Clinical and Translational Science Center (National Center for Advancing Translational Sciences, NIH) [UL1 TR001102]
- Harvard University
- Roche Diagnostics (Indianapolis, IN, USA)
- Erasmus Trustfonds
- Dunlevie Family Fund
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This study developed and validated a risk prediction model for adult congenital heart disease (ACHD), which showed good accuracy and applicability in predicting one-year risk of death, heart failure, or arrhythmia.
Aims Adequate risk prediction can optimize the clinical management in adult congenital heart disease (ACHD). We aimed to update and subsequently validate a previously developed ACHD risk prediction model. Methods and results A prediction model was developed in a prospective cohort study including 602 moderately or severely complex ACHD patients, enrolled as outpatients at a tertiary centre in the Netherlands (2011-2013). Multivariable Cox regression was used to develop a model for predicting the 1-year risks of death, heart failure (HF), or arrhythmia (primary endpoint). The Boston ACHD Biobank study, a prospectively enrolled cohort (n = 749) of outpatients who visited a referral centre in Boston (2012-2017), was used for external validation. The primary endpoint occurred in 153 (26%) and 191 (28%) patients in the derivation and validation cohorts over median follow-up of 5.6 and 2.3 years, respectively. The final model included 5 out of 14 pre-specified predictors with the following hazard ratios; New York Heart Association class >= II: 1.92 [95% confidence interval (CI) 1.28-2.90], cardiac medication 2.52 (95% CI 1.72-3.69), >= 1 reintervention after initial repair: 1.56 (95% CI 1.09-2.22), body mass index: 1.04 (95% CI 1.01-1.07), log2 N-terminal pro B-type natriuretic peptide (pmol/L): 1.48 (95% CI 1.32-1.65). At external validation, the model showed good discrimination (C-statistic 0.79, 95% CI 0.74-0.83) and excellent calibration (calibration-in-the-large = -0.002; calibration slope = 0.99). Conclusion These data support the validity and applicability of a parsimonious ACHD risk model based on five readily available clinical variables to accurately predict the 1-year risk of death, HF, or arrhythmia. This risk tool may help guide appropriate care for moderately or severely complex ACHD.
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