Heart failure risk predictions in adult patients with congenital heart disease: a systematic review. Issue 21 (26th July 2019)

• Record Type: Journal Article
• Authors: Wang, Fei; Harel-Sterling, Lee; Cohen, Sarah; Liu, Aihua; Brophy, James M; Paradis, Gilles; Marelli, Ariane J
• Is Part Of: Heart. Volume 105:Issue 21(2019)
• Page Start: 1661
• Page End: 1669
• Publication Date: 2019-07-26
• Subjects: congenital heart disease -- heart failure -- cardiac risk factors and prevention -- systemic review; Heart -- Diseases -- Treatment -- Periodicals; Cardiology -- Periodicals; 616.12
• DOI: 10.1136/heartjnl-2019-314977
• Languages: English
• ISSNs: 1355-6037

Abstract

Abstract : To summarise existing heart failure (HF) risk prediction models and describe the risk factors for HF-related adverse outcomes in adult patients with congenital heart disease (CHD). We performed a systematic search of MEDLINE, EMBASE and Cochrane databases from January 1996 to December 2018. Studies were eligible if they developed multivariable models for risk prediction of decompensated HF in adult patients with CHD (ACHD), death in patients with ACHD-HF or both, or if they reported corresponding predictors. A standardised form was used to extract information from selected studies. Twenty-five studies met the inclusion criteria and all studies were at moderate to high risk of bias. One study derived a model to predict the risk of a composite outcome (HF, death or arrhythmia) with a c-statistic of 0.85. Two studies applied an existing general HF model to patients with ACHD but did not report model performance. Twenty studies presented predictors of decompensated HF, and four examined patient characteristics associated with mortality (two reported predictors of both). A wide variation in population characteristics, outcome of interest and candidate risk factors was observed between studies. Although there were substantial inconsistencies regarding which patient characteristics were predictive of HF-related adverse outcomes, brain natriuretic peptide, New York Heart Association class and CHD lesion characteristics were shown to be important predictors. To date, evidence in the published literature is insufficient to accurately profile patients with ACHD. High-quality studies are required to develop a unique ACHD-HF prediction model and confirm the predictive roles of potential risk factors.