Prediction Models and Scores in Adult Congenital Heart Disease

Abstract

Nowadays, most patients with congenital heart disease survive to adulthood due to advances in pediatric cardiac surgery but often present with various comorbidities and long-term complications, posing challenges in their management. The development and clinical use of risk scores for the prediction of morbidity and/or mortality in adults with congenital heart disease (ACHD) is fundamental in achieving optimal management for these patients, including appropriate follow-up frequency, treatment escalation, and timely referral for invasive procedures or heart transplantation. In comparison with other fields of cardiovascular medicine, there are relatively few studies that report prediction models developed in the ACHD population, given the small sample size, heterogeneity of the population, and relatively low event rate. Some studies report risk scores originally developed in pediatric congenital or non-congenital population, externally validated in ACHD with variable success. Available risk scores are designed to predict heart failure or arrhythmic events, all-cause mortality, post-intervention outcomes, infective endocarditis, or atherosclerosis-related cardiovascular disease in ACHD. A substantial number of these scores are derived from retrospective studies and are not internally or externally validated. Adequately validated risk scores can be invaluable in clinical practice and an important step towards personalized medicine. Multicenter collaboration, adequate study design, and the potential use of artificial intelligence are important elements in the effort to develop reliable risk scores for the ACHD population.