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Prediction Models and Scores in Adult Congenital Heart Disease
Alexandra Arvanitaki1, Despoina Ntiloudi2, George Giannakoulas2
1Department of Cardiology III - Adult Congenital and Valvular Heart Disease, University Hospital Muenster, Albert-Schweitzer- Campus 1, 48149, Muenster, Germany.
Insights
Developing reliable risk scores for adults with congenital heart disease (ACHD) is crucial for personalized management and improved outcomes. Further research and validation are needed to address challenges in this complex patient population.
Area of Science:
- Cardiology
- Adult Congenital Heart Disease (ACHD) Research
- Clinical Prediction Models
Background:
- Advances in pediatric cardiac surgery enable more adults with congenital heart disease (ACHD) to survive into adulthood.
- ACHD patients often present with complex comorbidities and long-term complications, necessitating specialized management strategies.
- Optimal management of ACHD requires accurate prediction of morbidity and mortality to guide follow-up, treatment escalation, and timely interventions.
Purpose of the Study:
- To highlight the critical need for validated risk scores in the management of adults with congenital heart disease (ACHD).
- To discuss the challenges and limitations of existing prediction models in the ACHD population.
- To emphasize the importance of developing reliable risk scores for personalized medicine in ACHD.
Main Methods:
- Review of existing studies on risk prediction models in adults with congenital heart disease (ACHD).
- Analysis of challenges including small sample sizes, population heterogeneity, and low event rates.
- Discussion of the limitations of retrospective studies and the need for validation.
Main Results:
- Few prediction models are specifically developed and validated for the ACHD population.
- Existing risk scores, often adapted from other populations, show variable success in ACHD.
- Many available scores lack robust internal or external validation.
Conclusions:
- Validated risk scores are essential for optimizing ACHD patient care, including personalized follow-up and treatment decisions.
- Multicenter collaboration, robust study design, and potentially artificial intelligence are key to developing reliable ACHD risk scores.
- Improved risk stratification is a significant step towards achieving personalized medicine for adults with 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.
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