Gaynor, J. William

Individuals with congenital heart disease are living well into adulthood, resulting in a growing population at risk for neurocognitive and psychosocial challenges. Numerous studies have described these risks in childhood, but significant gaps remain in our understanding of how those challenges evolve across stages of adulthood and how to optimally integrate neurocognitive and psychosocial care for adults with congenital heart disease. A multidisciplinary group of experts and patient partners assembled in April 2024 in Atlanta, GA, forming 3 working groups: (1) Genetics and Brain Health, (2) Characterizing Neuropsychological and Psychological Outcomes, and (3) Neuropsychological and Psychosocial Interventions. Current knowledge was reviewed, knowledge gaps were identified, and recommendations to address these gaps were formulated. Five critical questions regarding the characterization of neuropsychological and psychological outcomes of adults with congenital heart disease were prioritized for discussion: which neurocognitive and psychosocial domains should be prioritized in research and clinical care, what are the trajectories of neurocognitive and psychosocial functioning over the lifespan, how should neurocognitive and psychosocial screening be deployed, what should neurocognitive and psychosocial assessments include, and how do we make comprehensive neurocognitive and psychosocial care a reality. Although many gaps in knowledge were identified, particularly around characterizing neurocognitive trajectories throughout adulthood, there is substantial evidence of increased risk for poor psychosocial outcomes among adults with with congenital heart disease. Clinical and research advances must progress in tandem to address these risks. Specific recommendations for advancing this field over the next decade are offered.

Background: Robust models exist to predict risk-adjusted mortality following congenital heart surgery. It is known that underlying diagnosis modifies predicted risk of operations, and institution-level outcomes vary based on their unique case mix. We therefore evaluated risk-adjusted outcomes for a subset of diagnosis-procedure (D-P) combinations within the Society of Thoracic Surgeons' (STS) congenital heart surgery database (CHSD). Methods: A clinician panel identified the most frequently encountered D-P combinations in CHSD between 07/2017 and 06/2021. Candidate modeling techniques were compared in a random 80% development cohort. Model performance was assessed using internal and cross-validation calibration, discrimination plots and optimism adjusted C-statistics. The final selected model was evaluated in the 20% validation sample. Results: The chosen subset of D-P combinations represented 45,384 of 87,589 (52%) unique episodes of surgical care in CHSD during this time-period. The development cohort (36,350 episodes) had 1.8% mortality (667 deaths). All candidate models had excellent discrimination with C-statistics ranging from 0.862 to 0.876. The model with the best combination of discrimination, calibration, and clinical face validity was a modified version of the current STS mortality risk model. This version included all current risk model variables with the addition of indicator variables for D-P combinations. In the 20% validation sample (9,034 episodes), this model was well calibrated (Figure) and had excellent discrimination (C = 0.879). Conclusion: We describe a cohort of D-P combinations widely encountered in the STS CHSD. Further, we refined the existing STS CHSD risk model for application to these D-P dyads to derive empirical risk-adjusted benchmark outcomes. This approach will benefit quality improvement efforts at an institutional level and may have implications for publicly reporting congenital heart surgery outcomes.