4.6 Article

Machine Learning to Predict Executive Function in Adolescents with Repaired d-Transposition of the Great Arteries, Tetralogy of Fallot, and Fontan Palliation

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JOURNAL OF PEDIATRICS
卷 246, 期 -, 页码 145-153

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MOSBY-ELSEVIER
DOI: 10.1016/j.jpeds.2022.03.021

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资金

  1. National Heart, Lung, and Blood Institute [R01 HL77681, P50 HL74734, R01 HL096825]
  2. Farb Family Fund [RR02172]
  3. National Center for Research Resources

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This study aimed to identify predictors of impaired executive function in adolescents who underwent surgical repair for critical congenital heart disease (CHD). It was found that family social class and factors such as low birth weight and a greater number of catheterizations predicted lower executive function scores. These findings highlight the importance of social class in mitigating the risks of executive dysfunction in CHD patients.
Objective To identify predictors of impaired executive function in adolescents after surgical repair of critical congenital heart disease (CHD). Study design We analyzed patient factors, medical and surgical history, and family social class from 3 single-center studies of adolescents with d-transposition of the great arteries (d-TGA), tetralogy of Fallot (TOF), and Fontan repair. Machine learning models were developed using recursive partitioning to predict an executive function composite score based on five subtests (population mean 10, SD 3) of the Delis-Kaplan Executive Function System. Results The sample included 386 patients (139 d-TGA, 91 TOF, 156 Fontan) of age 15.1 +/- 2.1 (mean +/- SD) years and an executive function composite score of 8.6 +/- 2.4. Family social class emerged as the most important predictive factor. The lowest (worst) mean executive function score (5.3) occurred in patients with low to medium social class (Hollingshead index < 56) with one or more neurologic events and a diagnosis of TOF. The highest (best) mean score (9.7) occurred in subjects with high social class (Hollingshead index >= 56) and shorter duration of deep hypothermic circulatory arrest. Other factors predicting lower executive function scores included low birth weight and a greater number of catheterizations. Conclusions In regression tree modeling, family social class was the strongest predictor of executive function in adolescents with critical CHD, even in the presence of medical risk factors. Additional predictors included CHD diagnosis, birth weight, neurologic events, and number of procedures. These data highlight the importance of social class in mitigating risks of executive dysfunction in CHD.

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