Estimating the optimal timing of surgery by imputing potential outcomes

Area of Science:

• Pediatric Cardiology
• Congenital Heart Disease
• Biostatistics

Background:

• Hypoplastic left heart syndrome (HLHS) is a severe congenital anomaly requiring prompt intervention.
• Standard treatment involves a two-stage surgical approach: Norwood procedure (Stage 1) followed by Stage 2 Palliation (S2P).
• The optimal timing for S2P remains an area of clinical uncertainty.

Purpose of the Study:

• To estimate the causal effect of S2P timing on post-operative survival in HLHS patients.
• To utilize statistical imputation methods within the Rubin Causal Model framework.
• To compare the performance of lognormal and restricted cubic spline models for outcome imputation.

Main Methods:

• Application of the Rubin Causal Model framework to impute potential survival outcomes.
• Utilizing statistical models, specifically lognormal and restricted cubic spline models.
• Conducting Monte Carlo studies to evaluate model performance.

Main Results:

• Both statistical models provided estimates for the causal effect of S2P timing.
• The models yielded comparable, though not identical, imputed survival values.
• Analysis of the Single Ventricle Reconstruction Trial (SVRT) data indicated optimal S2P timing at 6 months post-Norwood procedure.

Conclusions:

• The study supports a 6-month interval between the Norwood procedure and S2P for improved survival in HLHS.
• Statistical modeling provides a robust method for analyzing treatment timing in complex pediatric cardiac surgery.
• Further investigation into optimal surgical timing can refine treatment protocols for HLHS.