Congenital heart defects (CHD) are the most prevalent birth defects in the United States and surgical outcomes vary considerably across the country. The outcomes of treatment for CHD differ for specific patient subgroups, with non-Hispanic Black and Hispanic populations experiencing higher rates of mortality and morbidity. A valid comparison of outcomes within racial/ethnic subgroups is difficult given large differences in case-mix and small subgroup sizes. We propose a causal inference framework for outcome assessment and leverage advances in transfer learning to incorporate data from both target and source populations to help estimate causal effects while accounting for different sources of risk factor and outcome differences across populations. Using the Society of Thoracic Surgeons' Congenital Heart Surgery Database (STS-CHSD), we focus on a national cohort of patients undergoing the Norwood operation from 2016-2022 to assess operative mortality and morbidity outcomes across U.S. geographic regions by race/ethnicity. We find racial and ethnic outcome differences after controlling for potential confounding factors. While geography does not have a causal effect on outcomes for non-Hispanic Caucasian patients, non-Hispanic Black patients experience wide variability in outcomes with estimated 30-day mortality ranging from 5.9% (standard error 2.2%) to 21.6% (4.4%) across U.S. regions.

翻译：先天性心脏病（CHD）是美国最常见的出生缺陷，其手术结局在全国范围内存在显著差异。特定患者亚群（如非西班牙裔黑人和西班牙裔人群）的CHD治疗结局呈现更高的死亡率和发病率。由于病例组合的巨大差异和亚组样本量较小，对种族/民族亚组进行有效结局比较较为困难。我们提出一种因果推断框架用于结局评估，并利用迁移学习领域的进展整合目标人群与源人群的数据，以帮助估计因果效应，同时考量不同人群中风险因素与结局差异的不同来源。利用胸外科医师学会先天性心脏病手术数据库（STS-CHSD），我们聚焦于2016-2022年间接受诺伍德手术的全国患者队列，评估按种族/民族分层的美国地理区域手术死亡率和发病率结局。在控制潜在混杂因素后，我们发现种族和民族间的结局差异。虽然地理因素对非西班牙裔白种人患者的结局无因果效应，但非西班牙裔黑人患者在不同区域的结局存在广泛变异，其估计的30天死亡率在美国各地区间从5.9%（标准误2.2%）到21.6%（4.4%）不等。