The Quest for Precision Medicine: Unmeasured Patient Factors and Mortality After Congenital Heart Surgery

Abstract

Emerging data across many fields suggest that unique patient characteristics can impact disease manifestation and response to therapy, supporting "precision medicine" approaches and more individualized and targeted therapeutic strategies. In children undergoing congenital heart surgery, current risk models primarily focus on the population level, and their utility in understanding precise characteristics that place individual patients at risk for poor outcome remains unclear. We analyzed index surgeries in the Pediatric Cardiac Critical Care Consortium (PC4) registry (August 2014 to May 2016) and utilized a previously constructed model containing patient factors typically included in in-hospital mortality risk models (age, weight, prematurity, chromosomal anomalies/syndromes, preoperative factors, The Society of Thoracic Surgeons-European Association for Cardio-Thoracic Surgery score). Partitioned variances based on a hierarchical generalized linear model were used to estimate the proportion of variation in mortality explained by these factors. A total of 8406 operations (22 hospitals) were included. We found that only 30% of the total between-patient variation in mortality in our cohort was explained by the patient factors included in our model. Age, The Society of Thoracic Surgeons-European Association for Cardio-Thoracic Surgery score, and preoperative mechanical ventilation explained the greatest proportion of variation. Of the variation that remained unexplained, 95% was attributable to unmeasured patient factors. In stratified analyses, these results were consistent across patient subgroups. Patient factors typically included in congenital heart surgery risk models explain only a small portion of total variation in mortality. A better understanding of other underrecognized factors is critical in further defining risk profiles and in developing more individualized and tailored therapeutic strategies.