Predicting the risk of 7-day readmission in late preterm infants in California: A population-based cohort study.

Background and aims: The American Academy of Pediatrics describes late preterm infants, born at 34 to 36 completed weeks' gestation, as at-risk for rehospitalization and severe morbidity as compared to term infants. While there are prediction models that focus on specific morbidities, there is limited research on risk prediction for early readmission in late preterm infants. The aim of this study is to derive and validate a model to predict 7-day readmission. Methods: This is a population-based retrospective cohort study of liveborn infants in California between January 2007 to December 2011. Birth certificates, maintained by California Vital Statistics, were linked to a hospital discharge, emergency department, and ambulatory surgery records maintained by the California Office of Statewide Health Planning and Development. Random forest and logistic regression were used to identify maternal and infant variables of importance, test for association, and develop and validate a predictive model. The predictive model was evaluated for discrimination and calibration. Results: We restricted the sample to healthy late preterm infants ( Conclusions: Our 7-day readmission predictive model had moderate performance in differentiating at risk late preterm infants. Future studies might benefit from inclusion of more variables and focus on hospital practices that minimize risk.