Development and validation of a risk prediction model for unplanned 7-day readmission to PICU

Abstract

Abstract We studied risk factors and predicted the probability of a child being readmitted to the pediatric intensive care unit (PICU) within 7 days of being discharged home. From November 2011 and September 2022, a retrospective case-control study was conducted to develop a risk prediction model in the PICU. The case group included children aged 1 month to 18 years discharged home who required unplanned 7-day readmission to the PICU. Non-readmitted children were chosen as controls. Characteristics were collected on the first admission and divided into a developing set and a validation set. In the developing set, a nomogram was established to predict the risk of readmission, and its performance was assessed by receiver operating characteristic curves, calibration curves, and decision curve analysis (DCA). Internal validation was eventually performed on the model. 5266 children were involved in the study, with 173 eligible children in the case group and 184 in the control group. The model included five risk characteristics: complex chronic conditions, higher Pediatric Logistic Organ Dysfunction 2 scores on admission and discharge, sedation, and the Functional Status Scale score. In the two datasets, the area under the curves was 0.851 and 0.811, respectively. The calibration curve and DCA both performed well. And the model showed great reproducibility. The model demonstrated good capability for assessing the risk of 7-day readmission to the PICU, which could support early detection and intervention.

Keywords

• Pediatric intensive care unit
• Pediatrics
• Prognosis
• Readmission
• Predictive model