Predicting Parental Post-Traumatic Stress Symptoms Following their Child's Stay in a Pediatric Intensive Care Unit, Prior to Discharge

Authors

Mekela M. Whyte-Nesfield, Department of Pediatrics, Division of Pediatric Critical Care, Children's National Hospital, Washington, DC, USA.
Eduardo A. Trujillo Rivera, Department of Pediatrics, Division of Pediatric Critical Care, Children's National Hospital, Washington, DC, USA.
Daniel Kaplan, Department of Pediatrics, Division of Pediatric Critical Care, Rutgers Robert Wood Johnson Medical School, New Brunswick, NJ, USA.
Simon Li, Department of Pediatrics, Division of Pediatric Critical Care, Rutgers Robert Wood Johnson Medical School, New Brunswick, NJ, USA.
Pamela S. Hinds, Children's National Research Institute, Children's National Hospital, Washington, DC, USA.
Murray M. Pollack, Department of Pediatrics, Division of Pediatric Critical Care, Children's National Hospital, Washington, DC, USA.

Document Type

Journal Article

Publication Date

9-30-2024

Journal

Journal of intensive care medicine

DOI

10.1177/08850666241287442

Keywords

PTSD; acute post-traumatic stress disorder; acute stress disorder; critical care; critical illness; post-intensive care syndrome; post-traumatic stress disorder

Abstract

Develop an inpatient predictive model of parental post-traumatic stress (PTS) following their child's care in the Pediatric Intensive Care Unit (PICU). Prospective observational cohort. Two tertiary care children's hospitals with mixed medical/surgical/cardiac PICUs. Parents of patients admitted to the PICU. None. Preadmission and admission data from 169 parents of 129 children who completed follow up screening for parental post-traumatic stress symptoms at 3-9 months post PICU discharge were utilized to develop a predictive model estimating the risk of parental PTS 3-9 months after hospital discharge. The parent cohort was predominantly female (63%), partnered (75%), and working (70%). Child median age was 3 years (IQR 0.36-9.04), and more than half had chronic illnesses (56%) or previous ICU admissions (64%). Thirty-five percent (60/169) of parents met criteria for PTS (>9 on the Post-traumatic Stress Disorder Symptom Scale-Interview). The machine learning model (XGBoost) predicted subjects with parental PTS with 76.7% accuracy, had a sensitivity of 0.83 (95% CI 0.586, 0.964), a specificity of 0.72 (95% CI 0.506, 0.879), a precision of 0.682 (95% CI 0.451, 0.861) and number needed to evaluate of 1.47 (95% CI 1.16, 1.98). The area under the receiver operating curve was 0.78 (95% CI 0.64, 0.92). The most important predictive pre-admission and admission variables were determined using the Local Interpretable Model-Agnostic Explanation, which identified seven variables used 100% of the time. Composite variables of parental history of mental illness and traumatic experiences were most important. A machine learning model using parent risk factors predicted subsequent PTS at 3-9 months following their child's PICU discharge with an accuracy of 76.7% and number needed to evaluate of 1.47. This performance is sufficient to identify parents who are at risk during hospitalization, making inpatient and acute post admission mitigation initiatives possible.

APA Citation

Whyte-Nesfield, Mekela M.; Trujillo Rivera, Eduardo A.; Kaplan, Daniel; Li, Simon; Hinds, Pamela S.; and Pollack, Murray M., "Predicting Parental Post-Traumatic Stress Symptoms Following their Child's Stay in a Pediatric Intensive Care Unit, Prior to Discharge" (2024). GW Authored Works. Paper 5571.
https://hsrc.himmelfarb.gwu.edu/gwhpubs/5571

Department

Pediatrics