Screening for Delirium during Pediatric Inpatient Rehabilitation

Abstract

<h3>Research Objectives</h3> Delirium, an acute and fluctuating change in awareness and cognition, is a frequent and serious complication of severe pediatric illness yet is difficult to assess after acquired brain injury (ABI). Our primary objective was to implement delirium screening using the Cornell Assessment of Pediatric Delirium (CAPD) and describe the rate of positive delirium screens. Our secondary objective was to explore longitudinal trends in CAPD scores in children with ABI, to discriminate between static encephalopathy and gradual improvement. <h3>Design</h3> Prospective cohort study. <h3>Setting</h3> Pediatric inpatient rehabilitation unit. <h3>Participants</h3> Consecutive children with ABI admitted over 3 years. <h3>Interventions</h3> Children were screened for delirium twice daily with the CAPD throughout their rehabilitation hospitalization. A positive screen was not considered diagnostic for delirium, as longitudinal assessment was required to establish fluctuation and acuity versus static encephalopathy due to ABI. <h3>Main Outcome Measures</h3> Percentage of positive delirium screens and individual patient-level CAPD patterns. <h3>Results</h3> There were 14,280 CAPD administrations across 143 children with ABI (Mean Age = 10.86, SD = 4.72, Range = 1.3 - 19.9, Female = 64). The prevalence of positive screens was 27% (n = 3,861) and 60.8% (n = 87) of the children had at least one positive screen. Two raters independently identified four primary patterns for all children in this cohort: i. no delirium (n = 71, 49.7%), ii. improving (n = 45, 31.5%), iii. static encephalopathy (n = 18, 12.6%) and iv. episodic delirium (n = 9, 6.3%). <h3>Conclusions</h3> Delirium occurs frequently in children with ABI during inpatient rehabilitation. Routine delirium screening facilitates early detection and intervention that may maximize functional outcomes. Longitudinal screening allows for differentiation of children with varying patterns of recovery. Future research can use group-based trajectory modeling to identify distinct patterns that may predict outcomes. <h3>Author(s) Disclosures</h3> The authors have no conflicts of interest to disclose.