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Published on: January 16, 2019
Predictors of Post-Intensive Care Syndrome in ICU Survivors After Discharge: An Observational Study
Francesco Gravante1, Paolo Iovino2, Francesca Trotta1
1Department of Biomedicine and Prevention, University of Rome Tor Vergata, 00133 Rome, Italy.
Abstract:
Background/Objectives: Post-intensive care syndrome (PICS) includes new or worsening physical, cognitive, and mental impairments following intensive care unit (ICU) admission. However, its predictors remain poorly defined. This study aimed to identify the predictors of PICS among ICU survivors 30 days after discharge. Methods: This prospective, monocentric, observational study was conducted from September 2023 to March 2024. Adult ICU survivors were assessed using the Healthy Ageing Brain Care Monitor to evaluate their physical, cognitive, and mental dimensions. The predictors included age, sex, coma, sedation, clinical severity (APACHE score), risk of ICU delirium (PREDELIRIC score), infection, hospital length of stay, and mechanical ventilation duration. Multivariate linear regression was used to identify independent predictors (p < 0.05). Results: A total of 90 ICU survivors were enrolled in the study. Higher clinical severity (B = 0.17, p = 0.001) and high delirium risk (PREDELIRIC score: B = 3.11, p = 0.007) were associated with worse cognitive PICS. Functional PICS was predicted by clinical severity (B = 0.36, p = 0.002) and moderate delirium risk (PREDELIRIC score: B = 7.12, p = 0.009). Behavioural PICS was inversely associated with coma (B = -6.74, p = 0.023) but positively associated with sedation (B = 7.64, p = 0.013) and moderate delirium risk (B = 2.24, p = 0.031). Conclusions: Clinical severity, PREDELIRIC score, sedation, and coma were significant predictors of PICS subdomains. Multidisciplinary teams may be more effective by prioritising targeted screening to identify ICU survivors at elevated risk for PICS using validated predictors such as clinical severity and the PREDELIRIC score, and delivering focused interventions to those most likely to benefit.
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