Prediction Models for Physical, Cognitive, and Mental Health Impairments After Critical Illness: A Systematic Review and Critical Appraisal

• Authors: Kimberley J. Haines, Sunshine Hospital; Elizabeth Hibbert, Sunshine Hospital; Joanne McPeake, Glasgow Royal Infirmary; Brian J. Anderson, University of Pennsylvania; Oscar Joseph Bienvenu, University of Pennsylvania; Adair Andrews, Society of Critical Care Medicine; Nathan E. Brummel, Ohio State University; Lauren E. Ferrante, Yale University; Ramona O. Hopkins, Brigham Young University; Catherine L. Hough, Oregon Health and Science University; James Jackson, Vanderbilt University; Mark E. Mikkelsen, University of Kentucky; Nina Leggett, Sunshine Hospital; Ashley Montgomery-Yates, University of Pennsylvania; Dale M. Needham, Johns Hopkins University; Carla M. Sevin, Vanderbilt University; Becky Skidmore, Independent Information Specialist; Mary Still, Emory University; Maarten van Smeden, Utrecht University; Gary S. Collins, University of Oxford; Michael O. Harhay, University of Pennsylvania
• Journal Title: CRITICAL CARE MEDICINE
• Volume: Volume 48, Number 12
• Publisher: LIPPINCOTT WILLIAMS & WILKINS | 2020-12-01, Pages 1871-1880
• Type of Work: Article | Final Publisher PDF
• Publisher DOI: http://doi.org/10.1097/CCM.0000000000004659
• Subjects: Health Sciences, Health Care Management; Psychology, Clinical; Psychology, Cognitive
• Keywords: Science & Technology; Life Sciences & Biomedicine; Critical Care Medicine; General & Internal Medicine; critical care; postintensive care syndrome; prediction; INDIVIDUAL PROGNOSIS; CARE; RISK; BIAS; APPLICABILITY; SURVIVORSHIP; EXPLANATION; PERFORMANCE; CALIBRATION; MORTALITY

Abstract

OBJECTIVES: Improved ability to predict impairments after critical illness could guide clinical decision-making, inform trial enrollment, and facilitate comprehensive patient recovery. A systematic review of the literature was conducted to investigate whether physical, cognitive, and mental health impairments could be predicted in adult survivors of critical illness. DATA SOURCES: A systematic search of PubMed and the Cochrane Library (Prospective Register of Systematic Reviews ID: CRD42018117255) was undertaken on December 8, 2018, and the final searches updated on January 20, 2019. STUDY SELECTION: Four independent reviewers assessed titles and abstracts against study eligibility criteria. Studies were eligible if a prediction model was developed, validated, or updated for impairments after critical illness in adult patients. Discrepancies were resolved by consensus or an independent adjudicator. DATA EXTRACTION: Data on study characteristics, timing of outcome measurement, candidate predictors, and analytic strategies used were extracted. Risk of bias was assessed using the Prediction model Risk Of Bias Assessment Tool. DATA SYNTHESIS: Of 8,549 screened studies, three studies met inclusion. All three studies focused on the development of a prediction model to predict (1) a mental health composite outcome at 3 months post discharge, (2) return-to-pre-ICU functioning and residence at 6 months post discharge, and (3) physical function 2 months post discharge. Only one model had been externally validated. All studies had a high risk of bias, primarily due to the sample size, and statistical methods used to develop and select the predictors for the prediction published model. CONCLUSIONS: We only found three studies that developed a prediction model of any post-ICU impairment. There are several opportunities for improvement for future prediction model development, including the use of standardized outcomes and time horizons, and improved study design and statistical methodology.