Predicting Unplanned Readmissions to the Intensive Care Unit in the Trauma Population.

Autor:	O'Quinn PC; Quillen College of Medicine, East Tennessee State University, Johnson City, TN, USA., Gee KN; Department of Surgery, University of Tennessee Graduate School of Medicine, Knoxville, TN, USA., King SA; Department of Surgery, University of Tennessee Graduate School of Medicine, Knoxville, TN, USA., Yune JJ; Department of Trauma and Acute Care Surgery, PeaceHealth Sacred Heart Medical Center at RiverBend, Springfield, OR, USA., Jenkins JD; Department of Surgery, University of Tennessee Graduate School of Medicine, Knoxville, TN, USA., Whitaker FJ; Quillen College of Medicine, East Tennessee State University, Johnson City, TN, USA., Suresh S; Quillen College of Medicine, East Tennessee State University, Johnson City, TN, USA., Bollig RW; Department of Surgery, University of Tennessee Graduate School of Medicine, Knoxville, TN, USA., Many HR; Department of Surgery, University of Tennessee Graduate School of Medicine, Knoxville, TN, USA., Smith LM; Department of Surgery, University of Tennessee Graduate School of Medicine, Knoxville, TN, USA.
Jazyk:	angličtina
Zdroj:	The American surgeon [Am Surg] 2024 Sep; Vol. 90 (9), pp. 2285-2293. Date of Electronic Publication: 2024 May 24.
DOI:	10.1177/00031348241256067
Abstrakt:	Background: Unplanned readmission to intensive care units (UR-ICU) in trauma is associated with increased hospital length of stay and significant morbidity and mortality. We identify independent predictors of UR-ICU and construct a nomogram to estimate readmission probability. Materials and Methods: We performed an IRB-approved retrospective case-control study at a Level I trauma center between January 2019 and December 2021. Patients with UR-ICU (n = 175) were matched with patients who were not readmitted (NR-ICU) (n = 175). Univariate and multivariable binary linear regressionanalyses were performed (SPSS Version 28, IBM Corp), and a nomogram was created (Stata 18.0, StataCorp LLC). Results: Demographics, comorbidities, and injury- and hospital course-related factors were examined as potential prognostic indicators of UR-ICU. The mortality rate of UR-ICU was 22.29% vs 6.29% for NR-ICU ( P < .001). Binary linear regression identified seven independent predictors that contributed to UR-ICU: shock ( P < .001) or intracranial surgery ( P = .015) during ICU admission, low hematocrit ( P = .001) or sedation administration in the 24 hours before ICU discharge ( P < .001), active infection treatment ( P = .192) or leukocytosis on ICU discharge ( P = .01), and chronic obstructive pulmonary disease (COPD) ( P = .002). A nomogram was generated to estimate the probability of UR-ICU and guide decisions on ICU discharge appropriateness. Discussion: In trauma, UR-ICU is often accompanied by poor outcomes and death. Shock, intracranial surgery, anemia, sedative administration, ongoing infection treatment, leukocytosis, and COPD are significant risk factors for UR-ICU. A predictive nomogram may help better assess readiness for ICU discharge. Competing Interests: Declaration of Conflicting InterestsThe author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
Databáze:	MEDLINE
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