Functional Compromise Cohort Study (FCCS): Sarcopenia is a Strong Predictor of Mortality in the Intensive Care Unit.

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Functional Compromise Cohort Study (FCCS): Sarcopenia is a Strong Predictor of Mortality in the Intensive Care Unit.

World J Surg. 2017 Dec 29;:

Authors: de Hoogt PA, Reisinger KW, Tegels JJW, Bosmans JWAM, Tijssen F, Stoot JHMB

Abstract
BACKGROUND: Functional compromise in elderly patients is considered to be a significant contributing factor in increased postoperative morbidity and mortality. It is described as a state of reduced physiologic reserves including, e.g., sarcopenia, cachexia, malnutrition and frailty with increased susceptibility to adverse health outcomes. Aim of this study was to investigate the association of sarcopenia with mortality in ICU patients.
METHODS: A retrospective analysis of a total of 687 patients admitted to the ICU from January 2013 until December 2014 was performed. Indirect measurements of functional compromise in these patients were conducted. Sarcopenia was assessed using the L3 muscle index by using Osirix© on computed tomography scans. Groningen Frailty Indicator (GFI) and Short Nutritional Assessment Questionnaire (SNAQ) scores were extracted from the digital patient filing system and were used to assess frailty and nutritional status. These factors were analyzed using logistic regression analysis as predictor for in-hospital mortality and 6-month mortality, which was the primary endpoint along with other secondary outcome measures.
RESULTS: Age was an independent predictor of in-hospital mortality, OR 1.043 (95% CI 1.030-1.057, p < 0.001). Analysis of sarcopenia showed OR 2.361 (95% CI 1.138-4.895, p = 0.021), for GFI OR 1.012 (95% CI 0.919-1.113, p = 0.811) and for SNAQ OR 1.262 (95% CI 1.091-1.460, p = 0.002).
CONCLUSION: This study shows a promising role for the sarcopenia score as a predictor of mortality on the ICU, based upon CT imaging at L3 level and SNAQ score. Further research is necessary to test this in larger cohorts and to develop a possible instrument to predict mortality in the intensive care unit.

PMID: 29285609 [PubMed - as supplied by publisher]

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