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The importance of high total body water/fat free mass ratio and serial changes in body composition for predicting hospital mortality in patients with severe pneumonia: a prospective cohort study.

Authors :
Tseng CC
Hung KY
Chang HC
Huang KT
Wang CC
Chen YM
Lin CY
Lin MC
Fang WF
Source :
BMC pulmonary medicine [BMC Pulm Med] 2024 Sep 27; Vol. 24 (1), pp. 470. Date of Electronic Publication: 2024 Sep 27.
Publication Year :
2024

Abstract

Purpose: This study aimed to investigate the impact of body composition variables on hospital mortality compared to other predictive factors among patients with severe pneumonia. Additionally, we aimed to monitor the dynamic changes in body composition variables over the course on days 1, 3, and 8 after intensive care unit (ICU) admission for each patient.<br />Methods: We conducted a prospective study, enrolling patients with severe pneumonia admitted to the medical intensive care unit at Kaohsiung Chang Gung Memorial Hospital from February 2020 to April 2022. We collected clinical data from all patients and assessed their body composition at 1, 3, and 8 days post-ICU admission. On day 1, we analyzed clinical and body composition variables to predict in-hospital mortality.<br />Results: Multivariate analysis identified the Modified Nutrition Risk in the Critically Ill (mNUTRIC) score and the ratio of total body water to fat-free mass (TBW/FFM) as independent factors associated with in-hospital mortality in severe pneumonia patients. Receiver operating characteristic analysis determined that the TBW/FFM ratio was the most reliable predictive parameter of in-hospital mortality, with a cutoff value of 0.74. General linear regression with repeated measures analysis showed that hospital non-survivors displayed notable fluctuations in body water, fat, and muscle variables over the course of days 1, 3, and 8 after ICU admission.<br />Conclusions: The mNUTRIC score and TBW/FFM ratio emerged as independent factors for predicting hospital mortality, with the TBW/FFM ratio demonstrating the highest reliability as a predictive parameter.<br /> (© 2024. The Author(s).)

Details

Language :
English
ISSN :
1471-2466
Volume :
24
Issue :
1
Database :
MEDLINE
Journal :
BMC pulmonary medicine
Publication Type :
Academic Journal
Accession number :
39333963
Full Text :
https://doi.org/10.1186/s12890-024-03302-4