Association between BMI and outcomes in critically ill patients: an analysis of the MIMIC-III database

Obesity is a significant public health challenge, yet the link between BMI and mortality in critical illness remains unclear. This study analyzed 19,311 patients from the MIMIC-III database, categorized into underweight, normal weight, overweight, and obese groups. Using Cox models and restricted cubic splines, we explored the complex association between BMI and mortality. Finally, multiple sensitivity analyses were performed to test the robustness of the results. The proportion of underweight patients (2.3%) was the lowest, while overweight (34.8%) and obese (34.5%) patients constituted a large proportion. Being underweight portended a greater risk, while being overweight or obese was associated with a lower risk of mortality, which is consistent with the sensitivity analysis. Moreover, we observed a typical L-shaped association between BMI and the risk of mortality with and without adjustment, with the lowest mortality occurring at approximately 32 kg/m<sup>2</sup>. The overall pattern of the nonlinear association between BMI and mortality was similar for most subgroup analyses. Underweight was associated with a greater risk of mortality, while obesity and overweight were both associated with a lower risk of mortality in critically ill patients. BMI had a typical L-shaped association with the risk of mortality.

Authors

Institutions

Publication Details

Journal
Scientific Reports
Published
2024-12-27
DOI
https://doi.org/10.1038/s41598-024-82424-5
Citations
6
Primary Topic
Nutrition and Health in Aging
Type
article
Field-Weighted Citation Impact
1.96
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Association between BMI and outcomes in critically ill patients: an analysis of the MIMIC-III database

Wenbo Yu, Lizhu Sun, Weiwei Jiang, Tao Fan et al.
6 citations
Scientific Reports
Nutrition and Health in Aging
1.96
article

Association between BMI and outcomes in critically ill patients: an analysis of the MIMIC-III database

Wenbo Yu, Lizhu Sun, Weiwei Jiang, Tao Fan, Yan Zhu, Jihong Yuan, Wenfang Li, Shaoshuai Wu, Hai Xiao
article en
6 citations

Abstract

Obesity is a significant public health challenge, yet the link between BMI and mortality in critical illness remains unclear. This study analyzed 19,311 patients from the MIMIC-III database, categorized into underweight, normal weight, overweight, and obese groups. Using Cox models and restricted cubic splines, we explored the complex association between BMI and mortality. Finally, multiple sensitivity analyses were performed to test the robustness of the results. The proportion of underweight patients (2.3%) was the lowest, while overweight (34.8%) and obese (34.5%) patients constituted a large proportion. Being underweight portended a greater risk, while being overweight or obese was associated with a lower risk of mortality, which is consistent with the sensitivity analysis. Moreover, we observed a typical L-shaped association between BMI and the risk of mortality with and without adjustment, with the lowest mortality occurring at approximately 32 kg/m<sup>2</sup>. The overall pattern of the nonlinear association between BMI and mortality was similar for most subgroup analyses. Underweight was associated with a greater risk of mortality, while obesity and overweight were both associated with a lower risk of mortality in critically ill patients. BMI had a typical L-shaped association with the risk of mortality.

Scientific ReportsVol. 14(1)
Fudan University (CN), Shanghai University of Traditional Chinese Medicine (CN), Shanghai Changzheng Hospital (CN), Minhang District Central Hospital (CN), Seventh People's Hospital of Shanghai (CN), Obstetrics and Gynecology Hospital of Fudan University (CN)
Openalex Percentile: Top 13%
Nutrition and Health in Aging
1.96
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.