The association between nutrition risk status assessment and hospital mortality in Chinese older inpatients: a retrospective study

Our findings indicated that nutritional risk was an independent predictor of in-hospital mortality, with a cut-off value of 3.50 for the NRS2002 nutritional risk assessment being more appropriate than a cut-off value of 3.0.

Authors

Institutions

Publication Details

Journal
Journal of Health Population and Nutrition
Published
2024-12-27
DOI
https://doi.org/10.1186/s41043-024-00726-w
Primary Topic
Nutrition and Health in Aging
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

The association between nutrition risk status assessment and hospital mortality in Chinese older inpatients: a retrospective study

Jinhua Shen, Meng-Jun He, Fenghua Zeng, Xueqing Zhang et al.
Journal of Health Population and Nutrition
Nutrition and Health in Aging
article

The association between nutrition risk status assessment and hospital mortality in Chinese older inpatients: a retrospective study

Jinhua Shen, Meng-Jun He, Fenghua Zeng, Xueqing Zhang, Hui Mo, Jieqiong Liu
article en

Abstract

Our findings indicated that nutritional risk was an independent predictor of in-hospital mortality, with a cut-off value of 3.50 for the NRS2002 nutritional risk assessment being more appropriate than a cut-off value of 3.0.

Journal of Health Population and NutritionVol. 43(1)
Central South University (CN), The First People's Hospital of Changde (CN)
Zero hunger
Openalex Percentile: Top 66%
Nutrition and Health in Aging
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.