Evidence map›Paper›PMID 40777171›Full record

ArticleFrontiers in nutrition2025

The relationship between elderly nutritional risk index and short-term all-cause mortality in critically ill patients with cerebral injury: a retrospective cohort study from two cohorts.

Zirong Gao, Xun Mo, Yi Ge, Yanhui Lu, Shanshan Yu

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Article in Frontiers in nutrition, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

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7citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

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7 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Zirong Gao *Department of Neuro Intensive Care Unit, The Affiliated Jinyang Hospital of Guizhou Medical University, Guiyang, China.
Xun Mo *Department of Neuro Intensive Care Unit, The Affiliated Jinyang Hospital of Guizhou Medical University, Guiyang, China.
Yi Ge *Department of Neuro Intensive Care Unit, The Affiliated Jinyang Hospital of Guizhou Medical University, Guiyang, China.
Yanhui LuDepartment of Neuro Intensive Care Unit, The Affiliated Jinyang Hospital of Guizhou Medical University, Guiyang, China.
Shanshan YuDepartment of Neuro Intensive Care Unit, The Affiliated Jinyang Hospital of Guizhou Medical University, Guiyang, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The Geriatric Nutritional Risk Index (GNRI) is a simple and objective tool for assessing the risk of malnutrition, with potential practicality in critically ill patients with cerebral injury (CIPCI). However, the current evidence is still limited. Method: Patients diagnosed with cerebral injury were retrospectively retrieved from the Medical Information Marketplace for Intensive Care (MIMIC-IV) and the Affiliated Jinyang Hospital of Guizhou Medical University. Various statistical methods, including restricted cubic spline regression (RCS) regression, multivariate logistic regression, subgroup analyses, and KM survival curves, were used to examine the association between the GNRI index and short-term adverse outcomes in CIPCI. Finally, we used LASSO-COX regression and multifactorial COX regression to develop risk prediction models and assessed the validity of the risk models using subject work characteristics (ROC) curves, area under the ROC (AUC). Result: The final 1,244 CIPCIs were included in the analysis, of which the 28-day ICU/in-hospital mortality rates were 23.5 and 27.18%, respectively. In the fully adjusted model, continuous GNRI and GNRI category were significantly associated with 28-day ICU/in-hospital mortality, with HRs of, respectively, continuous GNRI: 0.97 (0.96-0.99)/0.97 (0.96-0.99) and [moderate nutritional risk vs. no nutritional risk: 1.66 (1.01-2.74) and 2.03 (1.26-3.28), higher nutritional risk vs. no nutritional risk: 1.79 (1.08-2.97)/2.11 (1.30-3.42)]. Meanwhile, the RCS showed an inverse linear association between continuous GNRI and both 28-day ICU/hospitalization mortality, and this association remained consistent across most subgroups. In addition, the results of the ROC curves showed that the risk model constructed in this study could identify highly-risk CIPCI more effectively than the traditional critical care score. Finally, all results have been further confirmed in the external queue. Conclusion: This study identifies that GNRI is negatively associated with short-term mortality in critically ill patients with cerebral injury and provides a simple and effective tool for risk stratification, allowing clinicians to identify at-risk individuals and provide timely intervention.

Indexed as

cerebral injurycritically illGNRIMIMICmortality

Identifiers

PMID40777171
PMCPMC12328167

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