Evidence map›Paper›PMID 42020706›Full record

Observational studyEuropean journal of clinical nutrition2026

Comparative study on the predictive value of PNI and GNRI for all-cause mortality rates of elderly patients in cardiac care unit and cardiovascular intensive care unit.

Wanlu Zhou, Jingjia Yu, Min Zheng, Ruizheng Shi

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Observational study in European journal of clinical nutrition, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

Authors and funding

4 authors.

Wanlu ZhouDepartment of Cardiovascular Medicine, Xiangya Hospital, Central South University, Changsha, China.ORCID http://orcid.org/0009-0000-5233-5249
Jingjia YuDepartment of Cardiovascular Medicine, The third Xiangya Hospital, Central South University, Changsha, China.
Min ZhengDepartment of Cardiovascular Medicine, Xiangya Hospital, Central South University, Changsha, China.
Ruizheng ShiDepartment of Cardiovascular Medicine, Xiangya Hospital, Central South University, Changsha, China. xyshiruizheng@csu.edu.cn.ORCID http://orcid.org/0000-0002-1537-4430

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe prognostic nutritional index (PNI) and geriatric nutritional risk index (GNRI) are reliable alternative biomarkers of nutrition. However, the relationship between nutritional indicators and mortality of elderly patients in the cardiac care unit (CCU) and cardiovascular intensive care unit (CVICU) remains unknown.

methodsThis retrospective observational study analyzed data from 811 elderly patients in the Medical Information Mart for Intensive Care IV (MIMIC-IV) database. The primary outcome was 360-day all-cause mortality. PNI and GNRI were evaluated using restricted cubic spline (RCS), Cox proportional hazards model, Kaplan-Meier curve, and subgroup analyses. Predictive models were developed using machine learning (ML) algorithms, and the predictive values of feature variables were assessed using the SHapley Additive exPlanation (SHAP) algorithm.

resultsRCS and Cox models showed that higher nutritional indices were associated with lower mortality risk. Kaplan-Meier curves further confirmed higher mortality in patients with lower indices. Four ML algorithms were constructed. Among these, the logistic regression (LR) algorithm demonstrated superior performance compared to the others, with PNI and GNRI identified as the key predictors. Subgroup analyses showed consistent PNI and GNRI effects across congestive heart failure (CHF), myocardial infarction (MI), acute kidney injury (AKI), and type 2 diabetes mellitus (T2DM), with no significant interactions.

conclusionNutritional indices were significantly associated with the mortality risk of elderly patients in CCU and CVICU.

Indexed as

Cardiovascular DiseasesCoronary Care UnitsGeriatric AssessmentIntensive Care UnitsNutritional StatusNutrition AssessmentAgedAged, 80 and overAlgorithmsFemaleHumansKaplan-Meier EstimateMalePredictive Value of TestsPrognosisProportional Hazards Models

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.