C-Reactive Protein–Adjusted Prognostic Nutritional Index for Mortality Prediction in Older Adults in Intensive Care: Comparative ROC, Calibration, and Decision-Curve Analyses

Background: In elderly intensive care patients, malnutrition and inflammation together shape the risk of mortality. Traditional indices (PNI, GNRI) are widely used but show variable predictive value. In this study, our primary objective is to evaluate whether iPNI = PNI/(1+ln[CRP+1]), an index adjusted for inflammation, improved the discrimination and clinical utility of early mortality compared to PNI and GNRI. Secondary factors are the length of stay in the intensive care unit (ICU) and the use of critical organ support therapies.Methods: A single-center retrospective cohort (2018-2024; n=673) of adults aged ≥65 years admitted to the ICU. The primary outcome was defined as ICU mortality. The secondary endpoint was the need for ICU admission and mechanical ventilation (MV), vasopressor (VP), or renal replacement therapy (RRT). We performed DeLong tests, bootstrap internal validation, calibration (intercept, slope, Brier), decision curve analysis (10–40% threshold values), age/sex-adjusted logistic models, Spearman correlations for LOS, and ROC with CRP stratified ROC for PNI and GNRI. Youden cutoff values were determined exploratory a priori.Results: iPNI demonstrated the highest discrimination (AUC 0.961, 95% CI 0.940-0.982), outperforming PNI (0.901, 0.876-0.927) and GNRI (0.681, 0.639-0.723) (both p

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Publication Details

Journal
Acibadem Universitesi Saglik Bilimleri Dergisi
Published
2026-03-03
DOI
https://doi.org/10.31067/acusaglik.1833054
Primary Topic
Nutrition and Health in Aging
Type
article
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article

C-Reactive Protein–Adjusted Prognostic Nutritional Index for Mortality Prediction in Older Adults in Intensive Care: Comparative ROC, Calibration, and Decision-Curve Analyses

Mustafa Timurkaan, Esra Suay Timurkaan
Acibadem Universitesi Saglik Bilimleri Dergisi
Nutrition and Health in Aging
article

C-Reactive Protein–Adjusted Prognostic Nutritional Index for Mortality Prediction in Older Adults in Intensive Care: Comparative ROC, Calibration, and Decision-Curve Analyses

Mustafa Timurkaan, Esra Suay Timurkaan
article en

Abstract

Background: In elderly intensive care patients, malnutrition and inflammation together shape the risk of mortality. Traditional indices (PNI, GNRI) are widely used but show variable predictive value. In this study, our primary objective is to evaluate whether iPNI = PNI/(1+ln[CRP+1]), an index adjusted for inflammation, improved the discrimination and clinical utility of early mortality compared to PNI and GNRI. Secondary factors are the length of stay in the intensive care unit (ICU) and the use of critical organ support therapies.Methods: A single-center retrospective cohort (2018-2024; n=673) of adults aged ≥65 years admitted to the ICU. The primary outcome was defined as ICU mortality. The secondary endpoint was the need for ICU admission and mechanical ventilation (MV), vasopressor (VP), or renal replacement therapy (RRT). We performed DeLong tests, bootstrap internal validation, calibration (intercept, slope, Brier), decision curve analysis (10–40% threshold values), age/sex-adjusted logistic models, Spearman correlations for LOS, and ROC with CRP stratified ROC for PNI and GNRI. Youden cutoff values were determined exploratory a priori.Results: iPNI demonstrated the highest discrimination (AUC 0.961, 95% CI 0.940-0.982), outperforming PNI (0.901, 0.876-0.927) and GNRI (0.681, 0.639-0.723) (both p

Acibadem Universitesi Saglik Bilimleri Dergisi(January, February, March 2026)
Elazığ Eğitim ve Araştırma Hastanesi (TR), University of Health Sciences (SO)
Zero hunger
Openalex Percentile: Top 34%
Nutrition and Health in Aging
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C-Reactive Protein–Adjusted Prognostic Nutritional Index for Mortality Prediction in Older Adults in Intensive Care: Comparative ROC, Calibration, and Decision-Curve Analyses — Mustafa Timurkaan, Esra Suay Timurkaan · Acibadem Universitesi Saglik Bilimleri Dergisi (2026) | TGRS Research Map | TGRS