Prognostic value of nine inflammatory biomarkers for 30-day mortality in critically ill elderly patients with osteoporotic hip fracture

The study aimed to assess the predictive significance of various inflammatory biomarkers among critically ill elderly patients with osteoporotic hip fracture (OHF). The research identified critically ill elderly patients with OHF through the MIMIC-IV database. Nine systemic inflammatory indicators, formed by diverse combinations of neutrophils, lymphocytes, monocytes, and platelets, were evaluated for their associations with 30-day all-cause mortality after ICU admission. An examination of the receiver operating characteristic curve was conducted to determine the strongest predictive biomarker. In addition, the least absolute shrinkage and selection operator (LASSO) regression was applied to identify potential influencing factors. Furthermore, Cox proportional hazards regression and restricted cubic spline analyses were further applied to evaluate the association between the optimal biomarker and time-to-event outcomes. Seven inflammatory markers demonstrated significant predictive value for 30-day all-cause mortality, among which the platelet-to-lymphocyte ratio (PLR) exhibited the largest area under the curve (AUC = 0.783). Subsequently, individuals were categorized into quartiles according to PLR. Multivariate Cox proportional hazards models demonstrated a significant association between elevated PLR levels and 30-day all-cause mortality. After adjustment for variables selected by LASSO regression, elevated PLR remained an independent prognostic factor for mortality (adjusted hazard ratio, 1.43; 95% confidence interval, 1.24-1.65; P < 0.001). Additionally, restricted cubic spline analysis further demonstrated a consistently increasing risk of all-cause mortality with rising PLR levels. This study demonstrates that PLR is an independent predictor of 30-day all-cause mortality in critically ill elderly patients with osteoporotic hip fracture. Patients with a PLR ≥ 188.64 exhibit a significantly increased non-linear risk of 30-day all-cause mortality. Furthermore, patients with a PLR ≥ 302.11 can be classified as high-risk individuals. PLR represents an inexpensive and readily accessible tool for rapidly identifying high-risk patients and optimizing individualized treatment strategies in ICU clinical practice.

Authors

Institutions

Publication Details

Journal
Scientific Reports
Published
2026-02-02
DOI
https://doi.org/10.1038/s41598-026-37945-6
Primary Topic
Inflammatory Biomarkers in Disease Prognosis
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Prognostic value of nine inflammatory biomarkers for 30-day mortality in critically ill elderly patients with osteoporotic hip fracture

Xing Yong-jie, Chao-Lu Wang, Yuxin Chen, Zhun Du et al.
Scientific Reports
Inflammatory Biomarkers in Disease Prognosis
article

Prognostic value of nine inflammatory biomarkers for 30-day mortality in critically ill elderly patients with osteoporotic hip fracture

Xing Yong-jie, Chao-Lu Wang, Yuxin Chen, Zhun Du, Fei Liu, Zhen-Jiang Liu, Xiao-min Li
article en

Abstract

The study aimed to assess the predictive significance of various inflammatory biomarkers among critically ill elderly patients with osteoporotic hip fracture (OHF). The research identified critically ill elderly patients with OHF through the MIMIC-IV database. Nine systemic inflammatory indicators, formed by diverse combinations of neutrophils, lymphocytes, monocytes, and platelets, were evaluated for their associations with 30-day all-cause mortality after ICU admission. An examination of the receiver operating characteristic curve was conducted to determine the strongest predictive biomarker. In addition, the least absolute shrinkage and selection operator (LASSO) regression was applied to identify potential influencing factors. Furthermore, Cox proportional hazards regression and restricted cubic spline analyses were further applied to evaluate the association between the optimal biomarker and time-to-event outcomes. Seven inflammatory markers demonstrated significant predictive value for 30-day all-cause mortality, among which the platelet-to-lymphocyte ratio (PLR) exhibited the largest area under the curve (AUC = 0.783). Subsequently, individuals were categorized into quartiles according to PLR. Multivariate Cox proportional hazards models demonstrated a significant association between elevated PLR levels and 30-day all-cause mortality. After adjustment for variables selected by LASSO regression, elevated PLR remained an independent prognostic factor for mortality (adjusted hazard ratio, 1.43; 95% confidence interval, 1.24-1.65; P < 0.001). Additionally, restricted cubic spline analysis further demonstrated a consistently increasing risk of all-cause mortality with rising PLR levels. This study demonstrates that PLR is an independent predictor of 30-day all-cause mortality in critically ill elderly patients with osteoporotic hip fracture. Patients with a PLR ≥ 188.64 exhibit a significantly increased non-linear risk of 30-day all-cause mortality. Furthermore, patients with a PLR ≥ 302.11 can be classified as high-risk individuals. PLR represents an inexpensive and readily accessible tool for rapidly identifying high-risk patients and optimizing individualized treatment strategies in ICU clinical practice.

Scientific ReportsVol. 16(1)
Chinese Academy of Medical Sciences & Peking Union Medical College (CN), Wangjing Hospital of China Academy of Chinese Medical Sciences (CN), Cixian People's Hospital (CN), Anyang Hospital of Traditional Chinese Medicine (CN)
China Academy of Chinese Medical Sciences
Good health and well-being
Openalex Percentile: Top 70%
Inflammatory Biomarkers in Disease Prognosis
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.