Prognostic value of the lactate dehydrogenase-to-albumin ratio for predicting mortality in critically ill pediatric patients: a retrospective cohort study

Elevated LAR independently predicts an increased mortality risk in critically ill pediatric patients. As an easily calculated ratio derived from routine laboratory parameters, LAR represents a valuable prognostic tool for risk stratification in the pediatric intensive care setting.

Authors

Institutions

Publication Details

Journal
Frontiers in Pediatrics
Published
2025-11-05
DOI
https://doi.org/10.3389/fped.2025.1692874
Primary Topic
Sepsis Diagnosis and Treatment
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 the lactate dehydrogenase-to-albumin ratio for predicting mortality in critically ill pediatric patients: a retrospective cohort study

Ping Yang, Yu Gou, Ming Liu
Frontiers in Pediatrics
Sepsis Diagnosis and Treatment
article

Prognostic value of the lactate dehydrogenase-to-albumin ratio for predicting mortality in critically ill pediatric patients: a retrospective cohort study

Ping Yang, Yu Gou, Ming Liu
article en

Abstract

Elevated LAR independently predicts an increased mortality risk in critically ill pediatric patients. As an easily calculated ratio derived from routine laboratory parameters, LAR represents a valuable prognostic tool for risk stratification in the pediatric intensive care setting.

Frontiers in PediatricsVol. 13
Suizhou Central Hospital (CN)
Zhejiang University
Openalex Percentile: Top 57%
Sepsis Diagnosis and Treatment
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.