Albumin-corrected anion gap as a predictor of 28-day mortality in acute respiratory distress syndrome: A machine learning-based retrospective study

Qiudie Liu, Mengqi Zhang and Daoxin Wang

PLOS ONE, 2025, vol. 20, issue 11, 1-17

Abstract: Background: Acute Respiratory Distress Syndrome (ARDS) remains a critical condition associated with high mortality rates, prolonged hospitalization, and reduced quality of life despite advances in critical care. The albumin-corrected anion gap (ACAG), an emerging biomarker reflecting acid-base disturbances, has been linked to poor outcomes in various critical illnesses. However, its prognostic value for mortality in ARDS patients remains unexplored. Methods: This retrospective study analyzed data from ARDS patients admitted to intensive care units (ICUs) in the MIMIC-IV database. Patients were stratified into quartiles (Q1–Q4) based on ACAG levels. The association between ACAG and 28-day all-cause mortality was comprehensively evaluated using restricted cubic splines, Kaplan–Meier survival analysis, and Cox proportional hazards regression. We employed the Boruta algorithm and LASSO (Least Absolute Shrinkage and Selection Operator) regression to identify key predictive factors. Six machine learning algorithms were used to develop predictive models, with performance assessed by the area under the ROC curve (AUC). Results: Higher ACAG levels were significantly associated with increased 28-day mortality risk in ARDS patients (P

Date: 2025
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0336662 (text/html)
https://journals.plos.org/plosone/article/file?id= ... 36662&type=printable (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0336662

DOI: 10.1371/journal.pone.0336662

Access Statistics for this article

More articles in PLOS ONE from Public Library of Science
Bibliographic data for series maintained by plosone ().