Evidence map›Paper›PMID 41764439›Full record

ArticleBMC infectious diseases2026

Relationship between red cell distribution width to albumin ratio (RAR) and mortality in ICU patients with sepsis-associated ARDS: a retrospective study based on MIMIC-IV.

Hongzhou Wu, Min He, Yujia Gui, Jinyi Zhou, Liting Yue, Xiaoqin Zhang

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Article in BMC infectious diseases, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1 · What the graph read from it

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3 · Its place in the literature

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1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Hongzhou Wu *School of Clinical Medicine, North Sichuan Medical College, Nanchong, Sichuan, 637000, P.R. China.
Min He *School of Clinical Medicine, North Sichuan Medical College, Nanchong, Sichuan, 637000, P.R. China.
Yujia GuiCenter of Critical Care Medicine, Sichuan Provincial People's Hospital, Chengdu, Sichuan, 610072, P.R. China.
Jinyi ZhouCenter of Critical Care Medicine, Sichuan Provincial People's Hospital, Chengdu, Sichuan, 610072, P.R. China.
Liting YueCenter of Critical Care Medicine, Sichuan Provincial People's Hospital, Chengdu, Sichuan, 610072, P.R. China.
Xiaoqin ZhangCenter of Critical Care Medicine, Sichuan Provincial People's Hospital, Chengdu, Sichuan, 610072, P.R. China. zhangxiaoqin@med.uestc.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe red cell distribution width-to-albumin ratio (RAR) is an emerging prognostic indicator. However, its correlation with clinical endpoints in individuals with sepsis-associated acute respiratory distress syndrome (SA-ARDS) remains unclear. This study examined the relationship between RAR and all-cause mortality (ACM) in the intensive care unit (ICU) patients with SA-ARDS using the MIMIC-IV database. The goal was to identify high-risk individuals early on and improve prognostic assessment.

methodsAnalyses were conducted using data from the MIMIC-IV (V3.1) database. Adult patients who met Sepsis-3 criteria and the Berlin definition of ARDS were included. The outcomes were 30-, 90-, 180-, and 365-day mortality following ICU admission. Kaplan-Meier (KM) curves were utilized to estimate survival at corresponding timepoints. Cox regression was utilized to evaluate the association between RAR and mortality risk, including subgroup analyses. Restricted cubic spline (RCS) regression was adopted to explore the nonlinear correlation of RAR with ACM and to identify a possible cutoff value. Receiver operating characteristic (ROC) curves were applied for quantifying RAR’s predictive ability. Propensity score matching (PSM) was used to validate the findings.

resultsThe current study included 6,042 patients. The first, median, and third quartiles of RAR were 4.14, 5.07, and 6.32, respectively. KM analysis revealed a significantly higher mortality risk in patients with high RAR (P < 0.001). Multivariable Cox regression analysis indicated an independent positive correlation of RAR with ACM. RCS curves revealed a nonlinear relationship (inflection point at 5.04). The areas under the curve (AUCs) for RAR predicting 30-, 90-, 180-, and 365-day mortality were 0.634, 0.648, 0.652, and 0.649, respectively. Subgroup analyses supported the association of RAR. PSM confirmed the robustness of these results.

conclusionsRAR was found to be independently associated with an increased 30-, 90-, 180-, and 365-day ACM in ICU patients with SA-ARDS. RAR may have potential value as an early indicator for identifying high‑risk ICU populations. CLINICAL TRIAL NUMBER: Not applicable.

Indexed as

Respiratory Distress SyndromeSepsisSerum AlbuminAgedFemaleHumansIntensive Care UnitsKaplan-Meier EstimateMaleMiddle AgedPrognosisRetrospective StudiesROC CurveSerum AlbuminAcute respiratory failureAlbuminMIMIC-IVRed cell distribution widthSepsis

Identifiers

PMID41764439
PMCPMC13049849

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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.