Evidence map›Paper›PMID 42889368›Full record

ArticleFrontiers in medicine2026

LDAR shows more consistent prognostic performance than other albumin-derived indices for 28-day ICU mortality in critically ill patients with urosepsis: evidence from a dual-cohort retrospective study.

Yi Mu, Hao Tang, Yan Zeng, Qian Wang, Tao Huang, Wei Li, Xiangbo Wu, Shengming Pi

Abstract read
In one paragraph

Article in Frontiers in medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Yi Mu *Department of Urology, Guiyang Public Health Clinical Center, Guiyang, China.
Hao Tang *Department of Urology, Guiyang Public Health Clinical Center, Guiyang, China.
Yan ZengDepartment of Urology, Guiyang Public Health Clinical Center, Guiyang, China.
Qian WangDepartment of Urology, Guiyang Public Health Clinical Center, Guiyang, China.
Tao HuangDepartment of Urology, Guiyang Public Health Clinical Center, Guiyang, China.
Wei LiDepartment of Urology, the Affiliated Hospital of Guizhou Medical University, Guiyang, China.
Xiangbo WuDepartment of Urology, Guiyang Public Health Clinical Center, Guiyang, China.
Shengming PiDepartment of Urology, Guiyang Public Health Clinical Center, Guiyang, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Urosepsis remains a leading cause of ICU mortality. Albumin-derived composite indices, which integrate nutritional, inflammatory, and metabolic parameters, hold prognostic promise; however, their comparative performance has not been directly assessed. Methods: We conducted a dual-cohort retrospective study using MIMIC-IV ( Results: In the derivation cohort, logLDAR, RAR, TAR, AGAR, and UAR were independently associated with 28-day ICU mortality in fully adjusted models (HRs = 1.292, 1.147, 1.136, 1.074, and 1.013, respectively; all Conclusion: Among the six albumin-derived indices, logLDAR demonstrated the most consistent and generalizable prognostic performance for 28-day ICU mortality in urosepsis, reflecting both tissue hypoxia and nutritional-inflammatory depletion, and remained robust under competing-risk adjustment. logLDAR may serve as a simple bedside biomarker for early risk stratification; however, prospective studies are warranted to determine whether interventions targeting its underlying pathways can improve outcomes.

Indexed as

albumin-derived indicescritical caredeep learningnutritional interventionrisk stratification

Identifiers

PMID42889368
PMCPMC13669183

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.