Evidence map›Paper›PMID 41799713›Full record

ArticleJournal of medical biochemistry2026

Prognostic utility of the lactate-to-albumin ratio for predicting 28-day all-cause mortality in critically ill cases with acute sepsis: A retrospective study on the basis of MIMIC-IV critical care database.

Jiaqi Cheng, Jiatong Hou, Yuefu Wang

Abstract read
In one paragraph

Article in Journal of medical biochemistry, 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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0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Jiaqi ChengBeijing Shijitan Hospital, Affiliated to Capital Medical University, Beijing, China.
Jiatong HouBeijing Shijitan Hospital, Affiliated to Capital Medical University, Beijing, China.
Yuefu WangBeijing Shijitan Hospital, Affiliated to Capital Medical University, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Sepsis constitutes a systemic dysregulated host response to infection and remains a predominant cause of ICU mortality globally. Given the limitations of conventional prognostic models (e.g., SOFA and APACHE II), incorporating variably subjective parameters, there is a pressing need to identify robust, objective biomarkers for early mortality risk stratification. This investigation delineated the prognostic significance of the lactate-to-albumin ratio (LAR) in predicting 28-day all-cause mortality (28-DACM) among critically ill septic cases. Methods: We performed a retrospective analysis utilizing the MIMIC-IV database (2008-2019), comprising 5,398 adult cases who met Sepsis-3 diagnostic criteria. Clinical and laboratory data within the initial 24-h post-ICU admission were extracted. The LASSO regression algorithm was implemented as a regularization technique to mitigate multicollinearity, enhance model generalizability, and facilitate high-dimensional feature selection. It was made to evaluate the prognostic utility of LAR through Kaplan-Meier (KM) survival estimation, receiver operating characteristic (ROC) curve analysis, and multivariate logistic regression modeling. Results: LAR values were remarkably escalated in non-survivors relative to survivors (median, 0.9 vs. 0.6; P < 0.001). ROC curve analysis unveiled that LAR outperformed lactate (AUC: 63.52% ), albumin (AUC: 43.34% ), and the SOFA score (AUC: 59.87% ), achieving the highest discriminatory capacity (AUC: 64.71% ; 95% CI: 62.85-66.58%). An optimal LAR threshold of 1.032 was identified, attaining sensitivity and specificity of 45.1% and 76.6% , respectively. KM analysis uncovered remarkably attenuated 28-day survival in cases with LAR >1.032 (P < 0.001). Multivariate logistic regression confirmed LAR as an independent predictor of 28-DACM (OR = 1.32; P < 0.001), following adjusting for confounding variables. Conclusions: The LAR serves as a clinically accessible, objective biomarker with superior prognostic performance relative to established indicators in association with sepsis. Its integration into early risk assessment algorithms may enhance prognostication and inform timely therapeutic decision-making. Prospective, multicenter investigations are warranted to validate its external generalizability and clinical utility.

Indexed as

all-cause mortalitylactate-to-albumin ratioMIMIC-IV databasesepsis

Identifiers

PMID41799713
PMCPMC12967197

What Socratic holds

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Registered trials

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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 Socratic graph.