PulseExploreJournal ClubDebatesTrendingResearchersJournals
Instagram
HomeExploreJournal ClubTrending
Synapse
⌘+K
Synapse
May 15, 2026Scientific Reports0 citationsOpen Access

The relationship between lactate-to-albumin ratio and prognosis in patients with sepsis-induced cardiomyopathy: a retrospective cohort study

JDJian Deng

Key Result

A high lactate-to-albumin ratio was independently associated with increased 28-day mortality in patients with sepsis-induced cardiomyopathy (adjusted OR 1.42; 95% CI 1.04-1.93).

Key Points

  • Evaluate the prognostic value of lactate-to-albumin ratio (LAR) in patients with sepsis-induced cardiomyopathy (SICM).
  • Retrospective analysis of data from SICM patients admitted to the ICU (2008-2022)
  • Calculated LAR using laboratory values within 24 hours of ICU admission
  • Performed survival analysis using Kaplan–Meier curves and multivariate logistic regression for mortality assessment.
  • Optimal LAR cutoff was found to be 1.094
  • High-LAR group exhibited significantly higher 28-day mortality (log-rank P < 0.001)
  • LAR was confirmed as an independent predictor of mortality (adjusted OR = 1.42, 95% CI: 1.04–1.93).

Study Design

Type

Cohort (n=1,810)

Multicenter

No

Structured PICO

Does a high lactate-to-albumin ratio predict 28-day mortality in patients with sepsis-induced cardiomyopathy?

P
Population
1,810 patients with sepsis-induced cardiomyopathy (SICM) admitted to the intensive care unit (ICU) of Beth Israel Deaconess Medical Center between 2008 and 2022.
I
Intervention
High lactate-to-albumin ratio (LAR) based on an optimal cutoff of 1.094, calculated using laboratory values obtained within 24 h of ICU admission
C
Comparator
Low lactate-to-albumin ratio (LAR) below the 1.094 cutoff
O
Outcome
28-day mortalityhard clinical

The lactate-to-albumin ratio is an independent predictor of 28-day mortality in patients with sepsis-induced cardiomyopathy, suggesting its utility as a practical biomarker for risk stratification.

Main Result

Effect estimate: adjusted OR 1.42 (95% CI 1.04-1.93)

p-value: p=<0.001

Abstract

The lactate-to-albumin ratio (LAR) has been reported as a prognostic marker in various diseases, but its association with outcomes in patients with sepsis-induced cardiomyopathy (SICM) remains unclear. This study aimed to evaluate the prognostic value of LAR in SICM patients. We retrospectively analyzed data from SICM patients admitted to the intensive care unit (ICU) of Beth Israel Deaconess Medical Center between 2008 and 2022. LAR was calculated using laboratory values obtained within 24 h of ICU admission. The optimal LAR cutoff was determined using R software. Survival analysis was performed with Kaplan–Meier curves, and multivariate logistic regression models were used to assess the association between LAR and 28-day mortality. Restricted cubic spline (RCS) analysis explored the dose–response relationship, and subgroup analyses evaluated consistency across populations. Among 1,810 included patients, the optimal LAR cutoff was 1.094. Kaplan–Meier analysis showed significantly higher 28-day mortality in the high-LAR group (log-rank P < 0.001). Multivariate logistic regression confirmed LAR as an independent predictor of mortality (adjusted OR = 1.42, 95% CI: 1.04–1.93). RCS revealed a non-linear relationship between LAR and mortality ( P for non-linear = 0.001), and subgroup analyses showed no significant interactions. LAR is independently associated with short-term prognosis in SICM patients and may serve as a practical biomarker for risk stratification.

Ask AI
Helpful
Bookmark
Share
View Full Paper

Cite This Study

Jian Deng (2026) conducted a cohort in Sepsis-induced cardiomyopathy (SICM) (n=1,810). Lactate-to-albumin ratio (LAR) vs. Low lactate-to-albumin ratio was evaluated on 28-day mortality (adjusted OR 1.42, 95% CI 1.04-1.93, p=<0.001). A high lactate-to-albumin ratio was independently associated with increased 28-day mortality in patients with sepsis-induced cardiomyopathy (adjusted OR 1.42; 95% CI 1.04-1.93).

synapsesocial.com/papers/6a06bbe8e7dec685947ac93bhttps://doi.org/10.1038/s41598-026-53097-z
Ask AI
Helpful
Bookmark
Share
View Full Paper