ArticleScientific reports2026
Association between lactate-to-albumin ratio and 30-day all-cause mortality in patients with acute pancreatitis-associated acute kidney injury.
Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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.
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.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In recent years, the lactate-to-albumin ratio (LAR) has emerged as a novel prognostic marker in various critical illnesses, including sepsis, heart failure, and acute respiratory failure. However, its predictive value in patients with acute pancreatitis (AP)-particularly those who develop acute pancreatitis-associated acute kidney injury (AP-AKI)-has not been fully evaluated. Given the high short-term all-cause mortality observed in AP-AKI patients, this study aims to examine the association between admission LAR levels and 30-day all-cause mortality in this population, with the goal of providing new evidence for clinical risk stratification and early intervention. We performed a retrospective cohort study of 877 critically ill patients with AP-AKI using the MIMIC-IV/III database, and used the eICU-CRD database and a cohort of AP-AKI patients admitted to the Department of Critical Care Medicine, First Affiliated Hospital of Fujian Medical University (FAHFMU) for external validation. Patients were stratified into four groups according to LAR quartiles. Confounding was assessed via linear or logistic regression with stepwise covariate removal, and univariable and multivariable Cox models were used to identify predictors of mortality. ROC analysis (AUC) evaluated LAR and other markers, establishing an optimal cut-off for Kaplan-Meier survival curves (log-rank test). Restricted cubic spline (RCS) functions were used to explore the potential nonlinear relationship between LAR and 30-day mortality. Subgroup analyses were conducted across age, sex, comorbidities, and treatment categories. The study found that higher LAR levels were significantly associated with increased 30-day mortality in AP-AKI patients. After adjusting for potential confounders, LAR remained an independent predictor of mortality (HR 1.172, 95% CI 1.054-1.303, P < 0.05). ROC analysis showed an AUC of 0.695 for LAR, surpassing that of lactate alone (0.683) or albumin (0.589), and comparable to the SOFA score (0.684). Compared with the low LAR group, the high LAR group had a significantly higher mortality rate (P < 0.001), and a nonlinear association between LAR and 30-day mortality was observed. LAR is an independent predictor of 30-day all-cause mortality in AP-AKI. Given its simplicity and accessibility yet modest discrimination, LAR may serve as a useful adjunct for early risk assessment, particularly when combined with established scores or used serially.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.