ArticleFrontiers in medicine2026
Development and internal validation of a prediction model for early identification of sepsis-associated acute kidney injury based on admission serum biomarkers: a retrospective cohort study.
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.
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Abstract
Objective: Sepsis-associated acute kidney injury (SA-AKI) is a critical complication that substantially increases intensive care unit mortality. Early identification is paramount for timely intervention. This study aimed to develop and internally validate a prediction model relying exclusively on the first serum laboratory indicators after hospital admission to predict SA-AKI risk at the earliest available laboratory assessment. Methods: Clinical data of 1,573 sepsis patients admitted to West China Hospital of Sichuan University (January 2024-December 2025) were retrospectively analyzed. Patients were divided into SA-AKI and non-SA-AKI groups per 2012 KDIGO criteria, and randomly split into training (70%, Results: LASSO regression selected 10 serum indicators, and multivariate logistic regression confirmed 8 independent risk factors: myoglobin (MYO), alanine aminotransferase (ALT), phosphorus (PO Conclusions: This study developed and internally validated a promising predictive model for estimating SA-AKI risk in sepsis patients using solely first routine serum laboratory indicators after admission. A nomogram is provided for individualized bedside risk estimation. This tool may support early risk stratification of high-risk individuals. External validation in multi-center, diverse cohorts is warranted before broader clinical implementation.
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