Abstract
The purpose of this study was to evaluate the predictive value of monocyte-to-lymphocyte ratio (MLR) on the short-term (28 days) and long-term (365 days) mortality risk in patients with acute pancreatitis (AP) using multiple statistical and machine learning (ML) models. Studies selected 1,044 eligible AP patients from the MIMIC-IV database and divided them into four groups based on their MLR values (MLR<0.32; 0.32 ≤ MLR<0.57; 0.57 ≤ MLR<1; MLR ≥ 1). Findings revealed that MLR demonstrated a U-shaped relationship with patient mortality risk, with the minimal mortality risk occurring at an MLR of approximately 0.57. Cox regression model analysis showed that after adjusting for multiple parameters, MLR was still significantly associated with the risk of death. Moreover, ML model analysis identified that MLR has potential value in predicting AP patient outcomes. This study suggests that MLR can be used as a potential indicator to assess prognostic risk in critically ill patients with AP to support clinical decision-making.
Data availability
The datasets are available in the physionet (https://physionet.org/content/mimiciv/0.4/).
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Acknowledgements
We acknowledged the contributions of the MIMIC-IV 2.2 program registry for creating and updating the MIMIC-IV database. Thanks to AJE for polishing the article.
Funding
Wei Wu grants from National Natural Science Foundation of China (82302418).
JunYuan Yang grants from Natural Science Foundation of Hubei Province (2024AFB530).
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JYY, CTD and MMG contributed equally to this work. WW designed the study, JYY and MMG drafted the manuscript. CTD, SY extracted the data from the MIMIC-IV database. SY, JDC analyzed the data, HDZ, HG, JX and YL guided the literature review. All authors read and approved the final manuscript.
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The MIMIC-IV database was approved by the Massachusetts Institute of Technology (Cambridge, MA) and consent was obtained for the original data collection.
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Yang, J., Dong, C., Guo, M. et al. Association between monocyte-to-lymphocyte ratio and mortality in patients with acute pancreatitis requiring intensive care unit admission: a retrospective cohort study and predictive model establishment based on machine learning. Sci Rep (2026). https://doi.org/10.1038/s41598-026-37791-6
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DOI: https://doi.org/10.1038/s41598-026-37791-6
