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Peer-reviewedCC BY-NC-ND 4.0BMC Gastroenterology

Prediction of 30-day mortality risk in patients with acute pancreatitis in ICU: a study based on the MIMIC-IV database

  • Huagen Li1,2,3
  • Zhen Liu1,2,3
  • Yixi Zhang1,2,3
  • Xumeng Fang4
4 affiliations
  1. 1Department of General Surgery, Beijing Friendship Hospital, Capital Medical University, Beijing, China
  2. 2State Key Laboratory of Digestive Health, Beijing Friendship Hospital, Capital Medical University, Beijing, China
  3. 3National Clinical Research Center for Digestive Disease, Beijing Friendship Hospital, Capital Medical University, Beijing, China
  4. 4Department of Radiation Oncology, Cancer Center, Zhongshan Hospital, Fudan University, Shanghai, China
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Abstract

Background: Acute pancreatitis (AP) in the intensive care unit (ICU) exhibits rapid progression and high 30-day mortality, necessitating efficient early risk prediction methods.

Methods: This study analyzed 724 ICU patients from the MIMIC-IV database. Key predictors were screened using LASSO regression, and a multivariate logistic regression model was constructed to evaluate 30-day mortality risk.

Results: Twelve key predictors–including blood urea nitrogen (BUN), red blood cell distribution width (RDW), pH, sepsis status, and vasopressor use—were identified. The model demonstrated strong discrimination, with area under the curve (AUC) values of 0.85 and 0.89 across sets, an overall accuracy of 77%, and significantly lower 30-day survival in high-risk groups (60% vs. 97%).

Conclusions: The proposed model effectively stratifies 30-day mortality risk in ICU AP patients, offering valuable support for early clinical intervention and personalized management.

Clinical trial number: Not applicable.

Supplementary Information: The online version contains supplementary material available at https://doi.org/10.1186/s12876-026-05463-4.

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Cite

BibTeXRIS
BibTeX
@article{li2026prediction,
  title = {{Prediction of 30-day mortality risk in patients with acute pancreatitis in ICU: a study based on the MIMIC-IV database}},
  author = {Huagen Li and Zhen Liu and Yixi Zhang and Xumeng Fang},
  journal = {BMC Gastroenterology},
  year = {2026},
  month = nov,
  doi = {10.1186/s12876-026-05463-4},
  url = {https://doi.org/10.1186/s12876-026-05463-4},
  note = {CC BY-NC-ND 4.0},
}
RIS
TY  - JOUR
TI  - Prediction of 30-day mortality risk in patients with acute pancreatitis in ICU: a study based on the MIMIC-IV database
AU  - Huagen Li
AU  - Zhen Liu
AU  - Yixi Zhang
AU  - Xumeng Fang
PY  - 2026
DA  - 2026/11/02
JO  - BMC Gastroenterology
DO  - 10.1186/s12876-026-05463-4
UR  - https://doi.org/10.1186/s12876-026-05463-4
AB  - Background: Acute pancreatitis (AP) in the intensive care unit (ICU) exhibits rapid progression and high 30-day mortality, necessitating efficient early risk prediction methods.  Methods: This study analyzed 724 ICU patients from the MIMIC-IV database. Key predictors were screened using LASSO regression, and a multivariate logistic regression model was constructed to evaluate 30-day mortality risk.  Results: Twelve key predictors–including blood urea nitrogen (BUN), red blood cell distribution width (RDW), pH, sepsis status, and vasopressor use—were identified. The model demonstrated strong discrimination, with area under the curve (AUC) values of 0.85 and 0.89 across sets, an overall accuracy of 77%, and significantly lower 30-day survival in high-risk groups (60% vs. 97%).  Conclusions: The proposed model effectively stratifies 30-day mortality risk in ICU AP patients, offering valuable support for early clinical intervention and personalized management.  Clinical trial number: Not applicable.  Supplementary Information: The online version contains supplementary material available at https://doi.org/10.1186/s12876-026-05463-4.
SN  - 1471-230X
ER  -