# Decoding dynamic lipase trajectory patterns and in-hospital mortality in acute pancreatitis: insights from machine learning in intensive care units

**Authors:** Yingyi Li, Xiaoqiang Liu, Xiaodong Zhu, Chanchan Lin, Qilin Yang, Zicheng Huang, Yisen Huang

PMC · DOI: 10.1186/s40001-025-03299-4 · European Journal of Medical Research · 2025-10-22

## TL;DR

The study uses machine learning to identify different patterns of serum lipase levels in acute pancreatitis patients and finds that these patterns are linked to in-hospital mortality.

## Contribution

The novel use of latent class trajectory modeling to classify lipase patterns and assess their mortality risk in acute pancreatitis patients.

## Key findings

- Three distinct lipase trajectory phenotypes were identified in acute pancreatitis patients.
- Class 2 and Class 3 lipase patterns were associated with significantly higher in-hospital mortality risk compared to Class 1.
- Monitoring lipase trajectories could improve risk stratification and clinical management in acute pancreatitis.

## Abstract

Serum lipase levels are crucial biomarkers in acute pancreatitis (AP), yet their dynamic patterns and prognostic implications remain incompletely understood. This study aimed to identify distinct lipase trajectory phenotypes and evaluate their association with in-hospital mortality in AP patients.

We conducted a retrospective analysis of 834 AP patients from the MIMIC-IV database using latent class trajectory modeling (LCTM) to identify distinct lipase trajectory phenotypes. Cox regression models, adjusted for demographics, comorbidities, clinical therapies, and critical illness markers, were employed to assess the association between trajectory classes and in-hospital mortality.

Three distinct lipase trajectory phenotypes were identified: Class 1 (n = 543) with consistently low levels, Class 2 (n = 51) with extremely high and variable levels, and Class 3 (n = 240) with moderately elevated levels. Class 2 patients were significantly older (66.8 ± 17.6 years) and had higher comorbidity burden (CCI: 5.6 ± 3.0). In-hospital mortality rates were 12.2%, 17.6%, and 19.2% for Classes 1, 2, and 3, respectively. After comprehensive adjustment, both Class 2 (HR: 2.21, 95% CI 1.04–4.71, p = 0.042) and Class 3 (HR: 1.61, 95% CI 1.08–2.40, p = 0.022) showed significantly higher mortality risk compared to Class 1.

Dynamic lipase trajectory patterns in AP patients demonstrate distinct phenotypes with significant prognostic value for in-hospital mortality. These findings suggest that monitoring lipase trajectories may enhance risk stratification and guide clinical management in AP patients.

## Linked entities

- **Diseases:** acute pancreatitis (MONDO:0006515)

## Full-text entities

- **Diseases:** AP (MESH:D010195)
- **Species:** Homo sapiens (human, species) [taxon 9606]

## Full text

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## Figures

4 figures with captions in the complete paper: https://tomesphere.com/paper/PMC12542429/full.md

## References

2 references — full list in the complete paper: https://tomesphere.com/paper/PMC12542429/full.md

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Source: https://tomesphere.com/paper/PMC12542429