Development and validation of a prediction model for invasive syndrome in liver abscess patients based on LASSO regression: a multi-center retrospective cohort study in China
We developed a nine-factor nomogram to predict individualized IKPLAS risk, demonstrating high discrimination and calibration, supporting early identification of high-risk patients and personalized management.
Authors
- Yongduan Song (ORCID: https://orcid.org/0000-0002-2167-1861)
- Yulin Ren (ORCID: https://orcid.org/0000-0003-3667-1466)
- Jialin Du
- Xiu‐Li Wang (ORCID: https://orcid.org/0000-0002-2732-9477)
- Hui Wang (ORCID: https://orcid.org/0000-0001-9651-2729)
- Xiaoyu Wen (ORCID: https://orcid.org/0000-0002-9037-8693)
- D Hao (ORCID: https://orcid.org/0000-0001-9006-0901)
- Changcheng Zhao (ORCID: https://orcid.org/0000-0002-8860-4954)
- Guang-Zhao Shao
Institutions
- Jilin University (CN)
- People's Liberation Army No. 150 Hospital (CN)
- First Hospital of Jilin University (CN)
- First Affiliated Hospital of Zhengzhou University (CN)
- Luoyang Orthopedic-Traumatological Hospital of Henan Province (CN)
Publication Details
- Journal
- Frontiers in Medicine
- Published
- 2025-11-28
- DOI
- https://doi.org/10.3389/fmed.2025.1572054
- Primary Topic
- Amoebic Infections and Treatments
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- People's Government of Jilin Province