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Prediction of severe sepsis-associated acute kidney injury incorporating immune-inflammatory profiles: development and validation of a machine learning model in a multicenter prospective cohort study

Key takeaways

Researchers built a computer model to spot which people with severe sepsis, a dangerous body-wide infection, will develop sudden kidney injury. They used immune and inflammation markers from patients at several hospitals. The model found patterns in past patients, but that is a link, not proof it will help new patients. It has not been tested in everyday care yet.

Who did this work

XIAOXIA GUO (Beijing Chao-Yang Hospital, Capital Medical University) · Fei Li (Beijing Chao-Yang Hospital, Capital Medical University) · Chang Xu (Beijing Chao-Yang Hospital, Capital Medical University) · Wenliang Ma (Beijing Chao-Yang Hospital, Capital Medical University) · Huimiao Jia (Beijing Chao-Yang Hospital, Capital Medical University) · Wenxiong Li (Beijing Chao-Yang Hospital, Capital Medical University) · Na Cui (Beijing Chao-Yang Hospital, Capital Medical University)

Source

Paper · OpenAlex, CKD works · 2026-08-11
https://doi.org/10.3389/fimmu.2026.1882789