An interpretable prediction model for severe sepsis-associated acute kidney injury in older ICU patients with sepsis: a prospective multicenter cohort study
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Wenliang Ma1, Jingyi Wang1, Jin Zhang1
1Department of Critical Care Medicine, Beijing Chao-Yang Hospital, Capital Medical University, Beijing, 100020, China.
Background:
Severe sepsis-associated acute kidney injury (severe SA-AKI) is clinically important in older adults with sepsis, but early identification remains challenging. This study aimed to characterize clinical and immuno-inflammatory features of severe SA-AKI and develop an interpretable prediction model for older ICU patients with sepsis.
Methods:
This prospective multicenter cohort study enrolled older adults with sepsis admitted to five tertiary ICUs between June 2023 and December 2025. Patients were temporally assigned to a training cohort and an internal temporal validation cohort. Severe SA-AKI was defined as KDIGO acute kidney injury stage 2 or 3 within 7 days after sepsis time zero or during ICU stay. Candidate predictors collected within 24 h after time zero were evaluated in the training cohort, and a logistic regression nomogram was developed and validated.
Results:
Among 1,236 included patients, the minimum age was 65 years, and the mean age was 74.6 ± 7.5 years; 258 patients developed severe SA-AKI. The final 7-variable model included non-renal SOFA score, chronic kidney disease, log(Lactate + 1), log(IL-6 + 1), NK-cell percentage, CD4 + T-cell percentage, and C3. The model achieved AUCs of 0.917 and 0.904 in the training and validation cohorts, respectively. Brier scores were 0.086 and 0.096. Severe SA-AKI incidence increased across low-, intermediate-, and high-risk groups: 0.5%, 13.0%, and 77.5%.
Conclusions:
A parsimonious model integrating clinical and immuno-inflammatory variables may support early severe SA-AKI risk stratification in older ICU patients with sepsis. External validation is warranted before broader clinical implementation.
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