A Prediction Model for Persistent Inflammation-Immunosuppression-Catabolism Syndrome in Patients with Sepsis: An Ambispective Cohort Study

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Objective: To develop and temporally validate an admission-variable model for estimating the risk of persistent inflammation-immunosuppression-catabolism syndrome (PICS) among patients with sepsis who remained in the intensive care unit (ICU) for ≥14 days. Methods: We conducted an ambispective, single-center cohort study. The retrospective development cohort included patients admitted from January 2023 to May 2025, and the prospective temporal validation cohort included patients admitted from June 2025 to February 2026. Candidate predictors measured at ICU admission were selected using least absolute shrinkage and selection operator (LASSO) regression and entered into a multivariable logistic regression model. Discrimination, calibration, and potential clinical utility were evaluated using the area under the receiver operating characteristic curve (AUC), calibration analyses, and decision curve analysis. Results: The development cohort included 242 patients, of whom 93 (38.4%) met the PICS criteria. Compared with respiratory infection, urinary infection (adjusted odds ratio (aOR 0.07, 95% CI 0.01-0.67), gastrointestinal infection (aOR 0.15, 95% CI 0.05-0.45), and skin or soft-tissue infection (aOR 0.29, 95% CI 0.11-0.77) were associated with lower odds of PICS. Higher lactate was associated with higher odds of PICS (aOR 1.20, 95% CI 1.07-1.34), whereas higher lymphocyte count (aOR 0.46, 95% CI 0.28-0.77), albumin (aOR 0.92, 95% CI 0.86-0.99), and vitamin D (aOR 0.88, 95% CI 0.83-0.94) were associated with lower odds. The AUC was 0.803 (95% CI 0.747-0.859) in the development cohort and 0.791 (95% CI 0.718-0.864) in the temporal validation cohort. Conclusion: Among patients with sepsis who remained in the ICU for ≥14 days, an admission-variable model showed acceptable discrimination in the development and temporal validation cohorts. External multicenter validation and prospective impact evaluation are required before clinical use.

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