Evidence map›Paper›PMID 42701811›Full record

ArticleInfection and drug resistance2026

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

Xiangning Zhong, Jindai Yang, Le Chang, Xiaoyu Wang, Lan Peng, Wenjuan Yan, Hongbin Hu, Zhongqing Chen, Yaoyuan Zhang

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Article in Infection and drug resistance, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

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9 authors.

Xiangning Zhong *Department of Critical Care Medicine, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong, People's Republic of China.
Jindai Yang *Department of Critical Care Medicine, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong, People's Republic of China.
Le ChangDepartment of Critical Care Medicine, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong, People's Republic of China.
Xiaoyu WangDepartment of Critical Care Medicine, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong, People's Republic of China.ORCID 0009-0004-3498-7349
Lan PengDepartment of Critical Care Medicine, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong, People's Republic of China.
Wenjuan YanDepartment of Critical Care Medicine, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong, People's Republic of China.
Hongbin HuDepartment of Critical Care Medicine, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong, People's Republic of China.
Zhongqing ChenDepartment of Critical Care Medicine, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong, People's Republic of China.
Yaoyuan ZhangDepartment of Critical Care Medicine, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Indexed as

intensive care unitpersistent inflammation-immunosuppression catabolism syndromevitamin D

Identifiers

PMID42701811
PMCPMC13546036

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.