ArticleFrontiers in medicine2026
Development and validation of a prediction model for refeeding syndrome in ICU patients receiving mechanical ventilation and enteral nutrition support: a single-center retrospective study from China.
Article in Frontiers in medicine, 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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Abstract
Objective: To develop and validate a risk prediction model for refeeding syndrome (RFS) in mechanically ventilated patients in the intensive care unit (ICU) receiving initial enteral nutrition therapy. Design: A retrospective cohort study was conducted at a tertiary hospital in Shenzhen, China. Setting: This single-center study was conducted in a tertiary hospital in Shenzhen, China. Participants: Patients who were admitted to the ICU of a tertiary hospital in Shenzhen for the first time and received enteral nutrition support between January 2022 and December 2024 were selected. The cohort was divided into a modeling set ( Methods: Factors potentially associated with refeeding syndrome (RFS) were collected, including patients' clinical indicators and refeeding-related conditions. Patients were divided into RFS and non-RFS groups according to the presence or absence of RFS. Potential variables were screened using the least absolute shrinkage and selection operator (LASSO) regression, followed by multivariate logistic regression analysis; a nomogram model was then constructed and validated. Results: Among the 664 patients in the modeling cohort, 300 cases (45.18%) developed refeeding syndrome (RFS). Following LASSO regression, multivariate logistic regression analysis was performed, and the results revealed that age ≥ 60 years, Nutritional Risk Screening 2002 (NRS-2002) score ≥ 3 points, Sequential Organ Failure Assessment (SOFA) score ≥ 10 points, Acute Physiology and Chronic Health Evaluation II (APACHE II) score ≥ 20 points, and pre-feeding albumin (ALB) < 30 g/L were identified as independent risk factors for RFS in mechanically ventilated ICU patients receiving enteral nutrition support ( Conclusion: The prediction model demonstrates good discrimination and calibration, enabling intuitive and convenient identification of ICU patients receiving enteral nutrition who are at high risk of refeeding syndrome, thereby providing a reference for early screening and intervention.
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