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Development and validation of glucose trajectory subphenotypes in critically ill patients on early enteral nutrition: a retrospective cohort study
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  • Published: 02 April 2026

Development and validation of glucose trajectory subphenotypes in critically ill patients on early enteral nutrition: a retrospective cohort study

  • Chenxi Weng1,
  • Jie Su1,
  • Huijuan Wang1,
  • Qi Lu1 &
  • …
  • Lixia Chen1 

Scientific Reports , Article number:  (2026) Cite this article

We are providing an unedited version of this manuscript to give early access to its findings. Before final publication, the manuscript will undergo further editing. Please note there may be errors present which affect the content, and all legal disclaimers apply.

Subjects

  • Diseases
  • Endocrinology
  • Health care
  • Medical research
  • Risk factors

Abstract

This study aimed to characterize blood glucose trajectories during the early phase of enteral nutrition (EN) in critically ill patients and develop a predictive model for these trajectories to improve clinical management and patient outcomes. A retrospective analysis was conducted on critically ill patients who received continuous EN for ≥ 2 consecutive days, using data from the intensive care unit (ICU) of a tertiary hospital. Group-Based Trajectory Modeling (GBTM) was employed to identify distinct subgroups based on patterns of blood glucose changes. An early risk prediction model for trajectory classification was constructed using the eXtreme Gradient Boosting (XGBoost) algorithm. A total of 478 patients met the inclusion criteria. Three distinct blood glucose trajectory subgroups were identified: Mild Hyperglycemia Stable (41.84%), Moderate Hyperglycemia Peaking (36.40%), and Severe Hyperglycemia Peaking (21.76%). The XGBoost model exhibited robust discriminative ability and good calibration. Key predictors of trajectory classification included insulin use, history of diabetes, C-reactive protein, and interleukin-6. This study highlights the heterogeneity of glycemic trajectories during the early phase of EN in critically ill patients. The developed XGBoost model demonstrated satisfactory predictive performance and may serve as a valuable tool for maintaining glycemic stability and optimizing outcomes in critically ill patients receiving nutritional support in the ICU.

Data availability

Data sets are not publicly available because they contain information that could compromise the privacy of research participants, but the minimal data used and/or analyzed in this study may be provided to the corresponding authors at their reasonable request.

Code availability

The custom code and analysis scripts used in this study are publicly archived in a Zenodo repository (https://zenodo.org/records/18580968) and correspond to release v1.0.0. The repository includes documentation and instructions for reproducibility.

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Acknowledgements

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Authors and Affiliations

  1. Department of Nursing, the Fourth Affiliated Hospital of School of Medicine, and International School of Medicine, International Institutes of Medicine, Zhejiang University, Yiwu, 322000, China

    Chenxi Weng, Jie Su, Huijuan Wang, Qi Lu & Lixia Chen

Authors
  1. Chenxi Weng
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  2. Jie Su
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  3. Huijuan Wang
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  4. Qi Lu
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  5. Lixia Chen
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Contributions

Study design: W.C.X, S.J, C.L.X. Data collection: W.H.J, L.Q. Data analysis: W.C.X, S.J. Study supervision: C.L.X. Manuscript writing: W.C.X, S.J. Critical revisions for important intellectual content: C.L.X. All listed authors meet the authorship criteria and all authors agree with the content of the manuscript.

Corresponding author

Correspondence to Lixia Chen.

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Competing interests

The authors declare no competing interests.

Ethics declarations

This study was approved by the Ethics Committee of the Fourth Affiliated Hospital of Zhejiang University School of Medicine (Ethics Approval Number: K2025118) and registered with the Chinese Clinical Trial Registry (ChiCTR2500103452).

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Weng, C., Su, J., Wang, H. et al. Development and validation of glucose trajectory subphenotypes in critically ill patients on early enteral nutrition: a retrospective cohort study. Sci Rep (2026). https://doi.org/10.1038/s41598-026-47083-8

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  • Received: 07 August 2025

  • Accepted: 30 March 2026

  • Published: 02 April 2026

  • DOI: https://doi.org/10.1038/s41598-026-47083-8

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Keywords

  • Intensive care units
  • Enteral nutrition
  • Blood glucose
  • Trajectory modeling
  • Prediction model
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