Identifying septic shock subgroups to tailor fluid strategies through multi-omics integration

Zhongheng Zhang (), Lin Chen, Bin Sun, Zhanwei Ruan, Pan Pan, Weimin Zhang, Xuandong Jiang, Shaojiang Zheng, Shaowen Cheng, Lina Xian, Bingshu Wang, Jie Yang, Bo Zhang, Ping Xu, Zhitao Zhong, Lingxia Cheng, Hongying Ni and Yucai Hong
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Zhongheng Zhang: Zhejiang University School of Medicine
Lin Chen: Zhejiang University School of Medicine
Bin Sun: Binzhou Medical University Hospital
Zhanwei Ruan: Wenzhou Medical University
Pan Pan: Chinese PLA General Hospital
Weimin Zhang: Dongyang
Xuandong Jiang: Dongyang
Shaojiang Zheng: The First Affiliated Hospital of Hainan Medical University
Shaowen Cheng: The First Affiliated Hospital of Hainan Medical University
Lina Xian: The First Affiliated Hospital of Hainan Medical University
Bingshu Wang: The Second Affiliated Hospital of Hainan Medical University
Jie Yang: Zhejiang University School of Medicine
Bo Zhang: Zhejiang University School of Medicine
Ping Xu: Zigong Fourth People’s Hospital
Zhitao Zhong: Zigong Fourth People’s Hospital
Lingxia Cheng: Zigong Fourth People’s Hospital
Hongying Ni: Zhejiang University School of Medicine
Yucai Hong: Zhejiang University School of Medicine

Nature Communications, 2024, vol. 15, issue 1, 1-14

Abstract: Abstract Fluid management remains a critical challenge in the treatment of septic shock, with individualized approaches lacking. This study aims to develop a statistical model based on transcriptomics to identify subgroups of septic shock patients with varied responses to fluid strategy. The study encompasses 494 septic shock patients. A benefit score is derived from the transcriptome space, with higher values indicating greater benefits from restrictive fluid strategy. Adherence to the recommended strategy is associated with a hazard ratio of 0.82 (95% confidence interval: 0.64–0.92). When applied to the baseline hospital mortality rate of 16%, adherence to the recommended fluid strategy could potentially lower this rate to 13%. A proteomic signature comprising six proteins is developed to predict the benefit score, yielding an area under the curve of 0.802 (95% confidence interval: 0.752–0.846) in classifying patients who may benefit from a restrictive strategy. In this work, we develop a proteomic signature with potential utility in guiding fluid strategy for septic shock patients.

Date: 2024
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DOI: 10.1038/s41467-024-53239-9

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