Individualized resuscitation strategy for septic shock formalized by finite mixture modeling and dynamic treatment regimen
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Published:2021-07-12
Issue:1
Volume:25
Page:
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ISSN:1364-8535
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Container-title:Critical Care
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language:en
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Short-container-title:Crit Care
Author:
Ma Penglin, Liu Jingtao, Shen Feng, Liao Xuelian, Xiu Ming, Zhao Heling, Zhao Mingyan, Xie Jing, Wang Peng, Huang Man, Li Tong, Duan Meili, Qian Kejian, Peng Yue, Zhou Feihu, Xin Xin, Wan Xianyao, Wang ZongYu, Li Shusheng, Han Jianwei, Li Zhenliang, Ding Guolei, Deng Qun, Zhang Jicheng, Zhu Yue, Ma Wenjing, Wang Jingwen, Kang Yan, Zhang ZhonghengORCID
Abstract
Abstract
Background
Septic shock comprises a heterogeneous population, and individualized resuscitation strategy is of vital importance. The study aimed to identify subclasses of septic shock with non-supervised learning algorithms, so as to tailor resuscitation strategy for each class.
Methods
Patients with septic shock in 25 tertiary care teaching hospitals in China from January 2016 to December 2017 were enrolled in the study. Clinical and laboratory variables were collected on days 0, 1, 2, 3 and 7 after ICU admission. Subclasses of septic shock were identified by both finite mixture modeling and K-means clustering. Individualized fluid volume and norepinephrine dose were estimated using dynamic treatment regime (DTR) model to optimize the final mortality outcome. DTR models were validated in the eICU Collaborative Research Database (eICU-CRD) dataset.
Results
A total of 1437 patients with a mortality rate of 29% were included for analysis. The finite mixture modeling and K-means clustering robustly identified five classes of septic shock. Class 1 (baseline class) accounted for the majority of patients over all days; class 2 (critical class) had the highest severity of illness; class 3 (renal dysfunction) was characterized by renal dysfunction; class 4 (respiratory failure class) was characterized by respiratory failure; and class 5 (mild class) was characterized by the lowest mortality rate (21%). The optimal fluid infusion followed the resuscitation/de-resuscitation phases with initial large volume infusion and late restricted volume infusion. While class 1 transitioned to de-resuscitation phase on day 3, class 3 transitioned on day 1. Classes 1 and 3 might benefit from early use of norepinephrine, and class 2 can benefit from delayed use of norepinephrine while waiting for adequate fluid infusion.
Conclusions
Septic shock comprises a heterogeneous population that can be robustly classified into five phenotypes. These classes can be easily identified with routine clinical variables and can help to tailor resuscitation strategy in the context of precise medicine.
Funder
Yilu Gexin Fluid Therapy Research Fund Project Young Scientists Fund
Publisher
Springer Science and Business Media LLC
Subject
Critical Care and Intensive Care Medicine
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