Individualized resuscitation strategy for septic shock formalized by finite mixture modeling and dynamic treatment regimen

• Published in: Critical care (London, England) Vol. 25; no. 1; pp. 1 - 16
• Main Authors: 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, Zhongheng
• Format: Journal Article
• Language: English
• Published: London BioMed Central Ltd 12.07.2021; BioMed Central; BMC
• Subjects: Algorithms; Blood pressure; Care and treatment; Clinical medicine; Clinical trials; Creatinine; Critical care; Diagnosis; Dopamine; Dynamic treatment regime; Fluid resuscitation; Fluid therapy; Hospitals; Infections; Intervention; Laboratories; Machine learning; Methods; Mortality; Respiratory failure; Resuscitation; Sepsis; Septic shock; China

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...