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利用体温轨迹识别新型脓毒症亚表型

Identifying Novel Sepsis Subphenotypes Using Temperature Trajectories.

机构信息

1Department of Medicine and.

2Department of Medicine, Loyola University Medical Center, Chicago, Illinois.

出版信息

Am J Respir Crit Care Med. 2019 Aug 1;200(3):327-335. doi: 10.1164/rccm.201806-1197OC.

Abstract

Sepsis is a heterogeneous syndrome, and identifying clinically relevant subphenotypes is essential. To identify novel subphenotypes in hospitalized patients with infection using longitudinal temperature trajectories. In the model development cohort, inpatient admissions meeting criteria for infection in the emergency department and receiving antibiotics within 24 hours of presentation were included. Temperature measurements within the first 72 hours were compared between survivors and nonsurvivors. Group-based trajectory modeling was performed to identify temperature trajectory groups, and patient characteristics and outcomes were compared between the groups. The model was then externally validated at a second hospital using the same inclusion criteria. A total of 12,413 admissions were included in the development cohort, and 19,053 were included in the validation cohort. In the development cohort, four temperature trajectory groups were identified: "hyperthermic, slow resolvers" ( = 1,855; 14.9% of the cohort); "hyperthermic, fast resolvers" ( = 2,877; 23.2%); "normothermic" ( = 4,067; 32.8%); and "hypothermic" ( = 3,614; 29.1%). The hypothermic subjects were the oldest and had the most comorbidities, the lowest levels of inflammatory markers, and the highest in-hospital mortality rate (9.5%). The hyperthermic, slow resolvers were the youngest and had the fewest comorbidities, the highest levels of inflammatory markers, and a mortality rate of 5.1%. The hyperthermic, fast resolvers had the lowest mortality rate (2.9%). Similar trajectory groups, patient characteristics, and outcomes were found in the validation cohort. We identified and validated four novel subphenotypes of patients with infection, with significant variability in inflammatory markers and outcomes.

摘要

脓毒症是一种异质性综合征,确定临床相关的亚表型至关重要。使用纵向体温轨迹来确定感染住院患者中的新型亚表型。在模型开发队列中,包括符合急诊科感染标准并在就诊后 24 小时内接受抗生素治疗的住院患者。比较幸存者和非幸存者在最初 72 小时内的体温测量值。对温度轨迹组进行基于组的轨迹建模,并比较组间患者特征和结局。然后使用相同的纳入标准在第二家医院进行模型外部验证。共纳入开发队列 12413 例,验证队列 19053 例。在开发队列中,确定了四个体温轨迹组:“高热、缓慢消退者”(1855 例;队列的 14.9%);“高热、快速消退者”(2877 例;23.2%);“正常体温者”(4067 例;32.8%);和“低体温者”(3614 例;29.1%)。低体温组患者年龄最大,合并症最多,炎症标志物水平最低,院内死亡率最高(9.5%)。高热、缓慢消退者年龄最小,合并症最少,炎症标志物水平最高,死亡率为 5.1%。高热、快速消退者死亡率最低(2.9%)。在验证队列中也发现了类似的轨迹组、患者特征和结局。我们确定并验证了感染患者的四个新型亚表型,炎症标志物和结局存在显著差异。

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Identifying Novel Sepsis Subphenotypes Using Temperature Trajectories.利用体温轨迹识别新型脓毒症亚表型
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本文引用的文献

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Pediatric Sepsis Endotypes Among Adults With Sepsis.成人脓毒症中的儿童脓毒症内型
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Objective Sepsis Surveillance Using Electronic Clinical Data.使用电子临床数据进行脓毒症监测的目标
Infect Control Hosp Epidemiol. 2016 Feb;37(2):163-71. doi: 10.1017/ice.2015.264. Epub 2015 Nov 3.
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Sepsis: a roadmap for future research.脓毒症:未来研究的路线图。
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