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Classification of patients with sepsis according to blood genomic endotype: a prospective cohort study

医学 内型 队列 败血症 前瞻性队列研究 队列研究 内科学 危险系数 重症监护医学 回顾性队列研究 置信区间 疾病
作者
Brendon P. Scicluna,Lonneke A. van Vught,Aeilko H. Zwinderman,Maryse A. Wiewel,Emma E. Davenport,Katie L. Burnham,Peter Nürnberg,Marcus J. Schultz,Janneke Horn,Olaf L. Cremer,Marc J. M. Bonten,Charles J. Hinds,Hector R. Wong,Julian C. Knight,Tom van der Poll,Friso M. de Beer,Lieuwe D. J. Bos,Jos F. Frencken,Maria E. Koster‐Brouwer,Kirsten van de Groep,Diana M. Verboom,Gerie J. Glas,Roosmarijn T. M. van Hooijdonk,Arie J. Hoogendijk,Mischa A. Huson,Peter M. Klein Klouwenberg,David S. Y. Ong,Laura R. A. Schouten,Marleen Straat,Esther Witteveen,Luuk Wieske
出处
期刊:The Lancet Respiratory Medicine [Elsevier]
卷期号:5 (10): 816-826 被引量:426
标识
DOI:10.1016/s2213-2600(17)30294-1
摘要

Host responses during sepsis are highly heterogeneous, which hampers the identification of patients at high risk of mortality and their selection for targeted therapies. In this study, we aimed to identify biologically relevant molecular endotypes in patients with sepsis.This was a prospective observational cohort study that included consecutive patients admitted for sepsis to two intensive care units (ICUs) in the Netherlands between Jan 1, 2011, and July 20, 2012 (discovery and first validation cohorts) and patients admitted with sepsis due to community-acquired pneumonia to 29 ICUs in the UK (second validation cohort). We generated genome-wide blood gene expression profiles from admission samples and analysed them by unsupervised consensus clustering and machine learning. The primary objective of this study was to establish endotypes for patients with sepsis, and assess the association of these endotypes with clinical traits and survival outcomes. We also established candidate biomarkers for the endotypes to allow identification of patient endotypes in clinical practice.The discovery cohort had 306 patients, the first validation cohort had 216, and the second validation cohort had 265 patients. Four molecular endotypes for sepsis, designated Mars1-4, were identified in the discovery cohort, and were associated with 28-day mortality (log-rank p=0·022). In the discovery cohort, the worst outcome was found for patients classified as having a Mars1 endotype, and at 28 days, 35 (39%) of 90 people with a Mars1 endotype had died (hazard ratio [HR] vs all other endotypes 1·86 [95% CI 1·21-2·86]; p=0·0045), compared with 23 (22%) of 105 people with a Mars2 endotype (HR 0·64 [0·40-1·04]; p=0·061), 16 (23%) of 71 people with a Mars3 endotype (HR 0·71 [0·41-1·22]; p=0·19), and 13 (33%) of 40 patients with a Mars4 endotype (HR 1·13 [0·63-2·04]; p=0·69). Analysis of the net reclassification improvement using a combined clinical and endotype model significantly improved risk prediction to 0·33 (0·09-0·58; p=0·008). A 140-gene expression signature reliably stratified patients with sepsis to the four endotypes in both the first and second validation cohorts. Only Mars1 was consistently significantly associated with 28-day mortality across the cohorts. To facilitate possible clinical use, a biomarker was derived for each endotype; BPGM and TAP2 reliably identified patients with a Mars1 endotype.This study provides a method for the molecular classification of patients with sepsis to four different endotypes upon ICU admission. Detection of sepsis endotypes might assist in providing personalised patient management and in selection for trials.Center for Translational Molecular Medicine, Netherlands.
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