医学
重症监护室
纵向研究
损伤严重程度评分
重症监护医学
创伤中心
队列
临床试验
内科学
组学
急诊医学
外伤
个性化医疗
生物信息学
精密医学
年轻人
疾病严重程度
队列研究
临床意义
重症监护
病理生理学
生物标志物发现
疾病
试验预测值
梅德林
生物标志物
纵向数据
病理
作者
Mitchell J. Cohen,Christopher Erickson,Ian S. Lacroix,Margot DeBot,Monika Ewa Dzieciatkowska,Sanchayita Sen,Terry R. Schaid,Lauren T. Gallagher,William Hallas,Otto Thielen,Alexis Cralley,Benjamin Stocker,Benjamin Ramser,Ava K. Mokhtari,Huma Baig,Christopher Sublette,Franklyn Nonso Iheagwam,Alyssa Caldwell-McGee,Jamie Cole,Kelly Nash
标识
DOI:10.1126/scitranslmed.adw5223
摘要
Understanding the complexity of trauma-induced thromboinflammation necessitates data-driven approaches. We hypothesized that longitudinal plasma profiling could reveal underlying differences in patients with injury who present with similar clinical characteristics but ultimately have different outcomes. Here, we performed multiomic analyses of longitudinal plasma samples from a clinical trial of patients with traumatic injury to identify molecular endotypes and trajectories that were associated with patient outcomes. The pathophysiologic states of patients with trauma were defined by the longitudinal proteomic and metabolomic plasma profiles from a diverse cohort. Then, patients were endotyped according to their longitudinal trajectories through trauma omic states, and injury patterns and outcomes were compared. We identified endotypes associated with divergent clinical outcomes despite similar injury patterns at presentation. Organ failure and time spent in the intensive care unit (ICU) were predicted with high accuracy using omic markers. Patients who presented with evidence of elevated proteasome activation, catabolism, and superoxide formation were vulnerable to heart failure, lung failure, and acute lung injury, respectively. In addition, omic markers of increased hypoxia, RBC lysis, and hydrolase activity better fit mortality and ICU time compared with injury covariates, while providing biological insight. Injury and outcome patterns persisted in a validation trauma cohort after endotype assignment at a single, early time point. These data align with the understanding that patients with trauma may experience markedly different biological responses and outcomes despite similar clinical presentations. We suggest that mapping patient trajectories through biological injury states could provide a framework for personalized patient treatment after trauma.
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