Ehrman Robert R, Sherwin Robert L, Reynolds Christian A, Korzeniewski Steven J, Welch Robert D, Kline Jeffrey A, Ying Hao, Levy Phillip D
Department of Emergency Medicine, Wayne State University School of Medicine, Detroit, Michigan, USA
Department of Emergency Medicine, Wayne State University School of Medicine, Detroit, Michigan, USA.
BMJ Open. 2025 Jun 8;15(6):e098987. doi: 10.1136/bmjopen-2025-098987.
Sepsis is a common condition with significant morbidity, mortality and annual costs of care in the billions of dollars. Despite innumerable studies on the causes of, and therapies for, sepsis, the mortality rate has not changed substantially in the last 20 years. Treatments remain generic, with current guidelines recommending the same approach for all patients, regardless of the litany of differences that exist at baseline. Moreover, the blanket administration of 30 cc/kg of intravenous fluid (IVF) to all patients is recognised as being directly harmful to some. Patient-level heterogeneity in prior sepsis trials is recognised as a substantial contributor to all these problems, yet no prior investigation has attempted to identify volume-informed septic phenotypes, a necessary first step towards precision care.
Predicated on prior studies demonstrating detectability of organ-level congestion, we hypothesise that central venous hypertension (1) is deleterious to the function of the lungs, liver, kidneys and vascular endothelium; (2) is worsened by cardiac dysfunction and IVF administration; and (3) contributes to adverse organ-specific and overall outcomes. Beginning in the emergency department, cardiac function will be assessed with echocardiography while congestion in the lungs and kidneys will be assessed using previously validated sonographic markers of congestion. Biomarkers for each organ will be collected concurrently, thereby increasing the fidelity of our phenotypic profiles by pairing indicators of macroscopic and microscopic stress and dysfunction. Data will also be collected at 24 hours and 7 days (or discharge, whichever comes first) after presentation. Classical and machine learning approaches will be used to analyse our large data stream and develop a rule-based system to identify distinct subpopulations of patients with sepsis who have greater risk/likelihood of both organ-specific and overall adverse outcomes.
This project has been approved by the Wayne State University Institutional Review Board, with patient enrolment beginning in April 2024. Findings will be reported and disseminated via conference presentations and open-access publications.
脓毒症是一种常见病症,具有较高的发病率、死亡率,每年的护理费用高达数十亿美元。尽管针对脓毒症的病因和治疗方法进行了无数研究,但在过去20年中死亡率并未有显著变化。治疗方法仍然缺乏针对性,当前指南建议对所有患者采用相同的治疗方法,而不考虑基线时存在的诸多差异。此外,对所有患者一律给予30 cc/kg的静脉输液被认为对某些患者直接有害。先前脓毒症试验中的患者个体异质性被认为是所有这些问题的一个重要因素,但此前没有研究试图确定基于容量信息的脓毒症表型,而这是迈向精准治疗的必要第一步。
基于先前证明器官水平充血可检测性的研究,我们假设中心静脉高压(1)对肺、肝、肾和血管内皮功能有害;(2)因心脏功能障碍和静脉输液而加重;(3)导致器官特异性和总体不良结局。从急诊科开始,将通过超声心动图评估心脏功能,同时使用先前验证的充血超声标志物评估肺和肾的充血情况。将同时收集每个器官的生物标志物,从而通过将宏观和微观应激及功能障碍指标配对来提高我们表型特征的准确性。还将在就诊后24小时和7天(或出院,以先到者为准)收集数据。将使用经典和机器学习方法分析我们的大数据流,并开发一个基于规则的系统,以识别脓毒症患者中具有器官特异性和总体不良结局更高风险/可能性的不同亚组。
本项目已获得韦恩州立大学机构审查委员会的批准,患者招募于2024年4月开始。研究结果将通过会议报告和开放获取出版物进行报告和传播。