Bachler Mirjam, Hell Tobias, Schausberger Lukas, Schlömmer Christine, Schäfer Volker, Liebensteiner Marlies, Schäffler Katharina, Schenk Bettina, Fries Dietmar, Innerhofer Petra, Niederwanger Christian
University for Health Sciences, Medical Informatics and Technology, Institute for Sports Medicine, Alpine Medicine and Health Tourism, Hall, Austria.
Department of Mathematics, Faculty of Mathematics, Computer Science and Physics, University of Innsbruck, Innsbruck, Austria.
PeerJ. 2019 Jun 21;7:e7147. doi: 10.7717/peerj.7147. eCollection 2019.
Sepsis is characterized by a pro-inflammatory and pro-coagulatory shift which can induce life-threatening complications. Close monitoring and risk stratification of sepsis patients is crucial for proper treatment and consequently patient outcome. Therefore, this study focuses on the response patterns of inflammatory and coagulatory parameters used in clinical routines to estimate the course of sepsis.
A total of 1,110 patients diagnosed with sepsis were retrospectively analyzed to identify response patterns for risk stratification of routine parameters measured at the peak level of C-reactive protein. Cluster analysis was used and the differences in the patient characteristics and 28-day survival were assessed. Cox proportional hazards regression model for survival stratified by the clusters was performed.
The analyses revealed the parameters to have five distinct response patterns. These clusters reflect the etiology as well as the course of sepsis associated with different mortalities. Here, impairment of the liver plays a crucial role in the ability to appropriately respond to sepsis. Of the routinely measured parameters, C-reactive protein and antithrombin seem to be unspecific for stratification of septic patients. Adjusted for the individual clusters, survival was associated with an increase in fibrinogen ( = 0.0042), platelets ( = 0.0003) and PT ( = 0.001) as well as a decrease in leukocytes ( = 0.034).
This study reveals that patients have distinct response patterns of inflammatory and coagulatory parameters depending on disease etiology. These patterns are associated with different mortalities although the patients have similar levels of C-reactive protein. Independently of the type of response, good coagulatory capacity seems to be crucial for patient survival.
脓毒症的特征是促炎和促凝转变，可引发危及生命的并发症。对脓毒症患者进行密切监测和风险分层对于恰当治疗及患者预后至关重要。因此，本研究聚焦于临床常规使用的炎症和凝血参数的反应模式，以评估脓毒症的病程。
对总共1110例诊断为脓毒症的患者进行回顾性分析，以确定在C反应蛋白峰值水平测量的常规参数用于风险分层的反应模式。采用聚类分析，并评估患者特征和28天生存率的差异。对按聚类分层的生存情况进行Cox比例风险回归模型分析。
分析显示这些参数有五种不同的反应模式。这些聚类反映了病因以及与不同死亡率相关的脓毒症病程。在此，肝脏功能损害在对脓毒症做出适当反应的能力中起关键作用。在常规测量的参数中，C反应蛋白和抗凝血酶似乎对脓毒症患者分层不具有特异性。根据各个聚类进行调整后，生存率与纤维蛋白原增加（P = 0.0042）、血小板增加（P = 0.0003）和凝血酶原时间增加（P = 0.001）以及白细胞减少（P = 0.034）相关。
本研究表明，根据疾病病因，患者的炎症和凝血参数有不同的反应模式。尽管患者的C反应蛋白水平相似，但这些模式与不同的死亡率相关。无论反应类型如何，良好的凝血能力似乎对患者生存至关重要。
