Qin Yin1, Bo Liu, Yunxia Chen, Yunzhou Zhao, Chunsheng Li. 1. Emergency Department of Beijing Chaoyang Hospital, Capital Medical University, 8# Worker's Stadium South Road, Beijing, 100020, China.
Abstract
INTRODUCTION: Soluble thrombomodulin (sTM) is a sensitive marker of endothelial damage. In this study we investigated the role of sTM in the evaluation of the severity and prognosis of septic patients in the emergency department (ED). MATERIALS AND METHODS: A prospective, observational cohort study was performed in the ED of an urban, university hospital. Patients who had suspected infection with two or more criteria of systemic inflammatory response syndrome were consecutively enrolled. sTM, D-Dimer and procalcitonin levels were measured on enrollment, and the Mortality in Emergency Department Sepsis (MEDS) score was calculated. A 30-day follow-up was performed for all patients. RESULTS: A total of 372 patients with sepsis, 210 patients with severe sepsis and 98 patients with septic shock were enrolled in this study. According to the disease severity, patients were divided into sepsis subgroup and severe sepsis subgroup (including septic shock). In addition, patients were divided into survivors subgroup and non-survivors subgroup according to the 30-day mortality. Plasma sTM levels in patients with severe sepsis were higher than those with sepsis (P<0.001). Compared with survivors, non-survivors has higher plasma sTM levels (P<0.001). Multivariate logistic regression analysis showed that sTM was an independent predictor of severe sepsis (odds ratio 1.11) and 30-day mortality (odds ratio 1.059). Receiver operating characteristic curve analysis showed that sTM was a useful parameter in prediction of severe sepsis (0.859) and 30-day mortality (0.78). Compared with the MEDS score alone, combination of sTM and the MEDS score can improve the accuracy in prediction of severe sepsis and 30-day mortality. CONCLUSIONS: sTM is a valuable biomarker in the risk stratification and prognosis evaluation of ED sepsis. Furthermore, sTM can enhance the ability of the MEDS score in prediction of severe sepsis and 30-day mortality.
INTRODUCTION: Soluble thrombomodulin (sTM) is a sensitive marker of endothelial damage. In this study we investigated the role of sTM in the evaluation of the severity and prognosis of septic patients in the emergency department (ED). MATERIALS AND METHODS: A prospective, observational cohort study was performed in the ED of an urban, university hospital. Patients who had suspected infection with two or more criteria of systemic inflammatory response syndrome were consecutively enrolled. sTM, D-Dimer and procalcitonin levels were measured on enrollment, and the Mortality in Emergency Department Sepsis (MEDS) score was calculated. A 30-day follow-up was performed for all patients. RESULTS: A total of 372 patients with sepsis, 210 patients with severe sepsis and 98 patients with septic shock were enrolled in this study. According to the disease severity, patients were divided into sepsis subgroup and severe sepsis subgroup (including septic shock). In addition, patients were divided into survivors subgroup and non-survivors subgroup according to the 30-day mortality. Plasma sTM levels in patients with severe sepsis were higher than those with sepsis (P<0.001). Compared with survivors, non-survivors has higher plasma sTM levels (P<0.001). Multivariate logistic regression analysis showed that sTM was an independent predictor of severe sepsis (odds ratio 1.11) and 30-day mortality (odds ratio 1.059). Receiver operating characteristic curve analysis showed that sTM was a useful parameter in prediction of severe sepsis (0.859) and 30-day mortality (0.78). Compared with the MEDS score alone, combination of sTM and the MEDS score can improve the accuracy in prediction of severe sepsis and 30-day mortality. CONCLUSIONS: sTM is a valuable biomarker in the risk stratification and prognosis evaluation of ED sepsis. Furthermore, sTM can enhance the ability of the MEDS score in prediction of severe sepsis and 30-day mortality.
Authors: Yan-Qiu Han; Li Yan; Lei Zhang; Pei-Heng Ouyang; Peng Li; Giuseppe Lippi; Zhi-De Hu Journal: Biochem Med (Zagreb) Date: 2021-06-15 Impact factor: 2.313
Authors: Kirby Tong-Minh; Iris Welten; Henrik Endeman; Tjebbe Hagenaars; Christian Ramakers; Diederik Gommers; Eric van Gorp; Yuri van der Does Journal: BMC Emerg Med Date: 2021-06-13