印度尼西亚某三级医院重症与非重症COVID-19患者凝血指标比较

Pandji Irani Fianza, Delita Prihatni, Dasep Bambang Purnama
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引用次数: 0

摘要

目的:探讨重症与非重症COVID-19患者凝血功能的差异。方法:在2020年7月至2021年6月的研究期间,371例COVID-19患者在Dr. Hasan Sadikin医院接受治疗。根据WHO标准将这些患者分为两组:有严重急性呼吸综合征至呼吸衰竭等临床症状的重症病例和无呼吸道症状的非重症病例。分析的数据包括凝血酶原时间(PT)、活化部分凝血活酶时间(aPTT)、国际标准化比率(INR)、纤维蛋白原、d -二聚体和血小板计数。结果:重症患者的中位INR显著高于非重症患者(1.04 vs. 0.94, p= 0.001),中位PT (12.3 vs. 12.0秒,p=0.030)和中位纤维蛋白原(522 vs. 428.5 mg/dl, p=0.004)也是如此。同样,重症患者d -二聚体的中位数也显著升高(1.91 vs. 0.75 mg/dl, p<0.001)。重症和非重症COVID-19患者aPTT和血小板计数中位数均在正常范围内(分别为28.6 vs 29.15 sec, p>0.652和246 vs 242 x103/mm3, p>0.924)。结论:INR、PT、纤维蛋白原和d -二聚体可作为预测COVID-19患者病情严重程度和选择适当治疗的特征。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Comparison of Coagulation Parameters between Severe and Non-severe COVID-19 Patients Treated in a Tertiary Hospital in Indonesia
Objective: To determine the differences in coagulation features in patients with severe versus non-severe COVID-19. Method: During the period of the study from July 2020 to June 2021, 371 COVID-19 patients were treated at Dr. Hasan Sadikin Hospital. These patients were divided into two groups based on the WHO critera into severe COVID-19 with clinical signs such as severe acute respiratory syndrome to respiratory failure and non-severe cases with no respiratory symptoms. Data analyzed were Prothrombin Time (PT), Activated Partial Thromboplastin Time (aPTT), International Normalized Ratio (INR), fibrinogen, D-dimer, and platelet count.Results: Median INR was significantly higher in patients with severe cases than in non-severe cases (1.04 vs. 0.94, p<0.001), which was also true for median PT (12.3 vs. 12.0 sec, p=0.030) and median fibrinogen (522 vs. 428.5 mg/dl, p=0.004). Similarly, the median D-dimer was significantly higher in severe patients (1.91 vs. 0.75 mg/dl, p<0.001). Median aPTT and platelet count were in normal limits for both severe and non-severe COVID-19 patients (28.6 vs. 29.15 sec, p>0.652 and 246 vs. 242 x103/mm3, p>0.924, respectively).Conclusions: The INR, PT, fibrinogen, and D-dimer can be considered as features that can be used to predict the severity of the disease and to choose the proper treatment for COVID-19 patients.
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