Retrospective Evaluation of COVID-19 Therapeutics

Z. X, P. K, Z. R, Li F, Xiao C, Zhai S, L. C, H. Q., An L, Y. C
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Abstract

Background: The pandemic outbreak of COVID-19 created panic all over the world. As therapeutics that can effectively wipe out the virus and terminate transmission is not available, supportive therapeutics is the main clinical treatments for COVID-19. Repurposing available therapeutics from other viral infections is the primary surrogate in ameliorating and treating COVID-19. The therapeutics should be tailored individually by analyzing the severity of COVID-19, age, gender, and the underlying conditions. Here, we retrospectively revisit the clinical data collected in China and systematically analyze the efficacy and target patients of different therapeutics and find that Arbidol and Traditional Chinese Medicine (TCM) increase the survival rate significantly, whereas antibacterial treatment is ineffective for viral and bacterial co infection. Multicenter collaboration and large cohort of patients will be required to evaluate therapeutics combinations in the future. Methods: This study is a single-center retrospective observational study of COVID-19 clinical data in China. We screen 2844 COVID-19 patients from the patients admitted to Tongji Hospital (Wuhan) between January 18, 2020, and April 25, 2020 and exclude cases with missing information or false positive diagnosis. Then the patients’ information with different severity will be study to evaluate the efficacy of treatment, including treatment modalities, past medical records, individual disease history, and clinical outcomes were analyzed. As the severity of illness is correlated with laboratory or clinical data, the information can be used to evaluate disease severity. We divide the patients into three groups with moderate, severe, and critical illness. Kaplan-Meier method, univariate and multivariate Cox regression are used to explore different treatment methods on clinical outcomes. Results: After screening, 2844 patients are selected for the study. The mean age of all the patients was 58.74 years (Standard Deviation, SD =15.28), and 49.0% is male. It shows that treatment with TCM (Hazard Ratio (HR) 0.191 [95% Confidence Interval (CI), 0.14 – 0.25]; p < 0.0001), antiviral therapy (HR 0.331 [95% CI 0.19 – 0.58]; p =0.000128), or Arbidol (HR 0.454 [95% CI 0.34 – 0.60]; p < 0.0001) is associated with good prognostic of patients. Multivariate Cox regression showed TCM treatment decreased the mortality hazard ratio by 69.4% (p < 0.0001). Larger Mean Platelet Volume (MPV), international standardized ratio of prothrombin (PT-INR), and K+ are associated with poorer survival. In contrast, larger Eosinophil Count (Eos#), Basophil Count (Baso#), Percentage of Basophils (Baso%), Total Calcium (Ca), Albumin/Globulin Ratio (ALB/GLO), Lymphocyte Count (Lymph#), and Percentage of Eosinophils (Eos%) are associated with better survival.
COVID-19治疗方法的回顾性评价
背景:2019冠状病毒病(COVID-19)大流行疫情在全球引发恐慌。由于没有有效消灭病毒和终止传播的治疗方法,支持性治疗是COVID-19的主要临床治疗方法。重新利用其他病毒感染的现有治疗方法是改善和治疗COVID-19的主要替代方法。治疗方法应根据COVID-19的严重程度、年龄、性别和潜在条件进行个性化定制。在此,我们回顾了国内收集的临床资料,系统分析了不同治疗方法的疗效和目标患者,发现阿比多尔和中药(TCM)可显著提高生存率,而抗菌治疗对病毒和细菌合并感染无效。未来需要多中心合作和大队列患者来评估治疗组合。方法:本研究为中国新冠肺炎临床资料的单中心回顾性观察研究。我们从2020年1月18日至2020年4月25日在武汉同济医院住院的患者中筛选出2844例新冠肺炎患者,排除信息缺失或假阳性的病例。然后研究不同严重程度患者的信息,包括治疗方式、既往病历、个人病史和临床结局分析,以评估治疗效果。由于疾病的严重程度与实验室或临床数据相关,这些信息可用于评估疾病的严重程度。我们将患者分为中度、重度和危重三组。采用Kaplan-Meier法、单因素及多因素Cox回归探讨不同治疗方法对临床结局的影响。结果:经筛选,共入选2844例患者。所有患者的平均年龄为58.74岁(标准差,SD =15.28),男性占49.0%。结果显示,中药治疗(风险比0.191[95%可信区间(CI), 0.14 ~ 0.25];p < 0.0001),抗病毒治疗(HR 0.331 [95% CI 0.19 - 0.58];p =0.000128)或阿比多尔(HR 0.454 [95% CI 0.34 - 0.60];P < 0.0001)与患者预后良好相关。多因素Cox回归分析显示,中药治疗使死亡率风险比降低69.4% (p < 0.0001)。平均血小板体积(MPV)、国际标准化凝血酶原比(PT-INR)和K+与较差的生存率相关。相反,较大的嗜酸性粒细胞计数(Eos#)、嗜碱性粒细胞计数(Baso#)、嗜碱性粒细胞百分比(Baso%)、总钙(Ca)、白蛋白/球蛋白比(ALB/GLO)、淋巴细胞计数(Lymph#)和嗜酸性粒细胞百分比(Eos%)与较好的生存率相关。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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