中国药物警戒 ›› 2021, Vol. 18 ›› Issue (10): 905-909.
DOI: 10.19803/j.1672-8629.2021.10.02

• 新型冠状病毒肺炎药物治疗研究专栏 • 上一篇    下一篇

静注新型冠状病毒肺炎人免疫球蛋白（pH4）治疗新型冠状病毒肺炎的疗效观察

宋美华, 张婷玉, 葛子若, 徐艳利, 陈志海*, 钱芳#   

  1. 首都医科大学附属北京地坛医院感染中心,北京 100015
  • 收稿日期:2021-06-07 出版日期:2021-10-15 发布日期:2021-10-27
  • 通讯作者: *陈志海,男,硕士,主任医师,感染性疾病。E-mail：chenzhihai0001@126.com。#为共同通信作者。
  • 作者简介:宋美华,女,硕士,主治医师,感染性疾病和突发新发传染性疾病。
  • 基金资助:
    国家重点研发计划（2020YFC0848300）

Efficacy of Human COVID-19 Immunoglobulin (pH4) for Intravenous Injection against COVID-19

SONG Meihua, ZHANG Tingyu, GE Ziruo, XU Yanli, CHEN Zhihai*, QIAN Fang#   

  1. Center of Infection Diseases, Beijing Ditan Hospital, Capital Medical University, Beijing 100015, China
  • Received:2021-06-07 Online:2021-10-15 Published:2021-10-27

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摘要： 目的 使用倾向性评分匹配法（propensity score matching, PSM）获得研究队列,探讨静注新型冠状病毒肺炎（coronavirus disease 2019, COVID-19）人免疫球蛋白（pH4）（human COVID-19 immunoglobulin（pH4）for intravenous injection, hCoVIgG）治疗普通型COVID-19的安全性和有效性。方法 回顾性调查2020年1月20日至2021年1月31日于北京地坛医院住院诊治的COVID-19患者525例,其中接受hCoVIgG（pH4）治疗的10例,未接受hCoVIgG（pH4）治疗的515例。根据年龄、性别、临床分型、是否合并基础病以及入院时C反应蛋白水平,对两组患者进行倾向性得分匹配。比较匹配后两组患者的人口学特征、临床表现、实验室检查等指标,并分析两组患者的核酸转阴时间、影像学炎症吸收时间、临床改善时间。同时应用人工智能辅助肺部CT分析肺部炎症情况。探究hCoVIgG（pH4）治疗普通型COVID-19患者的疗效。结果 匹配后得到9例hCoVIgG （pH4）治疗组及9例对照组。与对照组相比,hCoVIgG（pH4）治疗组患者核酸转阴时间（P=0.007）、影像学炎症吸收时间（P=0.001）均有显著缩短。C反应蛋白下降明显（P=0.03）。结论 hCoVIgG（pH4）治疗可帮助机体清除病毒,促进肺部炎症吸收。

关键词: 新型冠状病毒, 新型冠状病毒肺炎, 人免疫球蛋白（pH4）, 人工智能, 倾向性评分匹配

Abstract: Objective To investigate the safety and efficacy of human COVID-19 immunoglobulin (pH4) (hCoVIgG pH4) for intravenous injection in the treatment of common COVID-19 by obtaining the study cohort using the propensity score matching method. Methods A retrospective study was conducted of 525 patients with COVID-19 who were hospitalized in Beijing Ditan Hospital between January 2020 and January 2021. These patients were divided into two groups: the treatment group (n=10) and control group (n=515). The propensity scores of the two groups were matched according to age, gender, clinical classification, complications and the level of C-reactive protein at admission. After matching, the demographic characteristics, clinical manifestations, laboratory examination results and other indexes were compared between the two groups, while the nucleic acid negative conversion time, imaging inflammatory absorption time and clinical improvement time of the two groups were analyzed. At the same time, artificial intelligence was used to assist pulmonary CT in analyzing pulmonary inflammation. Results Nine cases were obtained from the treatment group and from the control group respectively after matching. Compared with the control group, the nucleic acid negative conversion time and imaging inflammatory absorption time in the treatment group were significantly shortened. C-reactive protein decreased significantly (P<0.05). Conclusion hCoVIgG can help the body to clear the virus and promote the absorption of pulmonary inflammation.

Key words: SARS-CoV-2, COVID-19, immunoglobulin（pH4）, artificial intelligence, propensity score matching

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