Gao Yuan, Dong Yixi, Bu Qiushi, Gong Zhijie, Wang Wei, Zhou Zhongkai, Gao Yunyi, Liu Liwei, Wu Menghua, Zhang Jiaying, Liang Lianchun, Li Hongjun, Jiang Mengxi, Luo Zujin, Ma Yingmin, Zhang Xinyu, Hu Zhongjie
Fourth Department of Liver Disease Center, Beijing You'An Hospital, Capital Medical University, Beijing, China.
School of Management, University of Science and Technology of China, Hefei, China.
Influenza Other Respir Viruses. 2024 Sep;18(9):e70006. doi: 10.1111/irv.70006.
There is still a lack of clinical evidence comprehensively evaluating the effectiveness of antiviral treatments for COVID-19 hospitalized patients.
A retrospective cohort study was conducted at Beijing You'An Hospital, focusing on patients treated with nirmatrelvir/ritonavir or azvudine. The study employed a tripartite analysis-viral dynamics, survival curve analysis, and AI-based radiological analysis of pulmonary CT images-aiming to assess the severity of pneumonia.
Of 370 patients treated with either nirmatrelvir/ritonavir or azvudine as monotherapy, those in the nirmatrelvir/ritonavir group experienced faster viral clearance than those treated with azvudine (5.4 days vs. 8.4 days, p < 0.001). No significant differences were observed in the survival curves between the two drug groups. AI-based radiological analysis revealed that patients in the nirmatrelvir group had more severe pneumonia conditions (infection ratio is 11.1 vs. 5.35, p = 0.007). Patients with an infection ratio higher than 9.2 had nearly three times the mortality rate compared to those with an infection ratio lower than 9.2.
Our study suggests that in real-world studies regarding hospitalized patients with COVID-19 pneumonia, the antiviral effect of nirmatrelvir/ritonavir is significantly superior to azvudine, but the choice of antiviral agents is not necessarily linked to clinical outcomes; the severity of pneumonia at admission is the most important factor to determine prognosis. Additionally, our findings indicate that pulmonary AI imaging analysis can be a powerful tool for predicting patient prognosis and guiding clinical decision-making.
目前仍缺乏全面评估新冠病毒肺炎住院患者抗病毒治疗效果的临床证据。
在北京佑安医院开展一项回顾性队列研究，重点关注接受奈玛特韦/利托那韦或阿兹夫定治疗的患者。该研究采用了三方分析——病毒动力学分析、生存曲线分析以及基于人工智能的肺部CT图像放射学分析，旨在评估肺炎的严重程度。
在370例接受奈玛特韦/利托那韦或阿兹夫定单药治疗的患者中，奈玛特韦/利托那韦组患者的病毒清除速度比接受阿兹夫定治疗的患者更快（5.4天对8.4天，p<0.001）。两组药物治疗的生存曲线未观察到显著差异。基于人工智能的放射学分析显示，奈玛特韦组患者的肺炎病情更严重（感染率为11.1对5.35，p=0.007）。感染率高于9.2的患者死亡率是感染率低于9.2患者的近三倍。
我们的研究表明，在针对新冠病毒肺炎住院患者的真实世界研究中，奈玛特韦/利托那韦的抗病毒效果显著优于阿兹夫定，但抗病毒药物的选择不一定与临床结局相关；入院时肺炎的严重程度是决定预后的最重要因素。此外，我们的研究结果表明，肺部人工智能成像分析可以成为预测患者预后和指导临床决策的有力工具。
