• FluTrackers.com Inc. does not provide medical advice. Information on this web site is collected from various internet resources, and the FluTrackers board of directors makes no warranty to the safety, efficacy, correctness or completeness of the information posted on this site by any author or poster. The information collated here is for instructional and/or discussion purposes only and is NOT intended to diagnose or treat any disease, illness, or other medical condition. Every individual reader or poster should seek advice from their personal physician/healthcare practitioner before considering or using any interventions that are discussed on this website. By continuing to access this website you agree to consult your personal physican before using any interventions posted on this website, and you agree to hold harmless FluTrackers.com Inc., the board of directors, the members, and all authors and posters for any effects from use of any medication, supplement, vitamin or other substance, device, intervention, etc. mentioned in posts on this website, or other internet venues referenced in posts on this website.
  • We are not asking for any donations. Do not donate to any entity who says they are raising funds for us.

Influenza Other Respir Viruses . Antiviral Effectiveness, Clinical Outcomes, and Artificial Intelligence Imaging Analysis for Hospitalized COVID-19

tetano

Editor, Senior Moderator
Influenza Other Respir Viruses


. 2024 Sep;18(9):e70006.
doi: 10.1111/irv.70006. Antiviral Effectiveness, Clinical Outcomes, and Artificial Intelligence Imaging Analysis for Hospitalized COVID-19 Patients Receiving Antivirals

Yuan Gao[SUP] 1 [/SUP], Yixi Dong[SUP] 2 [/SUP], Qiushi Bu[SUP] 3 [/SUP], Zhijie Gong[SUP] 2 [/SUP], Wei Wang[SUP] 4 [/SUP], Zhongkai Zhou[SUP] 4 [/SUP], Yunyi Gao[SUP] 5 [/SUP], Liwei Liu[SUP] 1 [/SUP], Menghua Wu[SUP] 6 [/SUP], Jiaying Zhang[SUP] 7 [/SUP], Lianchun Liang[SUP] 7 [/SUP], Hongjun Li[SUP] 4 [/SUP], Mengxi Jiang[SUP] 8 [/SUP], Zujin Luo[SUP] 9 [/SUP], Yingmin Ma[SUP] 10 [/SUP], Xinyu Zhang[SUP] 2 3 [/SUP], Zhongjie Hu[SUP] 11 [/SUP]



Affiliations
Free article Abstract

Introduction: There is still a lack of clinical evidence comprehensively evaluating the effectiveness of antiviral treatments for COVID-19 hospitalized patients.
Methods: 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.
Results: 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.
Conclusions: 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.

Keywords: COVID‐19; antiviral; artificial intelligence image; viral dynamics.

 
Back
Top Bottom