ArticleiScience2025
Real-world effectiveness of azvudine versus nirmatrelvir-ritonavir in hospitalized patients with COVID-19 and pre-existing diabetes.
Article in iScience, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
3 citing papers in PubMed.
- Effectiveness of nirmatrelvir/ritonavir and molnupiravir on post-COVID diabetes risk among an older adult cohort: a target trial emulation study.BMC medicine · 2026Article
- Evaluating the effectiveness and safety of Azvudine for hospitalised patients with COVID-19 and hypertension: a multicenter retrospective cohort study.Scientific reports · 2026Article
- The efficacy of azvudine in treating hospitalized COVID-19 patients: a retrospective single-center cohort analysis.Journal of thoracic disease · 2025Article
Corrections and comments
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Authors and funding
19 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Azvudine and nirmatrelvir-ritonavir are prioritized treatments for SARS-CoV-2 infection in China, but their effectiveness and safety in hospitalized patients with COVID-19 and pre-existing diabetes remains unknown. In this retrospective cohort study, we collected 32,864 hospitalized COVID-19 patients from nine hospitals, among which 636 azvudine recipients and 318 nirmatrelvir-ritonavir recipients were enrolled for final analysis after exclusion and propensity score matching. Kaplan-Meier and multivariate Cox regression analysis results showed that azvudine had a lower risk of all-cause death compared with nirmatrelvir-ritonavir for the treatment of patients with COVID-19 and pre-existing diabetes (log rank:
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.