The efficacy of azvudine in treating hospitalized COVID-19 patients: a retrospective single-center cohort analysis

Introduction

Azvudine, identified as an inhibitor of the human immunodeficiency virus (HIV) reverse transcriptase, demonstrated its potential to inhibit or halt the replication of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) as early as February 2020 (1). Recognizing its potential ability against coronavirus disease 2019 (COVID-19), the National Medical Products Administration (NMPA) approved phase III clinical trials in April 2020. A randomized, open-label, controlled study on the use of azvudine in treating COVID-19 indicated that it could accelerate the conversion of nucleic acid in mild to moderate Chinese COVID-19 patients, and shorten the time of nucleic acid turning negative (2). A randomized single-arm trial among Chinese individuals revealed that oral azvudine at a dosage of 5 mg once daily achieved a 100% cure rate for COVID-19, with a hospital stay of 9.00±4.93 days and negative viral nucleic acid transition time of 3.29±2.22 days (3). In Phase III, a randomized, double-blind, placebo-controlled trial conducted in Brazil, involving 91 patients with moderate COVID-19, the azvudine group exhibited significant benefits, including reduced hospitalization duration, expedited viral transition to negative, and decreased viral load (4). These trials collectively exhibited the efficacy of azvudine in COVID-19 treatment. Consequently, on July 25, 2022, the NMPA provisionally approved azvudine tablets by Henan True Biotechnology Co., Ltd. (China) for the additional indication of COVID-19 treatment. Following this, azvudine was endorsed as an anti-COVID-19 drug in the Diagnosis and Treatment Plan for Novel Coronavirus Pneumonia (Trial Version 10). The medication has been extensively utilized during specific pandemic surges, with an increasing number of clinical trials and real-world studies emerging on its efficacy and safety. This retrospective cohort study seeks to evaluate the efficacy of azvudine in treating hospitalized COVID-19 patients at Lishui Central Hospital, a major primary care facility in eastern China. We present this article in accordance with the STROBE reporting checklist (available at https://jtd.amegroups.com/article/view/10.21037/jtd-2025-486/rc).

Methods

Study design and patients

This single-center, retrospective cohort study was conducted at Lishui Central Hospital, focusing on hospitalized patients diagnosed with COVID-19 from December 2022 to October 2023. It was registered with the Chinese Clinical Trial Registry under the identifier ChiCTR2000030391. This study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The study was approved by the ethics board of Lishui Central Hospital (No. 2020-5). As this was a retrospective cohort study involving anonymized data without patient intervention, the ethics board waived the requirement for informed consent.

Inclusion criteria

Hospitalized patients who met the following criteria were included in this study: (I) hospitalized patients with a positive result of SARS-CoV-2 through reverse transcription-polymerase chain reaction (RT-PCR) or a clinical diagnosis of COVID-19; (II) hospitalized COVID-19 patients who were treated with azvudine as an antiviral therapy or received only the standard of care (SOC) therapy. SOC therapy should follow the Diagnosis and Treatment Protocol for Novel Coronavirus Pneumonia (Trial Version 9).

Exclusion criteria

Hospitalized COVID-19 patients were excluded from this study if they: (I) were under 18 years of age; (II) had been administered antiviral medications other than azvudine during their hospital stay; (III) prior to the diagnosis of COVID-19, had already received mechanical ventilation support, including non-invasive ventilation and endotracheal intubation.

The patient selection process is shown in Figure 1.

Figure 1 Enrollment process of hospitalized COVID-19 patients. COVID-19, coronavirus disease 2019.

Data source

The data on hospitalized COVID-19 patients was collected from the inpatient system of electronic medical records (EMRs). The EMRs information, such as demographic characteristics, clinical categories of COVID-19, date of admission, basic disease, time from symptom onset to hospitalization, prescription and drug dispensing records, co-medications, COVID-19 vaccination status, date of receiving ventilator-assisted ventilation, intensive care unit (ICU) admission, date of discharge and the date of death were collected. Patients’ basic diseases, like diabetes mellitus, hypertension, chronic lung diseases, chronic liver diseases, chronic kidney diseases, and cancer were gathered. Moreover, we assessed the influence of co-medications, such as systemic corticosteroids, immunomodulators, and antibiotics.

Treatment exposure

To better compare the outcome event impact of treatment exposure, we set a 38-day observation period, consistent with the methodology used by Sun et al. (5). The starting point is the time when the patient was diagnosed with COVID-19 after admission. We defined the treatment exposure period as the first 2 days after the diagnosis of COVID-19, in order to reduce the potential immortal time deviation between the start of treatment and the diagnosis of COVID-19.

Azvudine group: hospitalized COVID-19 patients who received SOC during their hospital stay were treated with azvudine at a dosage of 5 mg once daily via oral and a maximum treatment period of 14 days during the 38-day observation period.

Control group: hospitalized COVID-19 patients were treated with SOC, which excluded the use of azvudine and other antiviral medications throughout the 38-day observation period.

Outcomes

During the 38 days under observation for COVID-19 treatment, outcomes included all-cause death, ICU admission, and receiving ventilator-assisted ventilation (noninvasive ventilation or tracheal intubation). We collected specific dates of admission and occurrence of outcome events, then analyzed the rate of composite outcome of disease progression, all-cause mortality, incidence of ICU admission, and the rate of receiving ventilator-assisted ventilation. Patients had any of these outcome events during the 38-day observation period, it was recorded as one composite outcome of disease progression. If a patient experiences two or three of the outcomes, it is still counted as one composite outcome of disease progression. The occurrence time of the composite outcome is recorded as the time of the first-occurring outcome. The discharge status of all patients was censored. For those discharged as cured or improved, we recorded whether the outcome event occurred. Patients discharged without recovery were followed up by phone to track outcome measures. There were no lost-to-follow-up cases in this study.

Baseline covariates

The baseline covariates of hospitalized COVID-19 patients include gender, age, time of COVID-19 symptoms onset to hospital admission (0–5 days or over 5 days), COVID-19 vaccination status (with or without vaccination), severity of COVID-19 at admission (severe or non-severe), and concomitant drug treatment status (with or without systemic steroid, immunomodulators, and antibiotics). The selection of covariates was based on an existing similar study (5) and their clinical relevance to COVID-19, azvudine intervention and treatment outcomes. Patients were categorized as having severe cases if they exhibited any of the following criteria attributed to COVID-19: a respiratory rate of 30 breaths or more per minute, oxygen saturation at or below 93%, a PaO₂/FiO₂ (partial pressure of arterial oxygen/fraction of inspired oxygen) ratio of 300 mmHg or less, or lung infiltrates exceeding 50%, etc.

Statistical analysis

Data compilation and summarization were carried out using Microsoft Excel, while statistical analysis was conducted with SPSS software version 25.0 (IBM Corporation, Armonk, NY, USA). Each data set was subjected to the Shapiro-Wilk test for normality assessment. Quantitative data that followed a normal distribution were described using the mean with standard deviation, and these were analyzed using a two-sample t-test. In cases where data were not normally distributed, the median with interquartile range (P25–P75) was reported, and a two-sample rank sum test was applied. Categorical data were expressed as frequencies (with percentages), and comparisons between groups were made using the chi-square test or Fisher’s exact test, considering a significance level of α=0.05 and P<0.05 as indicative of statistical significance.

To determine the correlation between azvudine treatment and outcomes in hospitalized COVID-19 patients, we employed propensity score matching (PSM). We calculated the propensity scores for baseline covariates such as gender, age, time of COVID-19 symptoms onset to hospital admission, COVID-19 vaccination status, severity of COVID-19 at admission, and concomitant drug treatment status. Then, we performed 1:1 nearest-neighbor matching with a 0.25 caliper using propensity scores. The common support region of propensity scores and standardized mean differences (SMD) were used to assess covariate distribution similarity between azvudine and control groups in the matched samples. After PSM, the data balance is good, SMD value of baseline covariates were less than 0.1 and a high degree of overlap between the two groups according to the probability density distribution chart (Figure 2, Figure S1).

Figure 2 Standard mean differences between the groups before and after PSM. COVID-19, coronavirus disease 2019; PSM, propensity score matching.

Consider death event competes with ICU admission and receiving ventilator-assisted ventilation, a competing risk analysis was performed. We utilized a single-variable Cox regression model to estimate the hazard ratio (HR) along with its 95% confidence interval (CI) for each outcome when comparing the two groups and for subgroup analyses. For better clinical interpretability of outcomes, we reported the absolute risk reduction (ARR) with its 95% confidence interval (CI). When the observed effects were significant, we also calculated the number needed to treat (NNT) along with its 95% CI. The statistical analysis was performed using R software version 4.3.0.

Results

Patient characteristics

A total of 939 hospitalized COVID-19 patients were admitted to Lishui Central Hospital from December 2022 to October 2023, as shown in Figure 1. After applying the exclusion criteria, 697 patients were eligible for analysis, with 567 in the azvudine group and 130 in the control group. Following PSM, 130 patients from the azvudine group were matched with 130 patients from the control group. Table S1 details the baseline characteristics of the two groups. Before PSM, there were notable disparities in selected covariates of age, severity of COVID-19 at admission, COVID-19 vaccination status, and concomitant drug treatment status between the two groups as shown in Table 1. After PSM, the two groups were well-matched (Table 1), with SMD for all characteristics below 0.1 and a high degree of overlap in probability density distribution as shown in Figure 2 and Figure S1.

Clinical outcomes of PSM cohort

Cox regression analysis was utilized to examine the differences in clinical outcomes, including the composite outcome of disease progression, all-cause mortality, ICU admission, and receiving ventilator-assisted ventilation between the two groups. In a competing risk analysis, it showed that there is no significant impact of competitive risks between the death and ICU admission (P=0.055), death and receiving ventilator-assisted ventilation (P>0.99) on the core results. From Table 2, it can be observed that in the final analysis of 260 hospitalized patients with COVID-19, 13 patients had complex disease progression events during the 38-day observation period. One case in the azvudine group (0.77%), twelve cases in the control group (9.23%). There was a statistically significant difference in comparison between azvudine group and the control group (P=0.02). Azvudine was linked to a lower combined risk of disease progression (HR: 0.08, 95% CI: 0.01 to 0.62). It reduced the risk of composite outcome of disease progression (ARR: 0.08, 95% CI: 0.02 to 0.15; NNT: 12, 95% CI: 7 to 50). The treatment with azvudine notably reduced the cumulative incidence rates of composite outcome of disease progression, as shown in Figure 3A. There were 8 cases of all-cause death events, with one case in the azvudine group (0.77%) and seven cases in the control group (5.38%). Kaplan-Meier analysis showed that hospitalized COVID-19 patients treated with azvudine had a low all-cause death risk compared to control group (P=0.03, log-rank test) (Figure 3B). But after Cox regression adjusted for confounding factors, the difference wasn’t significant (P=0.07), with a hazard ratio of 0.14 (95% CI: 0.02 to 1.13) and ARR is 0.05 (95% CI: −0.01 to 0.10). A total of 8 cases required ICU admission, with one case in the azvudine group (0.77%) and seven cases in the control group (5.38%). There was also no statistically significant difference between the two groups (P=0.07) with a hazard ratio of 0.14 (95% CI: 0.02 to 1.13) and ARR is 0.05 (95% CI: −0.01 to 0.10). A total of 9 cases required ventilator-assisted ventilation, with one case in the azvudine group (incidence rate of 0.77%) and eight cases in the control group (incidence rate of 6.15%). There was a statistically significant difference between the two groups (P=0.047). Azvudine can reduce the risk of hospitalized COVID-19 patients’ ventilator-assisted ventilation needs, with a hazard ratio of 0.12 (95% CI: 0.02 to 0.97) and ARR is 0.05 (95% CI: −0.002 to 0.11). These results indicated that azvudine had therapeutic advantages for hospitalized COVID-19 patients, lowering the risk of experiencing composite disease progressions events and the need for receiving ventilator-assisted ventilation. Subgroup analyses of four outcomes, including composite outcome of disease progression, all-cause mortality, ICU admission, and receiving ventilator-assisted ventilation, showed generally robust results (Tables S2-S5). In vaccinated patients, statistically significant differences were found in outcomes of composite outcome of disease progression and ventilator-assisted ventilation needs. The azvudine group had a lower risk of disease progression (HR: 0.12, 95% CI: 0.01 to 0.94, P=0.044) and a similarly lower risk of needing ventilator-assisted ventilation (HR: 0.12, 95% CI: 0.01 to 0.94, P=0.044) compared to the control group.

Figure 3 Kaplan-Meier curves of composite outcome of disease progression (A) and all-cause death (B) for hospitalized COVID-19 patients treated with azvudine and SOC. COVID-19, coronavirus disease 2019; SOC, standard of care.

Discussion

Our analysis of a real-world patient cohort hospitalized with COVID-19 and administered azvudine showed that using azvudine improved patients’ clinical outcomes during the 38 days under observation. Azvudine therapy was notably linked to a composite endpoint that included reduced disease progression, and ventilator-assisted ventilation treatment requirements. Sun et al. performed a retrospective analysis of the efficacy of azvudine in COVID-19 patients who were treated with oral azvudine (5). The results of composite outcomes of disease progression were similar to this study. However, the research of Sun et al. did not find a significant correlation with azvudine administration to ventilator-assisted ventilation treatment requirements. A recent multicenter retrospective study from 9 hospitals in Henan Province, China, demonstrated that azvudine treatment offers significant survival and progression-free benefits (6). Additionally, two recent meta-analysis also showed that compared to SOC/placebo, azvudine is effective in promoting clinical improvement and accelerating PT-PCR negativity compared to standard care or placebo (7). When matched against nirmatrelvir/ritonavir, it lowered the risk of ICU admission (OR: 0.42, 95% CI: 0.23 to 0.75) and mechanical ventilation need (OR: 0.61, 95% CI: 0.44 to 0.86) (8). These results supporting our findings that azvudine is beneficial for the treatment of COVID-19.

Due to the high transmissibility and high mortality rate of COVID-19, it has resulted in the deaths of over 6 million people. Following the clinical application of azvudine, extensive research has been conducted to determine whether it can reduce the mortality rate of patients with COVID-19. In one retrospective cohort research conducted by Zong et al. (9), it was found that azvudine not only significantly reduced the overall hospital mortality rate in the population (11% vs. 24%, P<0.001), but also decreased the hospital mortality rates in the severe subgroup (10% vs. 32%, P<0.001) and critical subgroup (5% vs. 34%, P<0.02). A retrospective cohort study on 5 hospitals in Chongqing, China conducted by Liu et al., regarding the association between the administration of azvudine to COVID-19 patients and mortality rate. The results showed that COVID-19 patients’ treatment with azvudine significantly reduced mortality rate in the 28-day follow-up period (OR: 0.472, 95% CI: 0.312 to 0.714, P<0.001) (10). The result of a meta-analysis of 17 clinical studies also indicates that azvudine can reduce the mortality risk for all patients. Compared with COVID-19 patients who received a placebo or no antiviral therapy, azvudine treatment can reduce the death risk (11). The results of the above clinical studies and the Kaplan-Meier analysis of all-cause death of this study were similar. Azvudine has beneficial effects on COVID-19 patients with all-cause death outcome event.

Azvudine administration was linked to markedly reduced mortality of COVID-19 patients during the observation period, which may be related to its acceleration of virus clearance and alleviation of disease progression. Several clinical trial results of Phase III suggested that azvudine shortened the time for viral clearance and duration of hospitalization, and reduced viral load in moderate COVID-19 patients (2,4). In older, mild-to-moderate COVID-19 patients, azvudine treatment showed promising efficacy and acceptable safety (6,12). Other studies have shown that azvudine can improve lung function in mild and common COVID-19 patients, maintain their vital signs, shorten treatment time, and accelerate virus clearance (2,13). The symptoms of mild and common COVID-19 patients were relatively mild. Azvudine effectively controls the progression of the disease by inhibiting virus replication and reducing the damage to the body, resulting in significant improvement in clinical outcomes.

Nirmatrelvir/ritonavir is globally recognized as one of the most widely used drugs for COVID-19 infection therapy. In recent years, there have been multiple retrospective studies comparing and analyzing the efficacy and safety of azvudine and nirmatrelvir/ritonavir in Chinese COVID-19 patients in the real world. Azvudine treatment has shown similar safety to nirmatrelvir/ritonavir in hospitalized COVID-19 patients, with comparable or slightly better clinical benefits, although not as effective as nirmatrelvir/ritonavir in some secondary outcome measures (14-16). A recent multicenter retrospective study compared azvudine and nirmatrelvir/ritonavir in COVID-19 patients. It showed that azvudine was associated with an 18% lower risk of all-cause mortality than nirmatrelvir/ritonavir (95% CI: 0.676 to 0.987), but was not significantly different in terms of composite disease progression (17). In cancer patients with COVID-19, azvudine not only significantly lowers all-cause mortality risk but also reduced composite disease progression more effectively than nirmatrelvir/ritonavir (18). In patients with COVID-19 and diabetes, azvudine was associated with a lower risk of all-cause death than nirmatrelvir/ritonavir (log-rank P=0.044, HR: 0.63, 95% CI: 0.431 to 0.934) (19). Regarding drug safety, nirmatrelvir/ritonavir had a significantly higher rate of myocardial injury (13.5%) than azvudine (7.3%) (P=0.01). No significant difference was found in the occurrence of other adverse events between the two drugs (20). Based on these studies, it can be concluded that azvudine has similar efficacy and better safety compared to nirmatrelvir/ritonavir.

Since the vaccine’s efficacy against SARS-CoV-2 was recognized, vaccination is considered a strategy to swiftly deploy to decrease the incidence of serious illness and death (21,22). In our study, 54 patients were unvaccinated (accounting for 20.77%). Among those treated with azvudine, 30.69% were unvaccinated, and the rate of unvaccinated participants was higher than the control group (21.54%). To avoid potential confounding interference caused by vaccination, we used the nearest neighbor matching method to reduce data bias. According to the subgroup analyses, hospitalized COVID-19 patients who have received vaccinations markedly reduced the risk of composite disease progression events and ventilator-assisted ventilation needs after receiving azvudine treatment. This could be attributed to the vaccinated individuals’ quicker recognition of SARS-CoV-2. After azvudine is taken orally, it accumulates in the thymus in its active form, efficiently inhibiting the virus’s replication within the body and safeguarding the thymus’s immune capabilities. The two actions of rapid identification and inhibited replication of COVID-19 virus work together to provide strong protection for hospitalized COVID-19 patients.

Even though this study collected continuous data on all hospitalized COVID-19 patients, adjusted for related confounding interference factors, and decreased potential selection bias, some limitations should be noted. Firstly, although adjustments were made to known confounding factors and the use of propensity score matching, as a retrospective observational study, it is impossible to exclude all potential confounding factors completely. Secondly, it is single-center research with a limited sample size and lacks data from various regions and ethnicities. The study’s findings are specific to the Lishui area, indicating a need for additional research on azvudine’s effectiveness across different regions and among different populations to make a large-sample assessment of its clinical benefits. Thirdly, the study did not consider how other medications might influence azvudine’s effectiveness. The impact of potential drug interactions on azvudine’s efficacy and safety remains unclear. Finally, since safety observation and adverse drug reactions (ADR) were not evaluated, our knowledge of the drug remains incomplete. Given with above limitations, further investigation is required to better assess azvudine’s performance, such as clinical trials with multi-center, large samples, long-term follow-up, and real-world studies.

Conclusions

In this study, we found that azvudine can significantly reduce the composite outcome of hospitalized COVID-19 patients and those requiring ventilator assistance within a 38-day observation period. These results suggest that azvudine provides strong protection for COVID-19 patients and can be considered for treating the disease.

Acknowledgments

None.

Footnote

Reporting Checklist: The authors have completed the STROBE reporting checklist. Available at https://jtd.amegroups.com/article/view/10.21037/jtd-2025-486/rc

Data Sharing Statement: Available at https://jtd.amegroups.com/article/view/10.21037/jtd-2025-486/dss

Peer Review File: Available at https://jtd.amegroups.com/article/view/10.21037/jtd-2025-486/prf

Funding: This work was supported by the Zhejiang Provincial Natural Science Foundation of China (No. LBY22H280006) and Lishui Science and Technology Bureau (No. 2022SJZC081).

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://jtd.amegroups.com/article/view/10.21037/jtd-2025-486/coif). All authors report funding from the Zhejiang Provincial Natural Science Foundation of China and the Lishui Science and Technology Bureau for this study. The authors have no other conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. This study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The study was approved by the ethics board of Lishui Central Hospital (No. 2020-5). As this was a retrospective cohort study involving anonymized data without patient intervention, the ethics board waived the requirement for informed consent.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

References

1. Wang YX, Ma K, Xia ZJ. New use of old medicine, Azvudine. China Licensed Pharmacist 2023;20:25-7.
2. Ren Z, Luo H, Yu Z, et al. A Randomized, Open-Label, Controlled Clinical Trial of Azvudine Tablets in the Treatment of Mild and Common COVID-19, a Pilot Study. Adv Sci (Weinh) 2020;7:e2001435. [Crossref] [PubMed]
3. Zhang JL, Li YH, Wang LL, et al. Azvudine is a thymus-homing anti-SARS-CoV-2 drug effective in treating COVID-19 patients. Signal Transduct Target Ther 2021;6:414. [Crossref] [PubMed]
4. de Souza SB, Cabral PGA, da Silva RM, et al. Phase III, randomized, double-blind, placebo-controlled clinical study: a study on the safety and clinical efficacy of AZVUDINE in moderate COVID-19 patients. Front Med (Lausanne) 2023;10:1215916. [Crossref] [PubMed]
5. Sun Y, Jin L, Dian Y, et al. Oral Azvudine for hospitalised patients with COVID-19 and pre-existing conditions: a retrospective cohort study. EClinicalMedicine 2023;59:101981. [Crossref] [PubMed]
6. Sun R, Wang H, Sun J, et al. Effectiveness and Safety of Oral Azvudine for Elderly Hospitalized Patients With COVID-19: A Multicenter, Retrospective, Real-World Study. Adv Sci (Weinh) 2025;12:e2404450. [Crossref] [PubMed]
7. Amani B, Amani B. Effectiveness and safety of azvudine in COVID-19: A systematic review and meta-analysis. PLoS One 2024;19:e0298772. [Crossref] [PubMed]
8. Amani B, Amani B. Azvudine versus Paxlovid in COVID-19: A systematic review and meta-analysis. Rev Med Virol 2024;34:e2551. [Crossref] [PubMed]
9. Zong K, Zhou H, Li W, et al. Azvudine reduces the in-hospital mortality of COVID-19 patients: A retrospective cohort study. Acta Pharm Sin B 2023;13:4655-60. [Crossref] [PubMed]
10. Liu B, Yang M, Xu L, et al. Azvudine and mortality in patients with coronavirus disease 2019: A retrospective cohort study. Int Immunopharmacol 2023;124:110824. [Crossref] [PubMed]
11. Wang Y, Xie H, Wang L, et al. Effectiveness of azvudine in reducing mortality of COVID-19 patients: a systematic review and meta-analysis. Virol J 2024;21:46. [Crossref] [PubMed]
12. Zhou Z, Zheng H, Xiao G, et al. Effectiveness and safety of azvudine in older adults with mild and moderate COVID-19: a retrospective observational study. BMC Infect Dis 2024;24:47. [Crossref] [PubMed]
13. da Silva RM, Gebe Abreu Cabral P, de Souza SB, et al. Serial viral load analysis by DDPCR to evaluate FNC efficacy and safety in the treatment of mild cases of COVID-19. Front Med (Lausanne) 2023;10:1143485. [Crossref] [PubMed]
14. Wei AH, Zeng L, Wang L, et al. Head-to-head comparison of azvudine and nirmatrelvir/ritonavir for the hospitalized patients with COVID-19: a real-world retrospective cohort study with propensity score matching. Front Pharmacol 2023;14:1274294. [Crossref] [PubMed]
15. Deng G, Li D, Sun Y, et al. Real-world effectiveness of Azvudine versus nirmatrelvir-ritonavir in hospitalized patients with COVID-19: A retrospective cohort study. J Med Virol 2023;95:e28756. [Crossref] [PubMed]
16. Zhao Q, Zheng B, Han B, et al. Is Azvudine Comparable to Nirmatrelvir-Ritonavir in Real-World Efficacy and Safety for Hospitalized Patients with COVID-19? A Retrospective Cohort Study. Infect Dis Ther 2023;12:2087-102. [Crossref] [PubMed]
17. Wang H, Cui G, Cheng M, et al. Real-world effectiveness and safety of oral azvudine versus nirmatrelvir‒ritonavir (Paxlovid) in hospitalized patients with COVID-19: a multicenter, retrospective, cohort study. Signal Transduct Target Ther 2025;10:30. [Crossref] [PubMed]
18. Yang J, Min J, Ding L, et al. Effectiveness and safety of azvudine versus nirmatrelvir/ritonavir in hospitalized patients with COVID-19. BMC Infect Dis 2025;25:701. [Crossref] [PubMed]
19. Su G, Li S, Zhang D, et al. Real-world effectiveness of azvudine versus nirmatrelvir-ritonavir in hospitalized patients with COVID-19 and pre-existing diabetes. iScience 2025;28:111907. [Crossref] [PubMed]
20. Jia B, Sun J, Zhu D, et al. Efficacy and safety of azvudine versus nirmatrelvir/ritonavir in cancer patients with COVID-19. Sci Rep 2025;15:11022. [Crossref] [PubMed]
21. Xia S, Duan K, Zhang Y, et al. Effect of an Inactivated Vaccine Against SARS-CoV-2 on Safety and Immunogenicity Outcomes: Interim Analysis of 2 Randomized Clinical Trials. JAMA 2020;324:951-60. [Crossref] [PubMed]
22. Xia S, Zhang Y, Wang Y, et al. Safety and immunogenicity of an inactivated SARS-CoV-2 vaccine, BBIBP-CorV: a randomised, double-blind, placebo-controlled, phase 1/2 trial. Lancet Infect Dis 2021;21:39-51. [Crossref] [PubMed]