Ursodeoxycholic acid and COVID-19 outcomes: a cohort study and data synthesis of state-of-art evidence
Yang Yu, Guo-Fu Li, Jian Li, Lu-Yao Han, Zhi-Long Zhang, Tian-Shuo Liu, Shu-Xin Jiao, Yu-Wei Qiao, Na Zhang, De-Chuan Zhan, Shao-Qiu Tang, Guo Yu
Expert Review of Anti-infective Therapy, doi:10.1080/14787210.2024.2376153
Background: The potential of ursodeoxycholic acid (UDCA) in inhibiting angiotensin-converting enzyme 2 was demonstrated. However, conflicting evidence emerged regarding the association between UDCA and COVID-19 outcomes, prompting the need for a comprehensive investigation. Research design and methods: Patients diagnosed with COVID-19 infection were retrospectively analyzed and divided into two groups: the UDCA-treated group and the control group. Kaplan-Meier recovery analysis and Cox proportional hazards models were used to evaluate the recovery time and hazard ratios. Additionally, study-level pooled analyses for multiple clinical outcomes were performed. Results: In the 115-patient cohort, UDCA treatment was significantly associated with a reduced recovery time. The subgroup analysis suggests that the 300 mg subgroup had a significant (adjusted hazard ratio: 1.63 [95% CI, 1.01 to 2.60]) benefit with a shorter duration of fever. The results of pooled analyses also show that UDCA treatment can significantly reduce the incidence of severe/critical diseases in COVID-19 (adjusted odds ratio: 0.68 [95% CI, 0.50 to 0.94]). Conclusions: UDCA treatment notably improves the recovery time following an Omicron strain infection without observed safety concerns. These promising results advocate for UDCA as a viable treatment for COVID-19, paving the way for further large-scale and prospective research to explore the full potential of UDCA.
Abbreviations
Author contributions Guo YU, Yang Yu, De-Chuan Zhan: conception of cohort study; Guo YU, Guo-Fu Li: design of the study; Jian Li, Shao-Qiu Tang, Lu-Yao Han: Resources and data curation for cohort study; Yang Yu, Guo Yu, Lu-Yao Han, Zhi-Long Zhang, Tian-Shuo Liu: Investigation of cohort study; Guo-Fu Li: Conception of evidence synthesis and meta-analytical methodology; Lu-Yao Han, Shu-Xin Jiao, Yu-Wei Qiao, Na Zhang: Systematic review and meta-analysis; Lu-Yao Han, Guo-Fu Li, Guo Yu: interpretation of the results; Lu-Yao Han, Guo-Fu Li, Guo Yu: drafting of the manuscript; Guo-Fu Li, Guo Yu: critical revision of the manuscript for important intellectual content.
Declaration of interest The following financial interests may be considered potential competing interests: Y. Yu is the controlling shareholder of Polixir Technologies Co., Ltd. Zhi-Long Zhang and T.S. Liu declare receipt of employment by Polixir Technologies Co., Ltd. The research sponsor, Polixir Technologies Co., Ltd., did not play any role in research design, data collection, analysis and interpretation, report writing, and the decision to submit this paper for publication. The authors have no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed.
Reviewer disclosures Peer reviewers on this manuscript have no relevant..
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