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Effect of Antidiabetic Therapy on Clinical Outcomes of COVID-19 Patients With Type 2 Diabetes: A Systematic Review and Meta-Analysis

Zhan et al., Annals of Pharmacotherapy, doi:10.1177/10600280221133577
Oct 2022  
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Mortality 34% Improvement Relative Risk Ventilation 65% ICU admission 1% Metformin for COVID-19  Zhan et al.  META ANALYSIS c19early.org Favorsmetformin Favorscontrol 0 0.5 1 1.5 2+
Metformin for COVID-19
3rd treatment shown to reduce risk in July 2020
 
*, now with p < 0.00000000001 from 96 studies.
No treatment is 100% effective. Protocols combine treatments. * >10% efficacy, ≥3 studies.
4,800+ studies for 98 treatments. c19early.org
Meta analysis of 54 studies (34 for metformin) with a total of over 314,000 patients showing lower mortality with metformin, SGLT-2 inhibitors, and GLP-1 receptor agonists in COVID-19 patients with type 2 diabetes. Metformin, SGLT-2i, and GLP-1ra were associated with 34%, 20%, and 17% lower mortality risk respectively. However, insulin was associated with 52% higher mortality risk and higher ICU admission risk. No significant associations were found for DPP-4 inhibitors, sulfonylureas, α-glycosidase inhibitors, and thiazolidinediones.
22 meta analyses show significant improvements with metformin for mortality1-21, hospitalization7,13, progression1, and severity8,9,13.
Currently there are 96 metformin for COVID-19 studies, showing 35% lower mortality [30‑39%], 33% lower ventilation [17‑46%], 17% lower ICU admission [6‑26%], 18% lower hospitalization [11‑23%], and 5% fewer cases [-4‑13%].
risk of death, 34.0% lower, OR 0.66, p < 0.001, RR approximated with OR.
risk of mechanical ventilation, 65.0% lower, OR 0.35, p = 0.57, RR approximated with OR.
risk of ICU admission, 1.0% lower, OR 0.99, p = 0.92, RR approximated with OR.
Effect extraction follows pre-specified rules prioritizing more serious outcomes. Submit updates
Zhan et al., 29 Oct 2022, China, peer-reviewed, 8 authors. Contact: jhong_lz@163.com, xymacq@hotmail.com, xymacq@tmmu.edu.cn.
This PaperMetforminAll
Effect of Antidiabetic Therapy on Clinical Outcomes of COVID-19 Patients With Type 2 Diabetes: A Systematic Review and Meta-Analysis
BS Kegang Zhan, MS Liuqi Weng, PhD Li Qi, BS Luhan Wang, BS Hao Lin, MS Xiaoyu Fang, PhD Hong Jia, PhD Xiangyu Ma
Annals of Pharmacotherapy, doi:10.1177/10600280221133577
Background: No study has yet systematically evaluated the effect of antidiabetic therapy on clinical outcomes of COVID-19 patients with type 2 diabetes (T2D). Objective: We aimed to evaluate the effect of different antidiabetic therapy on clinical outcomes of COVID-19 patients with T2D. Methods: We comprehensively retrieved the published research which examined the effect of antidiabetic therapy on clinical outcomes of COVID-19 patients with T2D. The odds ratio (OR) and its 95% confidence interval (95% CI) for clinical outcomes were calculated using the random-effects model, and meta-regression was adopted to evaluate the potential sources of heterogeneity between studies. Results: A total of 54 studies were included in this study. We found that the use of metformin (OR = 0.66, 95% CI: 0.58-0.75), SGLT-2i (OR = 0.80, 95% CI: 0.73-0.88), and GLP-1ra (OR = 0.83, 95% CI: 0.70-0.98) were significantly associated with lower mortality risk in COVID-19 patients with T2D, while insulin use might unexpectedly increase the ICU admission rate (OR = 2.32, 95% CI: 1.34-4.01) and risk of death (OR = 1.52, 95% CI: 1.32-1.75). No statistically significant associations were identified for DPP-4i, SUs, AGIs, and TZDs. Conclusion and Relevance: We demonstrated that the usage of metformin, SGLT-2i, and GLP-1ra could significantly decrease mortality in COVID-19 patients with T2D. The heterogeneity across the studies, baseline characteristics of the included patients, shortage of dosage and the duration of antidiabetic drugs and autonomy of drug selection might limit the objectivity and accuracy of results. Further adequately powered and high-quality randomized controlled trials are warranted for conclusive findings.
Declaration of Conflicting Interests The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article. ORCID iDs Luhan Wang https://orcid.org/0000-0001-7917-9071 Xiangyu Ma https://orcid.org/0000-0001-7967-3950 Supplemental Material Supplemental material for this article is available online.
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