ImportancePatients with COVID-19 have a high prevalence of diabetes, and diabetes and blood glucose control are determinants of intensive care unit admission and mortality.ObjectiveTo evaluate the association between COVID-19–related adverse outcomes and 8 antihyperglycemic drugs in patients with diabetes who were subsequently diagnosed and hospitalized with COVID-19.Data SourcesData were retrieved and collected in PubMed, Embase, Cochrane Central Register, Web of Science, and ClinicalTrials.gov from database inception to September 5, 2022.Study SelectionFor this systematic review and network meta-analysis, randomized clinical trials and observational studies conducted among patients with diabetes while receiving glucose-lowering therapies for at least 14 days before the confirmation of COVID-19 infection were included after blinded review by 2 independent reviewers and consultations of disagreement by a third independent reviewer. Of 1802 studies initially identified, 31 observational studies met the criteria for further analysis.Data Extraction and SynthesisThis study follows the Preferred Reporting Items for Systematic Reviews and Meta-analyses reporting guideline. Bayesian network meta-analyses were performed with random effects.Main Outcomes and MeasuresA composite adverse outcome, including the need for intensive care unit admission, invasive and noninvasive mechanical ventilation, or in-hospital death.ResultsThirty-one distinct observational studies (3 689 010 patients with diabetes hospitalized for COVID-19) were included. The sodium-glucose cotransporter-2 inhibitors (SGLT-2is) were associated with relatively lower risks of adverse outcomes compared with insulin (log of odds ratio [logOR], 0.91; 95% credible interval [CrI], 0.57-1.26), dipeptidyl peptidase-4 inhibitors (logOR, 0.61; 95% CrI, 0.28-0.93), secretagogues (logOR, 0.37; 95% CrI, 0.02-0.72), and glucosidase inhibitors (logOR, 0.50; 95% CrI, 0.00-1.01). Based on the surface under the cumulative ranking curves value, SGLT-2is were associated with the lowest probability for adverse outcomes (6%), followed by glucagon-like peptide-1 receptor agonists (25%) and metformin (28%). A sensitivity analysis revealed that the study was reliable.Conclusions and RelevanceThese findings suggest that the use of an SGLT-2i before COVID-19 infection is associated with lower COVID-19–related adverse outcomes. In addition to SGLT-2is, glucagon-like peptide-1 receptor agonists and metformin were also associated with relatively low risk of adverse outcomes.

Background: We aimed to develop a simple nomogram and online calculator for predicting the risk of COVID-19-related mortality in patients with diabetes, and to compare the practicality and cost-effectiveness of the nomogram with previous prediction models.Methods: We did a retrospective study in hospitals designated for 127 patients with diabetes hospitalized for COVID-19 in Tehran. Adult patients with previous diabetes status or compliance with diabetes criteria on admission hospitalized for COVID-19 were enrolled. Based on the least absolute shrinkage and selection operator method and multivariable logistic regression computed, a nomogram was developed using predictors upon admission. C-statistics were validated internally in the cohort by bootstrap and in subtypes analysis. The accuracy and cost-effectiveness between the nomogram and previous models were compared through C-statistics.Results: From February 29 to July 20, 2020, 127 patients were eligible for inclusion in the cohort, of which 29 died for COVID-19. Loss of consciousness, pulse, neutrophil to lymphocyte ratio and albumin were independent risk factors for COVID-19 mortality in diabetes. The nomogram and the free online calculator had a high C-statistic of 0.900 (0.842-0.958) for predicting mortality in diabetes with COVID-19, which performed better discrimination and clinical usefulness than previous models. C-statistic values were stable in internal validation and different subtypes.Conclusions: The nomogram and online calculator were used by emergency physicians and vaccine prevention doctors to identify diabetes with high COVID-19 mortality, which performed better than previous models. These patients might benefit from intensive monitoring, early preventive measures and vaccination.

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