Evidence mapPaperPMID 40136608Full record

ReviewDiseases (Basel, Switzerland)2025

SGLT2 Inhibitors in COVID-19: Umbrella Review, Meta-Analysis, and Bayesian Sensitivity Assessment.

Vinay Suresh, Muhammad Aaqib Shamim, Victor Ghosh, Tirth Dave, Malavika Jayan, Amogh Verma, Vivek Sanker, Priyanka Roy, Mainak Bardhan

Abstract readReview
In one paragraph

Review in Diseases (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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0cells of the map it votes in
2citing papers in PubMed
field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

9 authors.

Vinay SureshKing George's Medical University, Lucknow 226003, India.ORCID 0000-0002-1401-9154
Muhammad Aaqib ShamimDepartment of Pharmacology, All India Institute of Medical Sciences, Jodhpur 342005, India.ORCID 0000-0003-3418-8171
Victor GhoshAndhra Medical College, Visakhapatnam 530002, India.ORCID 0000-0003-0914-1056
Tirth DaveBukovinian State Medical University, 58002 Chernivtsi, Ukraine.ORCID 0000-0001-7935-7333
Malavika JayanDepartment of Internal Medicine, Bangalore Medical College and Research Institute, Bangalore 560002, India.
Amogh VermaDepartment of Internal Medicine, Rama Medical College Hospital and Research Centre, Hapur 245304, India.ORCID 0000-0003-2499-4874
Vivek SankerDepartment of Neurosurgery, Trivandrum Medical College Hospital, Trivandrum 695011, India.ORCID 0000-0003-0615-8397
Priyanka RoyDepartment of Labour, Government of West Bengal, Kolkata 700001, India.ORCID 0009-0008-7269-7130
Mainak BardhanThe Dr. John T. Macdonald Foundation, Department of Human Genetics, University of Miami Miller School of Medicine, Miami, FL 33136, USA.ORCID 0000-0002-4106-409X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSeveral studies have reported a reduced risk of COVID-19-related mortality in patients taking antidiabetic medications. This is an umbrella review, meta-analysis, and Bayesian sensitivity assessment of SGLT2 inhibitors (SGLT2is) in COVID-19 patients with type 2 diabetes mellitus (T2DM).

methodsA search was conducted on the MEDLINE (PubMed), EMBASE, Cochrane, and ClinicalTrials.gov databases on 5/12/2023. We performed an umbrella review of systematic reviews and meta-analyses on the effects of SGLT2is in T2DM patients with COVID-19 and critically appraised them using AMSTAR 2.0. Trials investigating SGLT2i use in COVID-19 patients post-hospitalisation and observational studies on prior SGLT2i use among COVID-19 patients were included in the meta-analysis, adhering to the PRISMA guidelines.

resultsSGLT2is exhibited significantly lower odds of mortality (OR 0.67, 95% CI 0.53-0.84) and hospitalisation (OR 0.84, 0.75-0.94) in COVID-19 patients with T2DM. Bayesian sensitivity analyses corroborated most of the findings, with differences observed in hospitalisation and mortality outcomes. SGLT-2 inhibitors showed an OR of 1.20 (95% CI 0.64-2.27) for diabetic ketoacidosis. Publication bias was observed for hospitalisation, but not for mortality. The GRADE assessment indicated a low to very low quality of evidence because of the observational studies included.

conclusionsThe prophylactic use of SGLT2is reduces mortality and hospitalisation among COVID-19 patients, particularly in patients with diabetes. The utility of SGLT2is after hospitalisation is uncertain and warrants further investigation. A limited efficacy has been observed under critical conditions. Individualised assessment is crucial before integration into COVID-19 management.

Indexed as

Bayesian sensitivityCOVID-19hospitalisationmeta-analysismortalitySGLT2iSGLT2 inhibitorstype 2 diabetes mellitus

Identifiers

PMID40136608
PMCPMC11941288

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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 Socratic graph.