Evidence map›Paper›PMID 42741446›Full record

SynthesisFrontiers in pharmacology2026

Effectiveness of SGLT2 inhibitors in slowing chronic kidney disease progression and reducing mortality: a meta-analysis.

Arjun Sharma, Bharat Sharma, Deepthi Sree Vamaraju, Amrendra Kumar Ajay

Abstract readSystematic Review
In one paragraph

Synthesis in Frontiers in pharmacology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Arjun SharmaHarvard Medical School, Harvard University, Boston, MA, United States.
Bharat SharmaGori Devi Girls College, University of Rajasthan, Jaipur, Rajasthan, India.
Deepthi Sree VamarajuInstitute of Systems Science, National University of Singapore, Singapore, Singapore.
Amrendra Kumar AjayHarvard Medical School, Harvard University, Boston, MA, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Chronic kidney disease (CKD) represents a significant health problem worldwide with high morbidity, mortality, and development of end-stage kidney disease (ESKD). Sodium-glucose co-transporter 2 (SGLT2) inhibitors represent an innovative class of medications with possible cardiorenal advantages. We conducted a Meta-analysis to assess their efficacy in CKD management. Methods: Our Meta-analysis was performed using the Preferred Reporting Items for Meta-analyses (PRISMA) guidelines and is registered in PROSPERO (CRD420261362785). Databases used for conducting this systematic review include Cochrane Central Register of Controlled Trials (CENTRAL), PubMed, PubMed Central, and Google Scholar. The databases were searched from their inception till 16 April 2026. Clinical trials in adults diagnosed with CKD were included in this study if they compared the use of SGLT2 inhibitors versus placebo. A random-effects model was used for meta-analysis. Results: Thirteen randomized controlled trials (RCTs) (n = 49,931) were analyzed. A statistically significant increase in total and chronic estimated glomerular filtration rate (eGFR) slope was seen (mean difference: MD = 0.97 mL/min/1.73 m Conclusion: SGLT2 inhibitors were effective in delaying the progression of CKD and lowering mortality. However, despite having a relatively safe profile, this drug class comes with certain hazards that need to be monitored clinically. Systematic Review Registration: https://www.crd.york.ac.uk/prospero/, identifier CRD420261362785.

Indexed as

chronic kidney disease (CKD)end-stage kidney disease (ESKD)estimated glomerular filtration rate (eGFR)renal progressionSGLT2 inhibitors

Identifiers

PMID42741446
PMCPMC13572723

What OpenQuestion holds

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Registered trials

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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 OpenQuestion graph.