Evidence mapPaperPMID 42160591Full record

ArticleDiabetes care2026

Precision Prescribing of SGLT2 Inhibitors in Individuals With Type 2 Diabetes for Primary Prevention of Heart Failure: Model Development and Validation Study.

Katherine G Young, Andrew P McGovern, Rhian Hopkins, Thijs T Jansz, Pedro M Cardoso, Rury R Holman, Ewan R Pearson, Andrew T Hattersley, Angus G Jones, Kieran Docherty and 4 more

Abstract read
In one paragraph

Article in Diabetes care, 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
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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

14 authors.

Katherine G YoungClinical and Biomedical Sciences, University of Exeter Medical School, Exeter, U.K.ORCID 0000-0003-2570-3864
Andrew P McGovernClinical and Biomedical Sciences, University of Exeter Medical School, Exeter, U.K.ORCID 0000-0002-6833-9399
Rhian HopkinsClinical and Biomedical Sciences, University of Exeter Medical School, Exeter, U.K.ORCID 0000-0001-6054-3582
Thijs T JanszClinical and Biomedical Sciences, University of Exeter Medical School, Exeter, U.K.ORCID 0000-0002-5686-5033
Pedro M CardosoClinical and Biomedical Sciences, University of Exeter Medical School, Exeter, U.K.
Rury R HolmanDiabetes Trials Unit, Radcliffe Department of Medicine, University of Oxford, Oxford, U.K.ORCID 0000-0002-1256-874X
Ewan R PearsonDivision of Diabetes, Endocrinology and Reproductive Medicine, Ninewells Hospital and Medical School, University of Dundee, Dundee, U.K.ORCID 0000-0001-9237-8585
Andrew T HattersleyClinical and Biomedical Sciences, University of Exeter Medical School, Exeter, U.K.ORCID 0000-0001-5620-473X
Angus G JonesClinical and Biomedical Sciences, University of Exeter Medical School, Exeter, U.K.ORCID 0000-0002-0883-7599
Kieran DochertySchool of Cardiovascular and Metabolic Health, University of Glasgow, Glasgow, U.K.
Naveed SattarSchool of Cardiovascular and Metabolic Health, University of Glasgow, Glasgow, U.K.ORCID 0000-0002-1604-2593
Beverley M ShieldsClinical and Biomedical Sciences, University of Exeter Medical School, Exeter, U.K.ORCID 0000-0003-3785-327X
John M DennisClinical and Biomedical Sciences, University of Exeter Medical School, Exeter, U.K.ORCID 0000-0002-7171-732X
MASTERMIND Consortium

Funding

Medical Research Council MR/W003988/1
6 · The paper itself

Abstract

objectiveSodium-glucose cotransporter 2 inhibitors (SGLT2i) reduce heart failure (HF) risk in type 2 diabetes (T2D) and are recommended for patients with T2D who have atherosclerotic cardiovascular disease (ASCVD), HF, or chronic kidney disease (CKD). However, most individuals with T2D do not have these conditions, and current guidelines for this group do not indicate which individuals may benefit most from SGLT2i. We aimed to develop and validate a model to predict the individual-level HF benefit of SGLT2i in individuals with T2D without ASCVD, HF, or CKD. RESEARCH DESIGN AND

methodsWe developed the SGLT2i Absolute Benefit Response (SABRE) model, combining absolute HF risk from the validated QDiabetes-HF model with the SGLT2i-associated hazard ratio (HR) for HF hospitalization from a trial meta-analysis (HR 0.63) to estimate individual 5-year HF benefit. Model components and predictions were validated using U.K. primary care data with linked hospital and death records from 2013 to 2020.

resultsAmong 57,368 SGLT2i initiators and 111,673 comparator (dipeptidyl peptidase 4 inhibitor or sulfonylurea) initiators, SGLT2i use was associated with a 30% lower risk of new-onset HF (HR 0.70 [95% CI 0.63-0.78]), consistent with trial evidence. Relative HF benefit did not vary by baseline absolute HF risk (P = 0.82). The SABRE model-predicted 5-year absolute HF benefit with SGLT2i ranged from <0.1% to 14.1% (median 1.0% [interquartile range 0.6-1.8%]) and calibrated well against observed HF outcomes. SABRE provided more targeted HF prevention than current guidelines in those with T2D without ASCVD, HF, or CKD.

conclusionsThe SABRE model is an easily deployed clinical prediction model integrating trial evidence and allowing more precise targeting of SGLT2i for primary HF prevention in T2D.

Indexed as

Diabetes Mellitus, Type 2Heart FailureSodium-Glucose Transporter 2 InhibitorsAgedFemaleHumansMaleMiddle AgedSodium-Glucose Transporter 2 Inhibitors

Identifiers

PMID42160591
PMCPMC7619156

What Socratic holds

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LicenceCC BY
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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 Socratic graph.