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Real-world outcomes and safety of low- vs. standard-dose SGLT2 inhibitors in heart failure

2025· article· en· W7127593371 on OpenAlexaffabout
O Braver, M Santiago-Jimenez, TinuolaO Odugbemi, A Chu, Shalane Basque, D Cherney, A Weisman, Husam Abdel‐Qadir, C Jackevicius, D S Lee, J A Udell

Bibliographic record

VenueEuropean Heart Journal · 2025
Typearticle
Languageen
FieldMedicine
TopicDiabetes Treatment and Management
Canadian institutionsWomen's College HospitalMount Sinai HospitalInstitute for Clinical Evaluative SciencesUniversity Health Network
Fundersnot available
KeywordsEmpagliflozinDapagliflozinCanagliflozinPropensity score matchingDosingHeart failureAdverse effectRetrospective cohort study

Abstract

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Abstract Background Sodium-glucose cotransporter-2 inhibitors (SGLT2i) are a cornerstone in heart failure (HF) treatment. Unlike other guideline-directed medical therapies (GDMT), which require dose titration, SGLT2i were studied and approved at a fixed dose (e.g., 10 mg/day dapagliflozin or empagliflozin). However, lower doses are sometimes prescribed in real-world practice due to safety concerns, despite lacking clinical trial validation. These alternative dosing strategies have not been systematically studied, raising uncertainty about their clinical effectiveness and safety. Purpose To evaluate real-world outcomes of low-dose versus standard-dose SGLT2i in HF patients. Methods A retrospective cohort study using ICES administrative health databases was conducted. We identified HF patients aged ≥65 years in Ontario, Canada, who were newly prescribed either a low dose (5 mg daily) or standard dose (10 mg daily) of empagliflozin or dapagliflozin between June 1, 2016, and December 31, 2022. The primary outcome was all-cause mortality or cardiovascular (CV) hospitalization. Secondary outcomes included CV and HF hospitalizations, mortality, and adverse drug reactions. Propensity score matching (1:1) was used to adjust for confounders. Multivariable Fine-Gray proportional hazards models examined differences in outcomes between groups. Exclusion criteria included type 1 diabetes, long-term care residents, contraindications to SGLT2i, canagliflozin use and non-Ontario residency. Follow-up continued until treatment discontinuation, dose adjustment, a predefined outcome event, death or end of follow-up (December 31, 2023). Results Among 202,881 HF patients prescribed SGLT2i, 25,595 received a low dose and 177,286 a standard dose. Patients in the low-dose group tended to be older, had lower eGFR, and higher comorbidity burdens but fewer prior CV events and revascularizations. After matching, 46,218 patients remained (23,209 in each group) and baseline characteristics were well-balanced (absolute standardized differences < 0.1). The primary outcome incidence was 6.0 per 100 person-years in both groups. After multivariable adjustment, Low-dose SGLT2i was associated with a lower risk of the composite outcome (HR 0.93, 95% CI 0.88–0.99, p=0.02) and CV hospitalization (HR 0.84, 95% CI 0.78–0.91, p<0.0001), with no significant differences in HF hospitalization (HR 0.93, p=0.33) or mortality (HR 1.04, p=0.47). The incidence of genital mycotic infections and other adverse events was similar in both groups. Conclusion Low-dose SGLT2i was associated with a lower risk of the composite outcome (all-cause mortality or CV hospitalization) and a reduced risk of CV hospitalization compared to standard doses. There was no evidence of increased risk for HF, mortality, or adverse drug reactions. These findings support the consideration of low-dose SGLT2i in selected HF patients. Further studies are needed to clarify the long-term implications of this dosing approach.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.101
Threshold uncertainty score0.201

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.013
GPT teacher head0.287
Teacher spread0.274 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations1
Published2025
Admission routes2
Has abstractyes

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