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Record W2948249999 · doi:10.2337/db19-1665-p

1665-P: Fracture Risk in Patients Using Sodium-Glucose Cotransporter 2 Inhibitors: A Real-World Study

2019· article· en· W2948249999 on OpenAlexaboutno aff
Devin Abrahami, Antonios Douros, Hui Yin, Oriana Hoi Yun Yu, Laurent Azoulay

Bibliographic record

VenueDiabetes · 2019
Typearticle
Languageen
FieldMedicine
TopicDiabetes Treatment and Management
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineEmpagliflozinDapagliflozinHazard ratioCanagliflozinType 2 diabetesCohortCohort studyPopulationProportional hazards modelInternal medicineDiabetes mellitusConfidence intervalEnvironmental healthEndocrinology

Abstract

fetched live from OpenAlex

There are concerns that sodium-glucose co-transporter 2 inhibitors (SGLT2Is) may increase the risk of fractures in patients with type 2 diabetes. To date, large cardiovascular outcome trials have generated conflicting findings, and few real-world studies have been conducted to assess this association. As fracture risk in this vulnerable population is associated with increased mortality, there is an urgent need to address this safety issue using real-world data. Thus, the objective of this population-based cohort study is to determine if use of SGLT2Is is associated with an increased fracture risk in patients with type 2 diabetes. Using the UK Clinical Practice Research Datalink, a large primary care database, we identified a cohort of patients newly treated with antihyperglycemic drugs between January 2013 and December 2017. Use of SGLT2Is was modeled as a time-varying exposure and compared with use of dipeptidyl peptidase-4 inhibitors (DPP-4Is). Time-dependent Cox proportional hazards models were used to estimate hazard ratios (HRs) and 95% CIs of incident fractures associated with use of SGLT2Is overall and according to specific SGLT2Is (dapagliflozin, empagliflozin, canagliflozin). We conducted several sensitivity analyses to address potential sources of bias. The cohort included 73,178 patients, which generated 153,179 person-years of observation. During follow-up, 1,973 patients were newly diagnosed with fractures (incidence rate: 12.9/1000 per year). Compared with DPP-4Is, SGLT2Is were not associated with an increased risk of fracture (HR: 0.97, 95% CI: 0.79-1.19). Similar findings were observed when stratifying on specific SGLT2Is, with HRs ranging between 0.67 and 1.42, with all CIs including the null value. The sensitivity analyses yielded highly consistent findings. The results of this large population-based study suggest that use of SGLT2Is is not associated with fracture incidence. This finding should provide reassurance on the safety of this class of drugs. Disclosure D. Abrahami: None. A. Douros: None. H. Yin: None. O. Yu: None. L. Azoulay: None. Funding Canadian Institutes of Health Research

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)0.002
metaresearch head score (Gemma)0.008
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 score0.013
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.001

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 head0.008
GPT teacher head0.245
Teacher spread0.236 · 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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Citations0
Published2019
Admission routes1
Has abstractyes

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