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CONCOMITANT USE OF SULFONYLUREAS AND BETA-BLOCKERS AND THE RISK OF SEVERE HYPOGLYCEMIA: POPULATION-BASED COHORT STUDY

2022· article· en· W4283217706 on OpenAlexaff
Jenny Dimakos, Ying Cui, Robert W. Platt, Christel Renoux, B. Kristian Filion, Antonios Douros

Bibliographic record

VenueJournal of Hypertension · 2022
Typearticle
Languageen
FieldMedicine
TopicDiabetes Management and Research
Canadian institutionsJewish General HospitalMcGill University
Fundersnot available
KeywordsMedicineHazard ratioConcomitantInternal medicineHypoglycemiaAtenololBisoprololOdds ratioPopulationCardiologyAnesthesiaConfidence intervalInsulinHeart failureBlood pressure

Abstract

fetched live from OpenAlex

Objective: Evidence suggests that beta-blockers increase the risk of hypoglycemia. However, their effects among users of sulfonylureas, drugs that also cause hypoglycemia, are not well understood. Thus, our study assessed the potential association between concomitant use of sulfonylureas and beta-blockers and the risk of severe hypoglycemia. Design and method: This retrospective cohort study used the United Kingdom Clinical Practice Research Datalink linked to hospitalization and vital statistics data. It included patients with type 2 diabetes initiating sulfonylurea treatment between 1998 and 2020. Patients with use of beta-blockers in the 6 months prior to cohort entry were excluded. Time-dependent Cox proportional hazards models estimated confounder-adjusted hazard ratios (HRs) with 95% confidence intervals (CIs) of severe hypoglycemia associated with concomitant use of sulfonylureas and beta-blockers compared to sulfonylurea use alone. To account for residual confounding, we also performed an analysis using an active comparator, where the reference category was current concomitant use of sulfonylureas and thiazide diuretics. To explore the role of cardioselectivity in the hypoglycemic risk of beta-blockers, we further compared head-to-head current concomitant use of sulfonylureas and non-cardioselective beta-blockers (i.e., propranolol, carvedilol, sotalol, labetalol) versus current concomitant use of sulfonylureas and cardioselective beta-blockers (i.e., acebutolol, atenolol, bisoprolol, metoprolol, nebivolol, esmolol). Results: Our cohort included 252,869 patients initiating sulfonylureas. During a mean (standard deviation) follow-up of 8.6 (5.7) years, there were 16,857 events of severe hypoglycemia (crude incidence rate, 7.8 [95% CI, 7.6–7.9] per 1000 person-years). Compared to sulfonylurea use alone, concomitant use of sulfonylureas and beta-blockers was associated with a 53% increased risk of severe hypoglycemia (adjusted HR, 1.53; 95% CI, 1.42–1.65). The use of an active comparator led to consistent findings (adjusted HR, 1.69; 95% CI, 1.42–2.01). When comparing concomitant use of sulfonylureas and non-cardioselective beta-blockers to concomitant use of sulfonylureas and cardioselective beta-blockers, we were not able to detect an increased risk of severe hypoglycemia (adjusted HR, 0.95; 95% CI, 0.74–1.24). Conclusions: Our population-based study showed an increased risk of severe hypoglycemia associated with concomitant use of sulfonylureas and beta-blockers. Cardioselectivity of beta-blockers did not seem to play a major role in this regard.

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)0.004
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 score0.009
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.029
GPT teacher head0.253
Teacher spread0.225 · 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
Published2022
Admission routes1
Has abstractyes

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