1135-P: Concomitant Use of Sulfonylureas and Beta-Blockers and the Risk of Severe Hypoglycemia: A Population-Based Cohort Study
Bibliographic record
Abstract
Background: Beta-blockers may interact with sulfonylureas (SU) and increase their hypoglycemic risk. Our study assessed the potential association between concomitant use of SU and beta-blockers and the risk of severe hypoglycemia. Methods: We used the UK's Clinical Practice Research Datalink linked to hospitalization and vital statistics data of patients with type 2 diabetes initiating SU between 1998 and 2020, excluding those with beta-blocker use in the past 6 months. Time-dependent Cox models estimated hazard ratios (HRs) with 95% confidence intervals (CIs) of severe hypoglycemia associated with current concomitant use of SU and beta-blockers compared to current SU use alone, adjusted for baseline confounders. To address potential residual confounding, we repeated the analysis with current concomitant use of SU and thiazide diuretics as reference group. We also compared current concomitant use of SU and non-cardioselective (propranolol, carvedilol, sotalol, labetalol) vs. cardioselective beta-blockers (acebutolol, atenolol, bisoprolol, metoprolol, nebivolol, esmolol) to explore the role of beta-blocker cardioselectivity in this association. Results: Our cohort included 252,869 SU initiators. The crude incidence rate of severe hypoglycemia was 7.8 per 1000/year. Concomitant use of SU and beta-blockers was associated with an increased risk of severe hypoglycemia compared to SU use alone (HR, 1.53; 95% CI, 1.42-1.65) . Changing the reference group led to consistent findings (HR, 1.69; 95% CI, 1.42-2.01) . There was no difference in the risk when comparing concomitant use of SU and non-cardioselective beta-blockers to concomitant use of SU and cardioselective beta-blockers (HR, 0.95; 95% CI, 0.74-1.24) . Conclusion: Our large cohort study showed an increased risk of severe hypoglycemia associated with concomitant use of SU and beta-blockers compared to SU use alone. This association did not vary with beta-blocker cardioselectivity. Disclosure J.Dimakos: None. Y.Cui: None. R.W.Platt: Consultant; Amgen Inc., Biogen, Merck & Co., Inc., Nant Pharma, Pfizer Inc. C.Renoux: None. K.B.Filion: None. A.Douros: None. Funding Canadian Institutes of Health Research (PJT-165882)
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".