1093-P: Association between First-Line Monotherapy with Metformin and the Risk of Atrial Fibrillation in Patients with Type 2 Diabetes Mellitus
Bibliographic record
Abstract
Background: Atrial fibrillation (AF) is the most frequent cardiac arrhythmia and is associated with an increased risk of thromboembolic events, heart failure, and frequent hospitalizations. Type 2 diabetes mellitus (T2DM) has one of the strongest associations with AF with an overall 35% increased risk. Metformin is the first-line medication for T2DM and it has been proposed to have anti-inflammatory, pro-metabolic and cardioprotective benefits, but its effect on AF is not well studied. Our objective was to investigate whether the initial metformin monotherapy was associated with reduced AF rates compared to other non-insulin agents. Methods: This retrospective cohort analysis involved adults with newly diagnosed T2DM between 2007 and 2017, without any history of arrhythmias or contraindications to metformin use including GFR less than 30 ml/min who initiated a single antidiabetes therapy (except insulin). A multivariate analysis was performed to control for other variables that may have impacted the association between initial therapy with metformin and the outcomes of interest. Results: Out of 42384 cases with newly diagnosed diabetes, 5664 patients met the inclusion criteria. The majority of patients initiated monotherapy with metformin (81%), followed by sulfonylureas (13%) and thiazolidinediones (4%). The 10-year cumulative incidence of AF in the metformin group was 5.2% vs. 8.1% with others. Competing risk analysis did not demonstrate reduced rates of AF with metformin use (HR 0.92 95% CI 0.69 to 1.21; P = 0.55). Increased age and the presence of CHF were associated with significantly higher risk of AF (HR: 1.29, 95% CI: 1.21 to 1.37; P<0.001; HR: 2.73, 95% CI: 1.62 to 4.61; P<0.001, resp). Conclusion: In this observational study following patients with newly diagnosed T2DM, first-line therapy with metformin, when compared to other non-insulin antidiabetes therapies, was not found to be associated with a decreased risk of developing AF. Disclosure Z. Tekin: None. A. Milinovich: Research Support; Self; Novartis AG, Novo Nordisk Inc. X. Ji: Research Support; Self; Merck & Co., Inc., Novo Nordisk Inc. J. Bauman: None. M. Kattan: Consultant; Self; GlaxoSmithKline plc. Research Support; Self; Boehringer Ingelheim (Canada) Ltd., Novo Nordisk Inc. K.M. Pantalone: Consultant; Self; Bayer Inc., Eli Lilly and Company, Merck & Co., Inc., Novo Nordisk Inc., Sanofi. Research Support; Self; Merck & Co., Inc., Novo Nordisk Inc. Speaker’s Bureau; Self; AstraZeneca, Merck & Co., Inc., Novo Nordisk Inc. R.S. Zimmerman: Research Support; Self; Bayer U.S., Merck & Co., Inc., Novo Nordisk A/S. Speaker’s Bureau; Self; LifeScan, Inc., Merck & Co., Inc. Stock/Shareholder; Self; Baxter, Bristol-Myers Squibb, Pfizer Inc., Procter & Gamble Company. M.K. Chung: None. S. Kashyap: Other Relationship; Self; GI Dynamics Inc.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
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".