Atrial Fibrillation in the Context of Thyrotoxicosis: Prevalence and Clinical Determinants
Bibliographic record
Abstract
Background: Atrial fibrillation (AF) is a frequent but variably reported complication of thyrotoxicosis, with mechanisms that extend beyond thyroid hormone excess. Clarifying its prevalence and determinants may guide early detection and management. Methods: We conducted a retrospective cross-sectional study of adults with thyrotoxicosis. Clinical, biochemical, and electrocardiographic data were reviewed. Associations between variables and AF were assessed using generalized linear models with robust errors, and results expressed as adjusted odds ratios (ORs) with 95% confidence intervals (CIs). Results: Among 801 patients with thyrotoxicosis, 65 had AF, yielding a prevalence of 8.1% (95% CI: 6.3 - 10.2). Compared with non-AF patients, those with AF were older, more often male (48% vs. 20%), and more frequently had chronic kidney disease, dyslipidemia, diabetes, heart failure (HF), cerebrovascular disease, and thyroid crisis (all P < 0.01). In multivariable analysis, independent determinants included age 35 - 60 years (adjusted OR 5.48; 95% CI: 2.03 - 14.83), age > 60 years (adjusted OR 11.39; 95% CI: 3.43 - 37.76), male sex (adjusted OR 3.38; 95% CI: 1.70 - 6.30), HF (adjusted OR 11.25; 95% CI: 2.85 - 44.54), and thyroid crisis (adjusted OR 61.84; 95% CI: 21.89 - 181.32). Thyroid hormone levels were not independently associated with AF. Conclusion: AF was observed in approximately 8% of patients with thyrotoxicosis. The findings suggested that clinical vulnerabilities - older age, male sex, HF, and thyroid crisis - were more strongly associated with AF than thyroid hormone levels. These results supported targeted AF screening in high-risk thyrotoxic patients and indicated that rhythm management should consider patient susceptibility alongside restoring euthyroidism.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".