Gender and the Symptom Experience before an Atrial Fibrillation Diagnosis
Bibliographic record
Abstract
Atrial fibrillation (AF) is the most common arrhythmia in the world. Despite the increasing prevalence, there remains a limited understanding of how the pre-diagnosis symptom experience varies by gender. The purpose of this study was to retrospectively explore gender differences/similarities in the pre-diagnosis period of AF. Twenty-six adults (13 men and 13 women) were interviewed guided by the Symptom Experience in AF (SEAF). Data were analyzed using a two-step approach to thematic analysis. Women had greater challenges receiving a timely diagnosis, with 10 women (77%) experiencing symptoms ≥1 year prior to their diagnosis, in comparison to only three (23%) of the men. Women also reported more severe symptoms, less AF-related knowledge, viewed themselves as low risk for cardiovascular disease, and described how their comorbid conditions confused AF symptom evaluation. This study provides a foundational understanding of differences/similarities in the AF symptom experience by gender.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".