Impact of advanced age on management and prognosis in atrial fibrillation: insights from a population-based study in general practice
Bibliographic record
Abstract
OBJECTIVES: to examine the use of antithrombotic therapy and predictors of stroke and death in very elderly (≥85 years) atrial fibrillation (AF) patients in a general practice cohort from the UK. DESIGN: retrospective, observational cohort study; 12-month follow-up period. SETTING: eleven general practices serving the town of Darlington, England representing a population of 105,000 patients. PATIENTS: two thousand two hundred and fifty-nine patients with a history of AF, 561 (24.8%) aged ≥85 years. MAIN OUTCOME MEASURES: use of antithrombotic therapy by age group and predictors of stroke and death. RESULTS: five hundred and sixty-one (24.8%) AF patients aged ≥85 years (mean (SD) age 89 (4) years; 66% female) identified with a mean CHA2DS2-VASc score of 4.6 (SD 1.4). Thirty-six per cent received oral anticoagulation (OAC) compared with 57% in the 75-84 years age group. Forty-nine per cent of the very elderly received antiplatelet (AP) monotherapy; recorded OAC contraindications and declines were greatest among those aged ≥85 years. Stroke risk was highest among the very elderly (5.2% per annum), despite anticoagulation (3.9%). Multivariate analyses demonstrated an increased risk of stroke with AP monotherapy (odds ratio (OR) 2.45, 95% confidence intervals (CIs) 1.05-5.70) and a significant reduction in all-cause mortality with OAC therapy (OR 0.59, 95% CI 0.36-0.99). CONCLUSION: the majority of very elderly AF patients in general practice do not receive OAC despite their higher stroke risk; almost half received AP monotherapy. AP use independently increased the risk of stroke, signifying that effective stroke prevention requires OAC regardless of age, except where true contraindications exist.
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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 | 0.000 | 0.000 |
| 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".