Geriatric Conditions and Prescription of Vitamin K Antagonists vs. Direct Oral Anticoagulants Among Older Patients With Atrial Fibrillation: SAGE-AF
Bibliographic record
Abstract
Background: Geriatric conditions are common among patients with atrial fibrillation (AF) and relate to complications of oral anticoagulation (OAC). Objective: To examine the prevalence of geriatric conditions among older patients with AF on OAC and relate type of OAC to geriatric conditions. Methods: Participants had a diagnosis of AF, were aged 65 years, CHA2DS2VASC 2, and had no OAC contraindications. Participants completed a 6-component geriatric assessment that included validated measures of frailty (CHS Frailty Scale), cognitive function (MoCA), social support (MOS), depressive symptoms (PHQ9), vision, and hearing. Type of OAC prescribed was documented in medical records. Results: 86% of participants were prescribed an OAC. These participants were on average aged 75.7 (SD: 7.1) years, 49% were women, two thirds were frail or pre-frail, and 44% received a DOAC. DOAC users were younger, had lower CHA2DS2VASC and HAS-BLED scores, and were less likely to be frail. In Massachusetts, pre-frailty was associated with a significantly lower odds of DOAC vs. VKA use (OR=0.64, 95%CI 0.45, 0.91). Pre-frailty (OR=0.33, 95%CI 0.18-0.59) and social isolation (OR=0.38, 95%CI 0.14-0.99) were associated with lower odds of DOAC receipt in patients aged 75 years or older. Social isolation was associated with higher odds of DOAC use (OR=2.13, 95%CI 1.05-4.29) in patients aged 65-74 years. Conclusions: Geriatric conditions were common and related to type of OAC prescribed, differentially by age group. Research is needed to evaluate whether a geriatric examination can be used clinically to better inform OAC decision-making in older patients with AF.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".