P3617Improving the uptake of anticoagulation for prevention of atrial fibrillation related stroke
Bibliographic record
Abstract
Background: Suboptimal anticoagulation in patients with atrial fibrillation (AF) is associated with increased risk of stroke. In 2014/15 across 44 general practitioner (GP) practices in a South London Clinical Commissioning Group (CCG), only 73% of patients with AF at risk of stroke were anticoagulated. In the cohort of 489 patients who are not anticoagulated the CCG would expect to see up to 25 strokes per annum. At the time, the introduction of the CHA2DS2VASc score to assess stroke risk in primary care was expected to identify a higher number of at-risk patients requiring anticoagulant therapy. Aims: 1. To ensure all patients on the AF register have had an assessment of stroke risk using CHA2DS2VASc from 2015/16 2. To ensure all patients considered at risk are offered anticoagulant therapy, including reviewing any patients currently treated with aspirin for stroke prevention in AF 3. To educate practice staff on the use of stroke risk assessment tools, bleeding risk assessment tools and the role of anticoagulation in stroke prevention in 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 | 0.007 | 0.031 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.022 | 0.004 |
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".