P4608Benefits of active involvement of community pharmacists in know your pulse awareness campaign
Bibliographic record
Abstract
Background: Atrial fibrillation is the most common cardiac arrhythmia globally, responsible for one third of strokes, and often resulting in death or incapacity. This condition, frequently asymptomatic, is estimated to be up to 50% undiagnosed. Reducing this risk with appropriate detection and management strategies offers substantial economic and patient benefits. The International Pharmacist for Anticoagulation Care Taskforce- [iPACT] created a partnership with the Atrial Fibrillation Association (AFA) to test a model whereby pharmacists are actively involved in opportunistic screening for AF initially in all ages as a proof of concept. Purpose: To assess the feasibility of pharmacists implementing pulse checks in community pharmacy to enable identification of new cases of AF and subsequent initiation of anticoagulation. Methods: This initiative was tested in 5 iPACT member countries during global AF aware week (21–27th November 2016): Canada, New Zealand, Portugal, Spain, and UK. Materials (posters and leaflets) and training on pathophysiology of AF and demonstration of pulse taking was presented to all centres prior to taking part in the campaign. Any person walking into a community pharmacy over 18 years of age was offered a free pulse check. For any irregularity detected, individualised counselling was offered with a referral made to local family physician and recommendation that if AF was confirmed, anticoagulation should be offered in accordance with international guidelines. Written patient consent was obtained with ethics approval sought in countries requiring it.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.012 | 0.027 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.032 | 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".