World Stroke Organization Brain & hEart globAl iniTiative Program
Bibliographic record
Abstract
INTRODUCTION: The World Stroke Organization (WSO) Brain & Heart Task Force developed the Brain & hEart globAl iniTiative (BEAT), a pilot feasibility implementation program to establish clinical collaborations between cardiologists and stroke physicians who work at large healthcare facilities. METHODS: The WSO BEAT pilot project focused on atrial fibrillation (AF) and patent foramen ovale (PFO) detection and management, and poststroke cardiovascular complications known as the stroke-heart syndrome. The program included 10 sites from 8 countries: Brazil, China, Egypt, Germany, Japan, Mexico, Romania, and the USA The primary composite feasibility outcome was the achievement of the following 3 implementation metrics (1) developing site-specific clinical pathways for the diagnosis and management of AF, PFO, and the stroke-heart syndrome; (2) establishing regular Neurocardiology rounds (e.g., monthly); and (3) incorporating a cardiologist to the stroke team. The secondary objectives were (1) to identify implementation challenges to guide a larger program and (2) to describe qualitative improvements. RESULTS: The WSO BEAT pilot feasibility program achieved the prespecified primary composite outcome in 9 of 10 (90%) sites. The most common challenges were the limited access to specific medications (e.g., direct oral anticoagulants) and diagnostic (e.g., prolonged cardiac monitoring) or therapeutic (e.g., PFO closure devices) technologies. The most relevant qualitative improvement was the achievement of a more homogeneous diagnostic and therapeutic approach. CONCLUSION: The WSO BEAT pilot program suggests that developing neurocardiology collaborations is feasible. The long-term sustainability of the WSO BEAT program and its impact on quality of stroke care and clinical outcomes needs to be tested in a larger and longer duration program.
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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 | 0.021 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.013 | 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".