Abstract W P369: International Variability in Stroke Preventive Care
Bibliographic record
Abstract
Introduction: Research protocols for stroke prevention trials commonly specify goals for preventive care. We report variability in goal achievement between 3 countries participating in an on-going stroke secondary prevention trial. Methods: The Insulin Resistance Intervention after Stroke (IRIS) trial is testing pioglitazone, compared with placebo, for prevention of stroke and myocardial infarction among non-diabetic patients with a recent ischemic stroke/TIA. Preventive care is provided by personal physicians, although achievement of prevention goals is monitored and reported to participants and their physicians annually. Goals are from the American Heart Association guidelines: blood pressure (BP) <140/90 mmHg, statin therapy, and anti-platelet or anticoagulation depending on clinical indications. At baseline and year 1, we compared the proportions of participants meeting these goals in the largest enrolling countries: Canada (CA), United Kingdom (UK) and United States (US). Results: Participant characteristics were similar across countries, except the proportions of women and blacks were lower in the UK and CA than the US, and self-reported hypertension was more common in US than CA or UK. At baseline, achievement of BP goal was lower in the UK (53%) compared with the US (66%) and CA (75%) (Chi 2 p<0.0001). Statin therapy was used more commonly in the UK (91%) and CA (88%) compared with the US (80%) (Chi 2 p<0.0001). Differences persisted at year 1. At baseline, use of antithrombotic therapy was high (99%) in all countries. However, at year 1, use fell in US (96%) compared to CA and UK (p=0.02). Conclusions: Secondary preventive care for stroke varied among 3 countries for BP, statin therapy and antithrombotic therapies despite the IRIS protocol specifying uniform goals. These findings may be the result of disagreement among practitioners in the 3 countries for secondary prevention goals, variability in care delivery, or variability in research implementation. Understanding and resolving variability may lead to more efficient research and improved care for patients.
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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 | 0.057 | 0.168 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.026 | 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".