Abstract WP324: Integrated Systems Enhance Equitable and High-Quality Stroke Prevention Clinic Care
Bibliographic record
Abstract
Stroke prevention clinics were established in Ontario to provide comprehensive, equitable, evidence-based care for patients at high risk of stroke. However, depending on where patients present with their stroke symptoms there are differences in access to diagnostic services. Patients presenting to a primary care office or small hospital, have limited or no access to diagnostic services compared to those presenting to large academic hospitals. To overcome this inequitable access to stroke expertise and diagnostics, we developed a standard referral protocol, a centralized approach to triage and dedicated diagnostic imaging services in regional stroke prevention clinics. The objective of our research was to evaluate the degree to which these system supports have resulted in comprehensive stroke prevention best practice care. Retrospective data analysis was completed using the FY 2011/12 Ontario Stroke Audit of Secondary Stroke Prevention Clinics database. We examined differences in secondary stroke prevention best practices across the five stroke prevention clinics and if there were differences in practice by referral source (Emergency vs. Primary Care). A total of 1853 patients were seen at the five Champlain stroke prevention clinics in 2011/12. The majority of referrals were initiated from Emergency Departments 58.7%, followed by primary care 29.2%, specialists 9.2% and inpatient units 2.8%. Overall, high rates of neuroimaging (97.6%), and vascular imaging (97.6 %) were achieved with little variation across stroke prevention clinics. There was no variation in imaging rates by referral source. The stroke prevention clinics facilitated neuroimaging and vascular imaging for almost 30% of patients, as they did not have these tests completed at the site of initial presentation. Implementing a centralized stroke prevention clinic referral and triage system has enabled equitable access to essential diagnostic testing in the Champlain region. Rapid diagnostic imaging plays a vital role of in identifying stroke etiology, and influences patient prioritization, treatments and management in the stroke prevention clinic setting. Future research should include evaluation of patient outcomes relative to the timing of diagnostic testing.
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 | 0.011 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
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".