Abstract W P331: Management of TIA Patients Referred to Ontario Secondary Stroke Prevention Clinics From the Emergency Department
Bibliographic record
Abstract
Background: Previous studies have found that patients with TIA discharged from the emergency department (ED) have low rates of testing and treatment for secondary stroke prevention. Secondary Stroke Prevention Clinics (SPCs) were established in Ontario to increase access to diagnostics, treatment, and risk factor education programs for patients at risk of stroke. We aimed to characterize the management of patients with transient ischemic attack (TIA) and ischemic stroke referred to the SPCs following discharge from the ED. Method: The Ontario Stroke Registry performed a chart audit of 40 of 41 operational SPCs between April 1, 2011 and March 31, 2012. We included patients discharged from the ED and referred to a SPC with a diagnosis of probable stroke or TIA, and evaluated processes of best practice care. Using encrypted health card numbers, we linked to administrative databases to identify 7, 30 and 90 day outcomes after the index event. Results: Our study sample included 8,501 patients discharged from the ED and referred to a SPC with probable stroke/TIA. After evaluation in the SPC, 1,902 were given a final diagnosis of TIA and 1,126 ischemic stroke. The median age was 72 years and 46.6% were female. The median time from ED discharge to clinic visit was 8 days for TIA patients and 7 days for ischemic stroke patients. The majority of patients (>92%) received neuroimaging, carotid imaging and antithrombotic therapy, and rates of treatment were similar in those with TIA and stroke. The rate of death or recurrent stroke admission at 30 days was 3.6% among patients with confirmed ischemic stroke, and 0.4% in those with TIA. Conclusion: Ontario patients with TIA and ischemic stroke discharged from the ED with stroke secondary prevention clinic follow up receive high quality best practice secondary stroke prevention care. Further work will examine whether TIA patients discharged from EDs without SPC follow up have similar care and outcomes.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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".