Why stroke patients don't receive t-PA? An analysis of patient eligibility: Implications for improving clinical impact by increasing future treatment numbers
Bibliographic record
Abstract
P183 Background T-PA is an effective treatment of acute ischemic stroke within 3 hours. However, the success of t-PA on reducing disability is dependent on it being accessible to more patients. We identified the reasons why patients with ischemic stroke did not receive intravenous t-PA and assessed the community impact of the therapy in a large North American city. Methods Consecutive patients with acute ischemic stroke were identified in a prospective stroke registry at a teaching hospital between October 1996 and December 1999. Additional patients with ischemic stroke admitted to one of three other hospitals during the study period were identified. The Oxford Community Stroke Program Classification was used to record stroke type. Results Of 2165 stroke patients presenting to the emergency department 1179 (54.5%) were diagnosed with ischemic stroke, 31.7% with intracranial hemorrhage, and 13.8 % with transient ischemic attack. 84/339 (29%) patients were admitted within 3 hours of stroke received intravenous t-PA. The major reasons for exclusion for stroke patients presenting within 3 hours were mild stroke (20%), clinical improvement (18.6%), and specific protocol exclusions (11.5%). Delay in presentation to emergency department excluded 840/1179 (71%). 1817 ischemic stroke patients were admitted to Calgary hospitals during the study period of which 4.6% received intravenous t-PA. Generalization of the Calgary experience to other Canadian communities suggests the benefit from t-PA for ischemic stroke may be substantial with an additional 460 independent survivors per annum. Conclusion The effectiveness of t-PA can be improved by understanding why patients are excluded from its use. The eligibility of patients for t-PA must increase by promoting health education programs and by developing organized acute stroke care infrastructure within the community.
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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 | 0.017 | 0.100 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".