Abstract TMP19: Intravenous Recombinant Tissue-type Plasminogen Activator Use in Young Adults With Acute Ischemic Stroke
Bibliographic record
Abstract
Background: Intravenous recombinant tissue-type plasminogen activator (rt-PA) administration improves outcomes in acute ischemic stroke. However, young patients (<40 years old) presenting with stroke symptoms may experience delays in treatment due to misdiagnosis or a reluctance to treat since they do not fit the profile of a typical stroke patient. Methods: We analyzed data from the large national Get With The Guidelines–Stroke registry for acute ischemic stroke patients hospitalized between January 2009 and September 2015. Multivariable models with generalized estimating equations (GEE) were used to test for differences between younger (age 18-40) and older (age > 40) acute ischemic stroke patients, controlling for patient and hospital characteristics including stroke severity. Results: Of 1,320,965 AIS patients admitted to participating hospitals, 2.3% (30,448) were aged 18-40. Among these patients, 12.5% received rt-PA versus 8.8% of those aged >40 (p<0.001). Of patients arriving within 3.5 hours of symptom onset without contraindications, 68.7% of younger patients received IV rt-PA versus 63.3% of older patients (adjusted OR [aOR] 1.30, 95% CI 1.21 to 1.40), without evidence that age-related differences varied by sex (interaction p-value 0.25). Odds ratios of achieving target door-to-CT times and door-to-needle (DTN) times, and outcomes of rtPA-treated patients, are shown in the Table. Conclusions: Young acute ischemic stroke patients did not receive rt-PA treatment at lower rates than older patients. Outcomes were better and the rate of symptomatic intracranial hemorrhage was lower in the young patients. However, younger patients had significantly longer door-to-CT and DTN times, providing an opportunity to improve the care of these 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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".