The impact of lesion side on acute stroke treatment
Bibliographic record
Abstract
BACKGROUND: Only a small percentage of patients with acute stroke are treated with recombinant tissue plasminogen activator (rt-PA). OBJECTIVE: To investigate why patients with right-hemisphere strokes seem at high risk of not receiving rt-PA. METHODS: This study includes two phases. Phase 1: the authors compared demographic, clinical, and outcome measures between patients with right- and left-hemisphere strokes in the rt-PA Registry of Southwestern Ontario (RSWO); Phase 2: the authors tested the hypotheses generated in Phase 1 using the Registry of the Canadian Stroke Network (RCSN). A multiple logistic analysis was applied to detect independent predictors of rt-PA administration. RESULTS: Phase 1: of 179 rt-PA-treated patients, 39% had right-hemisphere syndrome. Patients with right-hemisphere strokes had a longer hospital stay (15 vs 9 days; p = 0.03). Phase 2: of 990 stroke patients in the RCSN, 505 (51%) had a right- and 485 (49%) a left-hemisphere syndrome. Of 110 rt-PA-treated patients, 37 (34%) had a right-hemisphere syndrome (p = 0.0001). Negative independent predictors of rt-PA administration were right-hemisphere stroke (OR, 0.55; CI: 0.31 to 0.96; p = 0.037), onset-to-emergency department time (OR, 0.99; CI 0.98 to 0.99; p = 0.04), and CNS score (OR, 0.78; CI 0.71 to 0.86; p < 0.0001). Neglect predicted rt-PA administration (OR, 2.32; CI 1.29 to 4.16; p = 0.004). CONCLUSIONS: Patients with right-hemisphere strokes are 45% less likely to be treated with recombinant tissue plasminogen activator (rt-PA) compared to patients with left-hemisphere strokes. The presence of neglect confers a twofold increased likelihood of rt-PA administration. Prehospital delay and lack of standardized scores for the neglect syndrome may limit accessibility of patients with right-hemisphere stroke to thrombolysis.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".