Thrombolysis in Patients With Marked Clinical Fluctuations in Neurologic Status Due to Cerebral Ischemia
Bibliographic record
Abstract
BACKGROUND: It is unclear whether thrombolysis benefits patients with fluctuating neurologic symptoms. OBJECTIVE: To evaluate the clinical course of patients with acute stroke who presented with marked fluctuations in neurologic status and received thrombolytic therapy. DESIGN: Prospective analysis. SETTING: London Health Science Centre University Hospital, London. Patients We prospectively identified patients who were treated with intravenous or intra-arterial recombinant tissue plasminogen activator between January 1, 2004, and January 1, 2006. For this analysis, we chose patients who had marked fluctuation in neurologic status at presentation and who received thrombolytic therapy. Main Outcome Measure Fluctuation of neurologic deficits, defined as a 4-point or greater increase or decrease in the National Institutes of Health Stroke Scale (NIHSS) score. RESULTS: Among 127 patients, 13 (10.2%) had clinical fluctuations. Patients with fluctuations presented with a lower NIHSS score (median, 7; interquartile range, 10-17) compared with patients without fluctuations (median, 12; interquartile range, 10-17) (P < .001). Fluctuation of symptoms or signs ceased after thrombolysis. At 24 hours after stroke, the median NIHSS score was 2 (range, 1-12). All patients had favorable neurologic and functional outcomes at 3 months after thrombolysis (modified Rankin scale score, 0-2). CONCLUSION: Thrombolysis may benefit patients with fluctuating symptoms or signs due to cerebral ischemia.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.001 | 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".