Does intravenous rtPA benefit patients in the absence of CT angiographically visible intracranial occlusion?
Bibliographic record
Abstract
BACKGROUND: In patients with acute stroke receiving intravenous tissue plasminogen activator (tPA), we postulated that the presence of intracranial occlusion on CT angiography (CTA) modifies the benefit of thrombolysis. MATERIALS AND METHODS: Using a retrospective cohort design, we identified patients with acute ischemic stroke in our CTA database between May 2002 and August 2007. All the patients had a CTA within 12 h of onset, a premorbid modified Rankin scale (mRS) < or = 1, and a baseline National Institute of Health Stroke Scale score(NIHSS)f > or = 6. The primary outcome was early effectiveness of tPA defined as an NIHSS score of < or = 2 at 24 h or a 4-point NIHSS improvement at 24 h. Secondary outcome included mRS < or = 1 at 90 days. The relationship between intracranial occlusion on CTA and benefit of tPA was assessed using a test for interaction. RESULTS: A total of 287 patients met the criteria [occlusion present N =168; (98 with tPA; 70 without tPA) and occlusion absent N = 119; (52 with tPA; 67 without tPA)]. Those with intracranial occlusion were likely to have more severe strokes (NIHSS > or = 15; P < 0.001) and abnormal brain imaging (ASPECTS < or =7; P < 0.001). For outcome of 4-point NIHSS score improvement at 24 h, benefit from tPA was observed only among patients with a visible occlusion (absolute difference in favor of tPA: 20.4% vs. 0.7%; P = 0.06). CONCLUSION: In patients with acute ischemic stroke, thrombolysis produced a better early clinical response among patients with intracranial occlusion, which needs to be confirmed in stroke thrombolysis trials.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".