Effects of thrombolysis for acute stroke in patients with pre-existing disability.
Bibliographic record
Abstract
BACKGROUND: Thrombolysis for acute stroke is beneficial in selected patients. Because clinical trials generally exclude patients with pre-existing disability, this subgroup of patients has not been studied. We examined the outcomes after thrombolysis of patients with and without disability before their stroke. METHODS: We prospectively followed 112 consecutive patients with acute ischemic stroke who were given intravenous thrombolysis treatment according to published protocols. Three-month outcomes of the patients with pre-existing disability (defined as a prestroke score of 2 or more on the modified Rankin scale [MRS]) were compared with those of patients without pre-existing disability (defined as a prestroke MRS score of 0 or 1) and with those of 168 patients similarly treated in the National Institute of Neurological Disorders and Stroke trial. RESULTS: At 3 months after the stroke, patients with pre-existing disability (21% of the 112) had a higher mortality rate than those without (33% v. 14%) (odds ratio 3.2, 95% confidence interval 1.0-10.1) and worse function (median MRS score 3 v. 2, p = 0.03). However, there was little difference between the 2 groups in neurologic impairment among the survivors (median score on the National Institutes of Health stroke scale 4 v. 2, p = 0.41) or in the total proportion of those with an MRS score of 0 or 1 or, for those with a prestroke score greater than 1, a return to the prestroke score (42% v. 41%, p = 0.87). INTERPRETATION: Although the true effectiveness of thrombolysis for acute stroke in patients with pre-existing disability is not known, treated patients appear able to return to their prestroke level of function as often as patients without pre-existing disability, despite a significantly higher mortality rate.
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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 | 0.001 |
| 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 | 0.001 |
| 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".