Factors Influencing Outcome and Treatment Effect in PROACT II
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: The PROACT II study demonstrated a significant benefit from treatment with intra-arterial pro-urokinase (r-proUK) in patients with middle cerebral artery occlusion treated within 6 hours of stroke onset. The purpose of the current study was to examine baseline factors to determine predictors of good outcome and response to treatment. METHODS: We selected from the baseline clinical, radiologic, and angiographic data variables that considered possibly related to outcome. A univariate analysis was performed to examine the association between these baseline factors and good outcome, defined as a modified Rankin scale score <or=2. A multivariate model then selected the most important variables independently influencing prognosis. A risk score for each patient was constructed on the basis of the patient's individual values for each independent variable. Patients were stratified into risk quartiles based on their risk scores, and an odds ratio for each risk quartile was calculated. The treatment effects of each quartile were compared. RESULTS: In the univariate analysis, screening National Institutes of Health stroke scale (NIHSS) score and age were strongly associated with good outcome. The multivariate model selected age, NIHSS score, and CT hypodensity as the most important prognostic variables. Dividing patients into quartiles based on risk scores achieved a uniform gradient of probability of good outcomes. A trend toward benefit of r-proUK treatment was seen in all risk quartiles, and no differential treatment effect was observed across risk groups. CONCLUSIONS: There was no evidence of differential effect of r-proUK across subgroups of patients stratified by risk.
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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".