Influence of Penumbral Reperfusion on Clinical Outcome Depends on Baseline Ischemic Core Volume
Bibliographic record
Abstract
Background and Purpose— In alteplase-treated patients with acute ischemic stroke, we investigated the relationship between penumbral reperfusion at 24 hours and clinical outcomes, with and without adjustment for baseline ischemic core volume. Methods— Data were collected from consecutive acute ischemic stroke patients with baseline and follow-up perfusion imaging presenting to hospital within 4.5 hours of symptom onset at 7 hospitals. Logistic regression models were used for predicting the effect of the reperfused penumbral volume on the dichotomized modified Rankin Scale (mRS) at 90 days and improvement of National Institutes of Health Stroke Scale at 24 hours, both adjusted for baseline ischemic core volume. Results— This study included 1507 patients. Reperfused penumbral volume had moderate ability to predict 90-day mRS 0 to 1 (area under the curve, 0.77; R 2 , 0.28; P <0.0001). However, after adjusting for baseline ischemic core volume, the reperfused penumbral volume was a strong predictor of good functional outcome (area under the curve, 0.946; R 2 , 0.55; P <0.0001). For every 1% increase in penumbral reperfusion, the odds of achieving mRS 0 to 1 at day 90 increased by 7.4%. Improvement in acute 24-hour National Institutes of Health Stroke Scale was also significantly related to the degree of reperfused penumbra ( R 2 , 0.31; P<0.0001). This association was again stronger after adjustment for baseline ischemic core volume ( R 2 , 0.41; P <0.0001). For each 1% of penumbra that was reperfused, the 24-hour National Institutes of Health Stroke Scale decreased by 0.069 compared with baseline. Conclusions— In patients treated with alteplase, the extent of the penumbra that is reperfused is a powerful predictor of early and late clinical outcomes, particularly when baseline ischemic core is taken into account.
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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 | 0.005 |
| 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 | 0.001 | 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".