ROLE OF PERFUSION CT SCAN IN ACUTE ISCHEMIC STROKE WITHIN 6 HOURS AFTER SYMPTOMS ONSET
Bibliographic record
Abstract
Background: CT-perfusion (CTP) has a growing role in evaluating stroke. It can be performed easily following non-contrast CT and has advantages of accessibility and speed. Differentiation of salvageable ischemic penumbra may help identify patients most likely to benefit from reperfusion therapies. However, its utility within the first 6 hours after stroke has been controversial.Methods : We retrospectively analyzed patients admitted to our stroke unit (terciary center) during 2017. We collected data obtained from initial imaging (Alberta Stroke Program Early CT Score (ASPECTS), arterial occlusion revealed by CT angiography (CTA), perfusion mismatch) and clinical data (on admission/at discharge NIHSS, age, sex, classic vascular risk factors and applied reperfusion therapies).Results : A total of 521 patients were admitted to our stroke unit during 2017. 168 met the inclusiu00f3n criteria (patients with acute neurological symptoms who were conducted a multiparametric CT scan with less tan six hours from onset). The mean time from symptom onset to CT imaging was 1,5 hours. 9% of patients had a non contrast CT ASPECTS of < 7 on arrival. 13,69% did not have any arterial occlusion revealed by CTA but showed perfusion alterations. Reperfusion therapies were performed in 78% (67,26% rtPA, 34,52% thrombectomy , 23,21% thrombectomy + rtPA). In 14 patients (8,33%) CT perfusion helped in clinical decisiu00f3n making. 3 patients were stroke mimics, and 11 patients had a non contrast CT ASPECT 5-6 on arrival. In this cases significant penumbra to core mismatch was used as selection criteria and helped decision making (6 underwent thrombectomy). Conclusion: CTP can help decission making in a small group of patients, especially in those cases with non contrast CT ASPECT 5-6 despite a short time after stroke and also in stroke mimics.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".