Recanalization and Functional Outcome in Patients with Cervico-cephalic Arterial Dissections
Bibliographic record
Abstract
BACKGROUND: Cervico-cephalic arterial dissections (CeAD) are an important cause of stroke in young patients. This study aimed to determine the frequency and predictors of recanalization in spontaneous CeAD and to study the effect of recanalization on functional outcomes. METHODS: We identified patients presenting with acute ischemic stroke secondary to CeAD from the CT angiography (CTA) database of the Calgary Stroke Program. Dissections were diagnosed based on standard clinical and imaging findings. At the discretion of treating stroke Neurologists, the patients were either treated with single antiplatelet or dual antiplatelet or triple therapy. Follow-up imaging with CTA, magnetic resonance imaging, and DSA was completed, and a Modified Rankin scale (mRS) was performed to determine the outcome. RESULTS: Fifty-six patients with CeAdD were studied. Thirty-four patients (18 VAD; vertebral artery dissection and 16 CAD; carotid artery dissection) were followed up for recanalization. Complete recanalization was observed in 27 subjects; 13 patients with VAD recanalized in comparison to 14 with CAD (p = 0.40). All non-recanalized patients had hypertension. A good clinical outcome (mRS ≤ 2) was observed in 47 patients. Interestingly, the likelihood of a good neurological outcome was not influenced by recanalization status. There was no difference in clinical outcome for different sites in VAD, whereas patients with intracranial CAD had severe strokes (NIHSS > 21). CONCLUSIONS: CeAD has good recanalization rates and neurological outcomes, with recanalization seen even in vessels with initial complete occlusion. The presence of hypertension may influence recanalization. The efficacy of dual antiplatelets and heparin for early recanalization needs to be assessed in future clinical 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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".