Posterior Circulation Alberta Stroke Program Early Computed Tomography Score (pc-ASPECT) for the Evaluation of Cerebellar Infarcts
Bibliographic record
Abstract
BACKGROUND: Patients with cerebellar ischemic stroke may be misdiagnosed and may exhibit a delayed time to acute stroke treatment compared with patients with anterior circulation ischemic stroke. The posterior circulation Alberta stroke program early computed tomography score (pc-ASPECT) score has been used to evaluate hyperacute stroke, much as the ASPECT in anterior circulation stroke recently. Our main objective was to evaluate the associations of the clinical and etiological characteristics of ischemic cerebellar infarction patients on admission with their pc-ASPECT scores, as well as the correlations of the pc-ASPECT score with morbidity and mortality rates. MATERIALS AND METHODS: We include 114 patients with cerebellar infarction who underwent 1 year of follow-up into the study. RESULTS: Patients with a pc-ASPECT score <7 were more likely to present with impaired consciousness ( P <0.001), multiple posterior circulation infarcts ( P <0.001), hydrocephalus ( P <0.001), lesions of the vermis ( P =0.028), and peduncle ( P =0.024), perfusion deficits in the total of posterior inferior cerebellar artery, anterior inferior cerebellar artery, superior cerebellar artery ( P <0.05), and basilar artery stenosis ( P =0.005), ischemia in additional anatomical structures in the posterior circulation ( P <0.001) compared with those with a score ≥7. CONCLUSIONS: Although the pc-ASPECT score alone is insufficient in some cases like vertebral artery dissection, using it together with the National Institutes of Health Stroke Scale (NIHSS) score and clinical findings may be beneficial during the hyperacute period of cerebellar ischemia. Presentation with impaired consciousness, basilar artery pathologies, vermian ischemia, and ischemia in additional anatomical structures in the posterior circulation other than the cerebellum appeared as important clinical and radiologic parameters predicting long-term prognosis.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".