Perfusion computed tomography and clinical status of patients with acute ischaemic stroke.
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: There is increasing availability of perfusion computed tomography (PCT) for assessment of acute ischaemic stroke patients. A semiquantitative evaluation of CT scans can be easily and quickly performed by the examining physician. In the current study, we investigated the correlation between the Alberta Stroke Program Early CT Score (ASPECTS) quantifying acute ischaemic changes on CT scans and clinical status of ischaemic stroke patients. MATERIAL AND METHODS: We analyzed the data of 34 patients with hemispheric ischaemic stroke, in whom both non-contrast CT (NCCT) and PCT were performed within 12 hours after stroke onset. NCCT and PCT [colour-coded maps of cerebral blood flow (CBF), cerebral blood volume (CBV), and time-to-peak (TTP)] were evaluated using ASPECTS. The correlations between ASPECTS and severity of neurological deficit, and prognostic value of ASPECTS for long-term clinical outcome were studied. RESULTS: We found a significant correlation between the baseline clinical status and ASPECTS for all CT techniques as well as between CBV and neurological deficit at discharge. ASPECTS ł7 in all CT techniques had a high sensitivity and positive predictive value for prognosis of 3-month functional independency. CONCLUSIONS: ASPECTS used for PCT and NCCT shows a good correlation with clinical status and prognosis of ischaemic stroke patients.
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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 | 0.001 |
| 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) | 0.001 | 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".