EARLY PREDICTION OF ACUTE ISCHEMIC STROKE OUTCOME BY USING ALBERTA STROKE PROGRAM EARLY CT SCORE (ASPECTS)
Bibliographic record
Abstract
Background and Purpose: The Alberta Stroke Program Early CT Score (ASPECTS) scale semiquantitatively assesses extent and location of ischemic changes within the middle cerebral artery (MCA) territory using a 10-point grading system. ASPECTS measured at baseline using noncontrast computed tomography (CT) scan. The aim of this study was to assess early prediction of clinical outcome after acute ischemic stroke by ASPECTS scale. Methods: The study based on convenience sample which included 82 first-ever acute ischemic stroke patients, admitted to Hue Central Hospital within 72 hours of stroke onset, from October 2013 to October 2014. Ischemic territory changes were defined as parenchymal CT hypoattenuation. We assessed all baseline CT scans, dichotomized ASPECTS at ≤ 7 and >7, defined good outcome (0 to 2) and poor outcome (3 to 6) as modified Rankin Scale (mRS) score at discharge. Univariate analysis and multivariable logistic regression analysis were performed to define the independent predictors for stroke outcome. Results: Mean age was 68.35 ± 13.93 years, proportion of male (51.2%) and female (48.8%) are approximately the same. ASPECTS score > 7 in 57 patients and ≤ 7 in 25 patients. Mean ASPECTS was 7.51 ± 2.25. Mean mRS at discharge was 2.28 ± 1.33. Good outcome (mRS ≤ 2) and poor outcome (mRS > 2) at discharge were 63.4% and 36.6% respectively. There is a negative correlation between ASPECTS and mRS (r = -0.86, p < 0.001). In the univariate analysis, atrial fibrillation, Glasgow Coma Scale (GCS) score at admisison, ASPECT score and infarct volume were significantly associated with stroke outcome. All of aforementioned variables underwent multivariate analysis, but none of them was proven to be an independent predictor of early outcome. Conclusion: In patients with first-ever acute ischemic stroke, ASPECT score which bases on conventional computed tomography scan is not independent predictor for clinical outcome at discharge. Key words: ischemic stroke, ASPECTS, outcome
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| 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".