ASPECTS and Functional Outcomes in Left versus Right Hemisphere Strokes: A Prospective Cohort Study
Bibliographic record
Abstract
Background: Stroke presents as the second most prominent factor contributing to global mortality. Immediate brain imaging can be valuable for assessing functional recovery potential. This study investigated the association between Alberta Stroke Program Early CT Score (ASPECTS) and functional outcomes in patients with left and right-hemisphere strokes. Methods: A prospective cohort study was conducted in July-Dec2 022, at a tertiary care hospital in Karachi including patients of either gender presenting within 2 days of stroke while excluding posterior circulation strokes, TIA & unwilling patients using a non-probability consecutive sampling technique. A total of 152 patients with acute ischemic stroke involving anterior circulation were analyzed and patients were categorized into two groups: the left hemisphere group (n=76) and the right hemisphere group (n=76) accordingly. ASPECTS scores were calculated from brain CT scans, while functional outcomes were measured using the modified Rankin Scale (mRS) at the three-month mark. Descriptive analysis and chi-square test were applied using SPSS vr25. Results: Patients (n=152) had a mean age of 61.75 ± 13 years, with males comprising 67% of the cohort. ASPECTS scores were notably higher in left hemisphere strokes (median 9, IQR 2) than right hemisphere strokes (median 8, IQR 3) (p=0.036). Higher ASPECTS scores (≥7) correlated with improved outcomes (mRS ≤2) in both hemispheres. There was no statistically significant difference in both groups’ functional outcomes (p=0.182). Conclusion: ASPECTS predicts functional outcomes in acute ischemic strokes equally well regardless of the affected hemisphere.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".