Correlation of Alberta Stroke Program Early Computed Tomography (CT) Score Among Ischaemic Stroke Patients and Their Outcomes at Selected Centres in Kampala: A Prospective Study
Bibliographic record
Abstract
Background Stroke contributes significantly to morbidity and is the second leading cause of death globally. The Alberta Stroke Program Early Computed Tomography (ASPECT) Score, a 10-point scoring system with anatomical regions of the brain over the middle cerebral artery (MCA) territory, is used to assess early ischaemic changes on a non-contrast computed tomography scan (NCCT) of the head. It is used as a predictor of functional outcome and in the stratification of ischaemic stroke patients' treatment to guide reperfusion and non-thrombolytic management. This study aimed to determine the correlation between the ASPECTS and the outcomes of ischaemic stroke patients in Kampala, Uganda. Methods This was a prospective study carried out at three selected centres. All patients diagnosed with ischaemic stroke involving the MCA underwent NCCT of the head to determine the ASPECTS. Enrolled participants were index admissions to the hospital following the symptoms and signs of stroke. Patient demographics, clinical presenting complaints, Glasgow Coma Scale (GCS), comorbidities, and medical and treatment history for individual patients were documented in the data collection tool. Study patients were recruited consecutively and followed up one month later using the Modified Rankin Scale (mRS). The participants' outcomes were described as favourable outcomes and poor outcomes. Spearman correlation analysis was carried out to measure the strength and direction of association between ASPECTS and mRS. Results The average ASPECTS score was 5.71, SD ± 3.4, with a left hemisphere predilection. There was a significant inverse correlation between ASPECTS and mRS scores (r = -0.618, p < 0.001). 17% (n=20) had favourable outcomes (mRS, 0-2), whereas 83.1% (n=98) had poor outcomes (mRS, ≥3) with 26.27% mortality. Poor outcomes among patients were associated with overall lower ASPECTS, no education, low GCS at admission, involvement of M3 and M5 brain regions and additional vascular territory-posterior cerebral artery involvement. Conclusion The inverse correlation between the ASPECTS and mRS seen in this study highlights the value of the ASPECTS as a reliable tool to predict functional outcomes in ischaemic stroke patients. The poor outcomes observed reflect the need to utilise the ASPECTS to ensure appropriate timely interventions and rehabilitation and for individualised stroke protocols in our hospitals to initiate thrombolytic and thrombectomy therapy.
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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) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| 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".