Abstract TP52: Comparison of Two Methods of the Alberta Stroke Program Early CT Score
Bibliographic record
Abstract
Introduction: Alberta Stroke Program Early CT Score (ASPECTS) is a validated clinical tool to predict early ischemic changes in acute ischemic stroke (AIS). In addition to scoring of non-contrast brain CT images (CT), head CT angiogram source images (CTA) have also been demonstrated as useful for scoring. We hypothesized that CTA ASPECTS would show superior inter-rater reliability as compared to CT ASPECTS, and that both would perform better in the setting of the favorable target mismatch (TM) profile on CT perfusion imaging (CTP). Methods: We reviewed AIS patients from 2010-2014 with an acute M1 middle cerebral artery occlusion that underwent CT, CTA, and CTP imaging at hospital admission. CT and CTA were independently scored by two experienced physician raters using the standard ASPECTS methodology. Inter-rater agreement was calculated with a weighted kappa. The cohort was then further stratified into either favorable or non-favorable TM profiles using volumetric measurements from the Olea Sphere software and the DEFUSE-3 definition of TM. Results: We included 68 patients. The mean±SD age was 62±18 years. 60% were men. The mean NIH stroke scale was 14.5±7.9. The median (IQR) follow-up modified Rankin Scale (mRS) was 3 (1,6). 37 of 68 (54%) patients had the TM profile and were significantly more likely to have lower follow-up mRS scores (z=3.5, p<0.001). Inter-rater agreement of CTA ASPECTS (kappa=0.82) was superior to CT ASPECTS (kappa=0.76). Patients with the TM profile demonstrated more reliable agreement on both CTA and CT ASPECTS scoring systems (kappa=0.79, 0.78), compared to those without the TM profile (kappa=0.71, 0.75). Discussion: We found that inter-rater agreement was higher for CTA ASPECTS as compared to CT ASPECTS and that both performed better in patents with the TM profile. Clinically this is important because it reaffirms the utility of CTA ASPECTS in this population of patients in which high reliability is paramount, as ASPECTS is often used in medical decision making when determining eligibility for medical and/or endovascular thrombolytic therapies.
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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 | 0.012 | 0.046 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".