An Acute Ischemic Stroke Classification Instrument That Includes CT or MR Angiography: The Boston Acute Stroke Imaging Scale
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: A simple classification instrument based on imaging that predicts outcomes in patients with acute ischemic stroke is lacking. We tested the hypotheses that the Boston Acute Stroke Imaging Scale (BASIS) classification instrument effectively predicts patient outcomes and is superior to the Alberta Stroke Program Early CT Score (ASPECTS) in predicting outcomes in acute ischemic stroke. MATERIALS AND METHODS: Of 230 prospectively screened, consecutive patients with acute ischemic stroke, 87 had noncontrast CT (NCCT)/CT angiography (CTA), and 118 had MR imaging/MR angiography (MRA) at admission and were classified as having major stroke by BASIS criteria if they had a proximal cerebral artery occlusion or, if no occlusion, imaging evidence of significant parenchymal ischemia; all of the others were classified as minor strokes. Outcomes included death, length of hospitalization, and discharge disposition. BASIS was compared with ASPECTS (dichotomized > or <or=7) in 87 patients who had NCCT/CTA. RESULTS: BASIS classification by NCCT/CTA was equivalent to MR imaging/MRA. Fifty-six of 205 patients were classified as having major strokes including all 6 of the deaths. A total of 71.4% and 15.4% of major and minor stroke survivors, respectively, were discharged to a rehabilitation facility, whereas 14.3% and 79.2% of patients with major and minor strokes were discharged to home. The mean length of hospitalization was 12.3 and 3.3 days for the major and minor stroke groups, respectively (all outcomes, P < .0001). In 87 NCCT/CTA patients, BASIS and ASPECTS agreed in 22 major and 44 minor strokes. BASIS classified 21 patients as having major strokes who were classified as having minor strokes by ASPECTS. The BASIS major/ASPECTS minor stroke group had outcomes similar to those classified as major strokes by both instruments. CONCLUSIONS: The BASIS classification instrument is effective and appears superior to ASPECTS in predicting outcomes in acute ischemic stroke.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".