Prediction of Infarct Growth and Neurological Deterioration in Patients with Vertebrobasilar Artery Occlusions
Bibliographic record
Abstract
We aimed to identify predictors of infarct growth and neurological deterioration (ND) in vertebrobasilar occlusions (VBOs) with a focus on clinical-core mismatch. From 2010 to 2018, VBO patients were selected from a university hospital registry. In total, 138 VBO patients were included. In these patients, a posterior circulation Alberta Stroke Program Early CT score (PC-ASPECTS) less than 6 was associated with futile outcome. Within patients with feasible cores, a decrease in PC-ASPECTS score of 2 or more on follow-up imaging was classified as infarct growth and could be predicted by a National Institutes of Health Stroke Scale (NIHSS) mental status subset of 1 or higher (odds ratio (OR): 3.34, 95% confidence interval (CI) (1.19–9.38), p = 0.022). Among the 73 patients who did not undergo reperfusion therapy, 13 patients experienced ND (increase in discharge NIHSS score of 4 or more compared to the initial presentation). Incomplete occlusion (vs. complete occlusion, OR 6.17, 95% CI (1.11–34.25), p = 0.037), poorer collateral status (BATMAN score, OR: 1.91, 95% CI (1.17–3.48), p = 0.009), and larger infarct cores (PC-ASPECTS, OR: 1.96, 95% CI (1.11–3.48), p = 0.021) were predictive of ND. In patients with VBO, an initial PC-ASPECTS of 6 or more, but with a decrease in the mental status subset of 1 or more can predict infarct growth, and may be used as a criterion for clinical-core mismatch. ND in VBO patients presenting with milder symptoms can be predicted by incomplete occlusion, poor collaterals, and larger infarct cores.
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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 | 0.000 | 0.003 |
| 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 | 0.001 | 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".