ASPECTS evolution after endovascular successful reperfusion in the early and extended time window
Bibliographic record
Abstract
BackgroundThe Alberta Stroke Program Early CT scan Score (ASPECTS) is a reliable imaging biomarker of infarct extent on admission but the value of 24-hour ASPECTS evolution in day-to-day practice is not well studied, especially after successful reperfusion. We aimed to assess the association between ASPECTS evolution after successful reperfusion with functional and safety outcomes, as well as to identify the predictors of ASPECTS evolution.MethodsWe used data from an ongoing prospective multicenter registry. Stroke patients with anterior circulation large vessel occlusion treated with endovascular therapy (EVT) and achieved successful reperfusion (modified thrombolysis in cerebral ischemia (mTICI) 2b-3) were included. ASPECTS evolution was defined as one or more point decrease in ASPECTS at 24 hours.ResultsA total of 2366 patients were enrolled. In a fully adjusted model, ASPECTS evolution was associated with lower odds of favorable outcome (modified Rankin Scale (mRS) score 0-2) at 90 days (adjusted odds ratio (aOR) = 0.46; 95% confidence interval (CI) = 0.37-0.57). In addition, ASPECTS evolution was a predictor of excellent outcome (90-day mRS 0-1) (aOR = 0.52; 95% CI = 0.49-0.57), early neurological improvement (aOR = 0.42; 95% CI = 0.35-0.51), and parenchymal hemorrhage (aOR = 2.64; 95% CI, 2.03-3.44). Stroke severity, admission ASPECTS, total number of passes, complete reperfusion (mTICI 3 vs. mTICI 2b-2c) and good collaterals emerged as predictors of ASPECTS evolution.ConclusionASPECTS evolution is a strong predictor of functional and safety outcomes after successful endovascular therapy. Higher number of EVT attempts and incomplete reperfusion are associated with ASPECTS evolution at day 1.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".