Computed tomography perfusion-defined ischemic core predicts functional outcome after basilar artery thrombectomy
Bibliographic record
Abstract
Purpose This study aimed to determine the optimal threshold for computed tomography perfusion (CTP)-defined ischemic core in patients with basilar artery occlusion (BAO) that predicts functional outcome. Methods A retrospective analysis was conducted on BAO patients who underwent endovascular thrombectomy at our stroke center between January 2018 and March 2024. Ischemic core was estimated using following thresholds: cerebral blood flow (CBF) < 10 or 15 mL/100 g/min by Syngo.via, cerebral blood volume < 1.2 mL/100 mL by Syngo.via, and time to maximum (Tmax) > 10 s by RAPID. A favorable functional outcome was defined as a modified Rankin Scale score of 0–3 at 90-day post-onset. The Posterior Circulation Alberta Stroke Program Early computed tomography Score (pc-ASPECTS) was semi-quantified to assess ischemic changes. Statistical analysis included intraclass correlation coefficient (ICC) and receiver operating characteristic analyses. Results A total of 85 patients were enrolled, and 39 (45.9%) had a favorable functional outcome. The ICC for pc-ASPECTS based on four core approaches between junior and senior observers ranged from 0.90 to 0.96. For the classification of favorable outcome, the volume and pc-ASPECTS core estimation approach (CBF < 10 mL/100 g/min by Syngo.via) had the best performance, with the largest area under the curve of 0.86 [(95% confidence intervals, 0.78–0.94); p < 0.001] and 0.87 [(95% confidence intervals, 0.80–0.94); p < 0.001], with a cut-off value of ≤ 2.2 (78.3%% sensitivity, 84.6% specificity), and ≥ 7 (92.3% sensitivity, 65.2% specificity). Conclusion In BAO patients following successful recanalization, the volume and pc-ASPECTS core estimation approach (CBF < 10 mL/100 g/min by Syngo.via) demonstrated the strongest predictive value for favorable functional outcomes.
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 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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".