Abstract T P26: Predictors of Clinical and Angiographic Outcomes in Acute Stroke Treatment: Subgroup Analysis From the Star Study
Bibliographic record
Abstract
Endovascular acute stroke treatment (AIS) has changed dramatically last years. Stent retrievers are progressively substituting other devices and old practices like intra-arterial thrombolysis. We present the subgroup analysis of the largest prospective multicentre study using stent retrievers on the treatment of AIS. The study was realized in 14 high volume and experienced stroke centres in Europe, Canada and Australia. 202 patients harbouring anterior circulation occlusions were included within 8 hours after onset. All procedures were performed with balloon guiding catheter. We observed that the occlusion location did not change the successful (TICI 2b or 3) recanalization rates (ICA - 76.5% and MCA - 86.4%: p=0.187) or good clinical outcomes (mRS 0-2) (ICA - 47.2% and MCA - 61.3%: p=0.137). However, it was significant when we considered excellent (mRS 0-1) outcomes only (ICA - 25% and MCA - 47.5%: p=0.016). There were no differences concerning the previous use of rtPA on the angiographic (TICI scores) (p=1.0) or clinical (mRS) (p=0.564) outcomes. The anaesthetic management also did not influence the revascularization (p=0.7) or patient’s status (p=0.343). Angiographic collateral status determined using the ASITN/SIR grading system was significantly correlated to good clinical outcomes (Grades 0-2 and Grades3-4, p=0.034). Also the time from the stroke onset to groin puncture influence clinical progress (0-3h, 3-4.5h, over 4.5h: p=0.002). Multivariate regression analysis on prediction of good outcomes was significant for age (OR-0.93 (0.89, 0.97)), baseline NIHSS (OR-0.87(0.79, 0.96)), absence of haemorrhage (OR-5.01 (1.65, 15.16)), time to treatment (OR-0.62(0.45-0.83)) procedure performed under conscious sedation (OR4.83(1.78,13.11)) and successful recanalization (OR-3.37(1.12,10.14)). Early and efficient revascularization is ideal situation for AIS. Conscious sedation can save time for endovascular procedure using a stent retriever in experienced centers.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.005 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".