O-001 Pre-treatment CTA ASPECTS as a predictor of clinical outcome in endovascular stroke therapy (EVT): results from the penumbra START trial
Bibliographic record
Abstract
Introduction/purpose There is no standard imaging approach for EVT patient selection. CT remains the most widely used modality for stroke evaluation. Ischemic change on non-contrast CT (NCCT) quantified using ASPECTS has been demonstrated to predict clinical response to EVT. To date, definitive studies evaluating the impact of CTA source image (CTA-SI) pre-treatment ASPECTS (pre-ASPECTS) on outcomes following EVT are lacking. START was a prospective, multicenter study to evaluate the influence of pre-treatment core infarct size in patients undergoing endovascular stroke therapy using the Penumbra System. Materials and Methods The imaging method was at each center's discretion and included NCCT, CTA-SI, CT perfusion, or MRI diffusion imaging. This study focused on the preliminary CTA-SI results. Results are reported from an interim analysis of the START trial data as adjudicated by a central Core Laboratory. Graded in a blinded fashion, ASPECTS was analyzed according to the a priori classification (0–4, 5–7, 8–10), as well as using the entire scale. Clinical outcomes were dichotomized as 90-day modified Rankin Scale scores of 0–2 (good) vs 3–6. Univariate and multivariate analyses were performed to determine predictors of outcome. Results Of the 147 patients enrolled, 77 met study criteria for this interim analysis. The mean age was 66.0±14.1 years; median NIHSS was 19 (14–24). Target vessel occlusions were in the ICA (22.1%), MCA (75.3%), and other (2.6%). The median pre-ASPECTS on CTA-SI was 6 (4–7). There were 20 (26%) patients with scores of 0–4, 43 (55.8%) with 5–7, 14 (18.2%) with 8–10. The rate of TIMI 2–3 revascularization was 85.3% (64/75). The median time from groin puncture to aspiration discontinuation was 71.5 (40–108) min. 37 (48.1%) patients achieved a good 90-day outcome. 22 (28.6%) died. Four (5.2%) patients suffered from symptomatic hemorrhage, and 11 (14.3%) suffered from asymptomatic hemorrhage. Higher pre-ASPECTS on CTA-SI was significantly associated with good outcomes (median 6 (IQR 5–7) vs 5 (IQR 3–7), p<0.05). The rate of good outcomes was 20.0% for ASPECTS 0–4, 55.8% for 5–7, and 64.3% for 8–10 (p=0.08). Adjusting for age and NIHSS and comparing ASPECTS 0–4 with 5–10, pre-ASPECTS 5–10 was an independent predictor of good outcome (OR 6.8, p=0.006). In ROC analysis, ASPECTS >4 was the optimal threshold for identifying good outcomes (89% sensitivity, 38% specificity). Other univariate predictors of good outcome were lower age (p=0.01), lower NIHSS (p=0.04), revascularization time (p<0.0001), and shorter time from groin puncture to aspiration cessation (p=0.0004). Conclusion Higher pre-treatment ASPECTS on CTA source images are associated with better outcomes following EVT. Comparative studies with NCCT ASPECTS are required to evaluate relative accuracy for patient selection. Competing interests D Frei: None. A Yoo: None. D Heck: None. F Hellinger II: None. V McCollom: None. D Fiorella: None. A Turk III: None. T Malisch: None. O Zaidat: None. M Alexander: None. T Devlin: None. E Levy: None. Q Shah: None. F Hui: None. M Goyal: None. B Ghodke: None. A Shaibani: None. M Harrigan: None. T Jovin: None. M Madison: None. Z Chaudhry: None. R Gonzalez: None. L Barraza: Penumbra, Inc. S Sit: Penumbra, Inc. A Bose: Penumbra, Inc.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| 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) | 0.001 | 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 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".