O-001 Pre-treatment CTA ASPECTS as a predictor of clinical outcome in endovascular stroke therapy (EVT): results from the penumbra START trial
Notice bibliographique
Résumé
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.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,003 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,002 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».