E-033 Current international practice patterns in endovascular techniques used in the treatment of cerebral venous thrombosis
Notice bibliographique
Résumé
Introduction Cerebral venous thrombosis (CVT) accounts for approximately 0.5–1% of all strokes. Current treatment for CVT is consensus guided, with unfractionated or low-molecular-weight heparin recommended in the acute management. The role of endovascular therapy (EVT) is less well-defined. A randomized trial, TO-ACT, and a propensity score analysis from the ACTION-CVT trial did not demonstrate a survival or functional benefit for EVT in CVT. Decision-making around EVT in the treatment of CVT remains case-by-case and current practice patterns are not well known. Therefore, we sought to characterize current international practice patterns for EVT in CVT, and explore regional variability. Methods A comprehensive survey was distributed to stroke physicians, interventional neurologists, interventional neuroradiologists, and endovascular neurosurgeons through local networks and professional societies in 2023. The 53-question survey asked about practice patterns and EVT techniques used in the management of CVT. Results Overall, 863 physicians completed the survey with a response rate of 31.4%. Herein, we present data from the 299 neurointerventionalists respondents comprising 158 (52.8%) interventional neurologists, 97 (32.4%) interventional neuroradiologists, 28 (9.4%) endovascular neurosurgeons, and 16 (5.4%) interventional radiologists completed the survey. Respondents were predominantly male (82.6%) and practicing in an academic hospital with a comprehensive stroke center (73.6%). Respondents practiced in North America (12.7%), Asia (58.9%), Europe (25.1%), South America (1.7%), Africa (1.0%) and Oceania (0.7%). In the past three years, 61.9% of respondents performed EVT for the treatment of CVT. Most respondents had performed 2 to 5 cases (51.9%), while only 8.6% had performed more than 10 cases in the past three years. The majority of respondents (85.6%) felt the superficial dural sinuses were amenable to intervention, 34.1% felt the deep venous sinuses were amenable and 9.4% perceived the superficial cortical veins were amenable. Mechanical thrombectomy with aspiration was the most utilized technique with 56.2% of respondents using it in the past three years. The other most utilized techniques were mechanical thrombectomy with stent retriever (50.5%), direct thrombolysis with tissue plasminogen activator (33.4%), direct administration of heparin (32.8%) and balloon angioplasty (23.4%). There was significant regional variability in the EVT techniques used (p<0.001). Direct administration of heparin was more common in Asia, with 46.6% respondents in Asia reporting its use in the past three years. Mechanical thrombectomy with stent retriever or aspiration, and thrombus maceration with wire, were used less commonly in Asia compared to North American and European neurointerventionalists. Eighty percent of neurointerventionalists agreed that in certain situations, EVT was superior to standard medical management of CVT, and 72.6% supported future trials of EVT in the management of CVT. Conclusions In our international survey, more than half of neurointerventionalists have treated CVT with endovascular therapy in the past three years. Mechanical thrombectomy with aspiration or stent retriever are the most commonly used techniques, however, there is regional variability. Overall, the use of endovascular therapy in the management of CVT is rare. These data may inform the design of future clinical trials to guide practice. Disclosures A. Rebchuk: None. B. Brakel: None. J. Ospel: None. Y. Chen: None. M. Heran: None. M. Goyal: None. M. Hill: None. Z. Miao: None. X. Huo: None. Y. Chen: None. S. Sacco: None. S. Yaghi: None. M. Ton: None. G. Thomalla: 2; C; Acandis, Alexion, Amarin, Astra Zeneca, Bayer, Boehringer Igelheim, BristolMyersSquibb/Pfizer, Daiichi Sanyo, Stryker. G. Boulouis: None. H. Yamagami: 1; C; Bristol-Myers Squibb. 3; C; Stryker, Medtronic, J&J, Bayer, Daiichi Sankyo, Bristol-Myers Squibb, Otuska Pharmaceutical. W. Hu: None. S. Nagel: 2; C; Brainomix. 3; C; Boehringer Ingelheim, Pfizer. V. Puetz: None. E. Kristoffersen: None. J. Demeestere: None. Z. Qiu: None. M. Abdalkader: None. S. Al Kasab: None. J. Siegler: 1; C; National Institutes of Health (R61NS135583). 2; C; AstraZeneca. 6; C; Philips, Viz.ai, Philips, Medtronic. D. Strbian: 1; C; Boehringer Ingelheim. 2; C; Orion, Herantis Pharma, CSL Behring. 6; C; Boehringer Ingelheim, Alexion/Astra Zeneca, BMS/Janssen. U. Fischer: 1; C; Medtronic, Stryker, Rapid medical, Penumbra, Boehringer Ingelheim. 2; C; Medtronic, Stryker, CSL Behring. 3; C; Alexion/Portola, Boehringer Ingelheim, Biogen, Acthera. J. Coutinho: 1; C; Bayer, Astrazeneca. 4; C; TrianecT. A. Munckhof: None. D. de Sousa: None. B. Campbell: None. J. Raymond: None. X. Ji: None. G. Saposnik: None. T. Nguyen: 2; C; Brainomix. T. Field: None.
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 machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,008 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,003 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,031 | 0,007 |
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 source (Gemma direct ou Codex distillé), 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 ».