Understanding Aneurysm Coiling in Practice: A Delphi Inquiry into Expert Perception
Notice bibliographique
Résumé
Introduction and Aims Cerebral aneurysm coiling, a prominent procedure under the neurointerventional angiography umbrella, is a challenging endovascular technique requiring significant hands‐on clinical training. As part of the mandatory angiography fellowship, trainees learn and practice complex skills within the walls of the operating theatre (Angio Suite), guided by expert interventionalists. Unfortunately, training assessment is currently limited to subjective scales and quantity of clinical exposure, rather than tested objective criteria adopted in other medical specialties. In order to advance training in this field, objective methods of assessments need to be created, validated and applied to available training systems. However, a representative schema of performed tasks and events in aneurysm coiling needs to be assembled in preparing new assessment methods. Methods A multiple‐phase Delphi assessment was distributed via Survey Monkey to the Canadian Interventional Neuro Group (CING). A total of 85 expert interventionalists were quired on their perception of the importance, frequency and severity of core steps and errors in cerebral angiography and aneurysm coiling. Participants were provided with opportunities to provide feedback on the accuracy of the steps. Questions containing feedback or discrepancy in outcomes were reformatted and resubmitted to active participants in the next phase for clarification. Once an agreement is achieved across the entire procedural spectrum, results are redistributed to all parties and data collection is completed. Results and Discussion A total of 21 experts responded to the survey, with 13 completing the survey in full. The most important steps pertained to the aneurysm coiling stage, with the most disagreement revolving around techniques in femoral artery puncture and catherization of the aorta. The highest frequency of errors was reported during the advancement of gauge and starter wire at the start of the procedure, and inconsistent flushing of the endovascular space. The lowest frequency of errors was found to be during aneurysm coiling. Severity of possible errors climbed throughout the procedure, with the highest scores seen in microcatheter advancement and coil deployment within the aneurysm. These results identify areas of training that are exposed to the highest level of risk (eg. steps within the aneurysm coiling stage) or highest rate of error (eg. aortic and supra‐aortic catherization). The next phase of the study will reassess divergence of scores through step ranking and account for individual expert comments. The results will be essential in shaping the methodology of an Angio Suite‐based procedural workflow assessment and subsequent development of an objective training and assessment protocol. Support or Funding Information There are no conflicts of interest to disclose. This research was partly funded by the Canadian Institutes of Health Research (CIHR) Frederick Banting and Charles Best Canada Graduate Scholarships Doctoral Award (CGS‐D). This abstract is from the Experimental Biology 2019 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .
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 | 0,066 | 0,062 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,004 | 0,002 |
| Études des sciences et des technologies | 0,007 | 0,010 |
| Communication savante | 0,006 | 0,005 |
| Science ouverte | 0,002 | 0,011 |
| Intégrité de la recherche | 0,003 | 0,004 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 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 ».