An Expert Delphi Consensus on Risk Factors for Adverse Events After Endovascular Aortic Aneurysm Repair: Tier 1 Study From the International RIsk Stratification in EVAR (IRIS-EVAR) Working Group
Notice bibliographique
Résumé
PURPOSE: Tier 1 of the International RIsk Stratification in EndoVascular Aneurysm Repair (IRIS-EVAR) project aimed to identify important risk factors for adverse events following endovascular aneurysm repair (EVAR). MATERIALS AND METHODS: Initially, the steering committee proposed a number of risk factors for adverse events following EVAR. A Delphi consensus was performed as expert panelists were presented with risk factors and provided the opportunity to propose additional risk factors during the process. Experts in EVAR completed an online survey via 3 structured rounds. The first round opened in July 2022, and the third round closed in December 2022. Panelists rated risk factors using a 4-point Likert scale. Consensus was defined as >70% of participants agreeing/strongly agreeing or disagreeing/strongly disagreeing with a statement in each round. RESULTS: Thirty-five panelists from 12 countries completed the 3 rounds of surveys. Of a total of 64 individual risk factors assessed by the panelists, 37 (58%) had consensus that they were important for adverse events following EVAR. Risk factors were stratified in 4 domains: 14 (38%) were related to preoperative anatomy, 3 (8%) related to the aortic device selection, 8 (22%) related to the procedure performance, and 12 (32%) related to postoperative surveillance. Factors with the highest consensus in each domain were as follows: proximal aortic neck length <15 mm (98% consensus), anatomy non-compliant with instructions for use (94% consensus), length of achieved proximal aortic neck post implantation <10 mm (98% consensus), and non-satisfactory seal at landing or overlapping zones/sac expansion/kink or stenosis (100% consensus each), respectively. CONCLUSIONS: Clinically important risk factors for adverse events after EVAR were identified via expert consensus. These factors will be used to develop an expert consensus-informed risk stratification and surveillance strategies.Clinical impactThis is the first study to apply an in-depth Delphi methodology to achieve an expert consensus on risk factors for adverse events after endovascular aneurysm repair (EVAR). Important risk factors were stratified in 4 domains: preoperative anatomy (14 factors), aortic device (3 factors), EVAR procedure (8 factors), and postoperative surveillance (12 factors). This study will potentially influence future clinical practice by providing evidence informed by experts regarding predictors of adverse events following EVAR that can be taken into account during decision making and developing post-EVAR surveillance strategies. These findings will inform a risk stratification tool for everyday use by vascular surgeons.
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 | 0,002 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| 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 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 ».