Real-World Experience With the Angio-Seal Closure Device: Insights From Manufacturer and User Facility Device Experience Database
Notice bibliographique
Résumé
PURPOSE: Angio-Seal (Terumo Medical Corporations, Somerset, New Jersey) device is indicated for femoral arteriotomy closure. Real-world published data on complications are limited. We present 1 year of safety events involving Angio-Seal from the US Food and Drug Administration's post-market surveillance database of Manufacturer and User Facility Device Experience (MAUDE). Steps for managing frequent device-related problems are discussed. MATERIALS AND METHODS: Angio-Seal MAUDE data from November 2019 to December 2020 was classified according to (1) mode of device failure, (2) complication, (3) treatment, and (4) Cardiovascular and Interventional Radiological Society of Europe (CIRSE) adverse event classification system. RESULTS: There were 715 safety events, involving Angio-Seal VIP (93.1%), Evolution (5.7%), STS Plus (1.1%), and sizes 6F (62.5%) and 8F (37.5%). Failure mode involved unrecognized use of a damaged device (43.4%), failed deployment (20.1%), failed arterial advancement (6.3%), detachment of device component (4.9%), failed retraction (3.6%), operator error (1.1%), and indeterminate (20.6%). Of total, 44.8% of events were associated with patient harm. Complications involved minor blood loss (34.1%), hematoma (5.6%), significant blood loss (1.4%), and pseudoaneurysm (1.4%). Of total, 43.3% of cases required manual compression (MC), whereas 8.8% required more advanced intervention. Interventions included surgical repair (49.2%), thrombin injection (9.5%), balloon tamponade (6.3%), covered stent (4.8%), and unspecified (30.2%). Majority of safety events were CIRSE grade 1 (92.0%), followed by grades 2 (3.1%), 3 (4.6%), and 6 (deaths, 0.3%). Minority of devices were returned for manufacturer analysis (27.8%). CONCLUSIONS: The majority of safety events were associated with minor blood loss or local hematoma and could be addressed with MC alone. Most events were attributed to damaged device; however, very few devices were returned to manufacturer for analysis. This should be encouraged to allow for root cause analysis in order to improve safety profile of devices. System-level strategies for addressing barriers to under-reporting of safety events may also be considered.Clinical ImpactOur study highlights important safety events encountered in real-world practice with Angio-Seal closure device. The MAUDE database captures real-world device malfunctions not typically appreciated in conventional clinical trials. Our study provides valuable insight for clinician-users on anticipating and managing the most common device malfunctions. Additionally, our data provide feedback for manufactures to optimize product design and direct manufacturer user training to improve safety. Finally, we hope that the study promotes system-level strategies that foster reporting of safety events and undertaking of root cause analysis.
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 | 0,003 | 0,015 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,002 | 0,002 |
| 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 | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,001 |
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 ».