Glenoid preparation in reverse shoulder arthroplasty: robotic arm–assisted preparation compared to manual preparation and patient-specific guides
Notice bibliographique
Résumé
BACKGROUND: Precise and accurate glenoid preparation is important for the success of shoulder arthroplasty. Despite advancements in preoperative planning software and enabling technologies, most surgeons execute the procedure manually. Patient-specific instrumentation (PSI) facilitates accurate glenoid guide pin placement for cannulated reaming; however, few commercially available systems offer depth of reaming control. Robotic arm-assisted bone preparation has gained popularity in knee and hip arthroplasty, but at the present time there is limited information available on the use of robotics for shoulder arthroplasty. The purpose of this study was to compare glenoid preparation and final implant position using 3 techniques: manual, manual assisted with PSI, and robotic arm-assisted bone preparation. METHODS: Six shoulder surgeons participated in this study using 3 preparation techniques: (1) manual reaming, (2) manual reaming over a pin inserted using PSI, and (3) preparation using a robotic arm assist with an end-effector burr and haptic boundaries. Each surgeon randomly conducted each technique on 2 separate Bone Matrix glenoid models, for a total of 36 glenoid models tested. To compare the techniques, the final prepared Bone Matrix models underwent a computed tomographic scan with 3D virtual model generation. The prepared 3D virtual glenoid models were then compared to the preoperatively planned models. Parameters compared included deviations in version, inclination, anterior-posterior (AP) translation, superior-inferior (SI) translation, and depth of reaming. RESULTS: Regarding glenoid version with values reported as mean deviations from the preoperative plan, the robotic-assisted technique (1°) was significantly better than manual (9°, P < .001) and PSI (4°, P < .001) techniques at executing the preoperative plan. Regarding inclination, the robotic-assisted technique (2°) was significantly better than manual (9°, P = .003) but not significantly different than PSI (3°, P = .211). The robotic arm technique, with AP translation, resulted in significantly lower mean displacements (0.3 mm) than the manual technique (2 mm, P = .001) and the PSI technique (2 mm, P = .002). With SI translation, the robotic arm-assisted technique (0.7 mm) resulted in significantly lower mean displacements as compared to the manual (2 mm, P = .007) and PSI (1 mm, P = .011). The robotic arm-assisted technique (0.4 mm) did not result in significantly lower mean depth of reaming displacements compared to the manual technique (0.8 mm, P = .051) but did when compared to PSI (0.8 mm, P = .036). CONCLUSIONS: Glenoid preparation using a robotic arm with an end-effector burr and haptic boundaries was significantly better in its ability to execute a preoperatively planned implant position than manual preparation in 4 of the 5 glenoid metrics examined and was significantly better than PSI in 4 of the 5 glenoid metrics.
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 | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 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) | 0,000 | 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 ».