Efficacy of Computer-Aided Design and Manufacturing Versus Computer-Aided Design and Finite Element Modeling Technologies in Brace Management of Idiopathic Scoliosis: A Narrative Review
Notice bibliographique
Résumé
The efficiency and design quality of scoliosis braces produced by the conventional casting method depends highly on the orthotist's experience. Recently, advanced engineering techniques have been used with the aim of improving the quality of brace design and associated clinical outcomes. Numerically controlled machine tools have provided enormous opportunities for reducing the manufacturing time and saving material. However, the effectiveness of computer-aided brace manufacturing for scoliosis curve improvement is controversial. This narrative review is aimed at comparing the efficacy of braces made by the conventional method with those made by two computer-aided methods: computer-aided design and manufacturing (CAD-CAM), and computer-aided design and finite element modeling (CAD-FEM). The comparison was performed on scoliosis parameters in coronal, sagittal, and transverse planes. Scientific databases were searched, and 11 studies were selected for this review. Because of the diversity of study designs, it was not possible to decisively conclude which brace-manufacturing method is most effective. Similar effectiveness in curve correction was found in the coronal plane for braces made by using advanced manufacturing and conventional methods. In the sagittal plane, modern braces seem to be more effective than traditional braces, but there is an ongoing debate among clinicians, about which CAD-CAM and CAD-FEM brace provides a better treatment outcome. The relative effectiveness of modern and conventional methods in correcting deformities in the transverse plane is also a controversial subject. Overall, advanced engineering design and production methods can be proposed as time- and cost-efficient approaches for scoliosis management. However, there is insufficient evidence yet to conclude that CAD-CAM, and CAD-FEM methods provide significantly better clinical outcomes than those of conventional methods in the treatment of scoliosis curve. Moreover, for some factors, such as molding and the patient's posture during the data acquisition, in brace curve-correction plan, the orthotist's experience and scoliosis curve flexibility should be explored to confidently compare the outcomes of conventional, CAD-CAM, and CAD-FEM methods.
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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 | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,004 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| 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 ».