CORR Insights®: Revisions of Monoblock Metal-on-metal THAs Have High Early Complication Rates
Notice bibliographique
Résumé
Where Are We Now? Attempts to address the limitations of early metal-on-polyethylene (MoP) bearings, well outlined in the introduction of this paper, have historically followed two different approaches. The first approach concentrated on improving the materials and design of MoP articulations, with reductions in wear and resultant osteolysis. The second approach abandons polyethylene altogether, and seeks alternative bearing materials such as the metal-on metal (MoM) bearings described in this study. In retrospect, it was somewhat simplistic to presume that the improved wear characteristics of MoM bearings would occur without some disadvantages. Early failure rates are well documented [1], complicated by an incompletely understood potential for aggressive bone and soft tissue reaction [2, 3] rarely seen with MoP. The clinical importance of metal ion concentrations is another concern [1], which was beyond the scope of this study. Rather, the current manuscript provided important insight into the frequency of early complications and factors contributing to failure. Where Do We Need To Go? It is clear that understanding the factors and mechanisms involved in these early failures is critical. Patient, design, and material factors contributing to failure (and success) can be identified from retrospectively collected data. The minimum 2-year followup guideline for publication of clinical results should be waived (as in this series) when issues and failures arise. The timing of when to introduce new technology into patient care always a difficult and complex decision, but in the future, consideration for longer-term preclinical trials may be an option. Stryker and colleagues stressed the challenges associated with revision of the failed hips in this case series, which should be a major factor surgeons should consider when selecting THA bearings. As with all bearing couples, a complete understanding of the in vivo response, and its clinical impact to the patient, must be considered. This an area of intense study at many centers and answers will surely be forthcoming. How Do We Get There? There is no substitute for quality data obtained from long-term followup studies. Only with such information can failures be identified, understood, and avoided in the future. The unfortunate situation documented in this series is that the failures resulting in revision occurred early. This is the most worrisome scenario for arthroplasty surgeons. Registry data are essential for many reasons, but information from registries about the pathogenesis of failure is by its nature limited. When dealing with a potentially serious biologic response as in MoM bearings, detailed case series will be required, which should provide detailed radiographic review, likely MR evaluation, tissue sampling, metal ion levels, and any other analyses that can help surgeons and scientists understand - and we hope, prevent - future problems.
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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 | 0,002 | 0,019 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,002 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,031 | 0,014 |
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 ».