Current Total Knee Designs: Does Baseplate Roughness or Locking Mechanism Design Affect Polyethylene Backside Wear?
Notice bibliographique
Résumé
BACKGROUND: Tibial baseplate roughness and polyethylene-insert micromotion resulting from locking-mechanism loosening can lead to polyethylene backside wear in TKAs. However, many retrieval studies examining these variables have evaluated only older TKA implant designs. QUESTIONS: We used implant-retrieval analysis to examine if there were differences in: (1) backside damage scores, (2) backside damage modes, and (3) backside linear wear rates in five TKA implant designs owing to differing baseplate surface roughness and locking mechanisms. Additionally, we examined if (4) patient demographics influence backside damage and wear. METHODS: Five TKA implant models (four modern and one historical design) were selected with different tibial baseplate and/or locking mechanism designs. Six tibial inserts retrieved at the time of revision from each TKA model were matched for time in vivo, age of the patient at TKA revision, BMI, sex, revision number, and revision reason. Each insert backside was analyzed for: (1) visual total damage score and (2) individual visual damage modes, both by two observers and with an intraclass correlation coefficient of 0.66 (95% CI, 0.39-0.92), and (3) linear wear rate measured by micro-CT. Median primary outcomes were compared among the five designs. For our given sample size among five groups we could detect with 80% power a 10-point difference in damage score and an 0.11-mm per year difference in wear rate. RESULTS: The polished tibial design with a partial peripheral capture locking mechanism and anterior constraint showed a lower total damage score compared with the nonpolished tibial design with only a complete peripheral-rim locking mechanism (median, 12.5; range, 9.5-18.0; 95% CI, 9.58-16.42 versus median, 22.3; range, 15.5-27.0; 95% CI, 17.5-26.5; p = 0.019). The polished baseplate with a tongue-in-groove locking mechanism showed more abrasions than the nonpolished baseplate with a peripheral-rim capture and antirotational island (median, 7.25; range, 0.5-8.0; 95% CI, 2.67-8.99 versus median, 0.75; range, 0-1.5; 95% CI, 0.20-1.47; p = 0.016)). Dimpling was a unique wear mode to the nonpolished baseplates with the peripheral-rim capture and antirotational island (median, 5.5; range, 2.0-9.0; 95% CI, 2.96-8.38) and the peripheral-rim capture alone (median, 9.0; range, 6.0-10.0; 95% CI, 7.29-10.38). Overall, the linear wear rate for polished designs was lower than for nonpolished designs (0.0102 ± 0.0044 mm/year versus 0.0224 ± 0.0119 mm/year; p < 0.001). Two of the polished baseplate designs, the partial peripheral capture with anterior constraint (median, 0.083 mm/year; range, 0.0037-0.0111 mm/year; 95% CI, 0.0050-0.0107 mm versus median, 0.0245 mm/year; range, 0.014-0.046 mm/year; 95% CI, 0.0130-0.0414 mm; p = 0.008) and the tongue-in-groove locking mechanism (median, 0.0085 mm/year; range, 0.005-0.015 mm/year; 95% CI, 0.0045-0.0138 mm; p = 0.032) showed lower polyethylene linear wear rates compared with the nonpolished baseplate design with only a peripheral-rim capture. CONCLUSIONS: Total damage scores and linear wear rates were highest involving the nonpolished design with only a peripheral rim capture. There were no differences among the other TKA designs regarding damage and wear, but this finding should be considered in the setting of a relatively small sample size. CLINICAL RELEVANCE: Our study showed that in the complex interplay between baseplate surface finish and locking mechanism design, a polished baseplate with a robust locking mechanism had the lowest backside damage and linear wear. However, improvements in locking mechanism design in nonpolished baseplates potentially may offset some advantages of a polished baseplate. Further retrieval analyses need to be done to confirm such findings, especially analyzing current crosslinked polyethylene. Additionally, we need mid- and long-term studies comparing TKA revisions attributable to wear and osteolysis among implants before understanding if such design differences are clinically relevant.
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 | 0,002 | 0,006 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 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 ».