Cementless Oxford Unicompartmental Knee Replacements: More Data, More Questions
Notice bibliographique
Résumé
Commentary Unicompartmental knee replacement (UKR) is recognized as a valuable procedure for patients with isolated, single-compartment knee arthritis. The proposed benefits of the less-invasive UKR over a total knee replacement include decreased mortality, decreased length of stay, fewer complications, and improved patient-reported functional outcome measures1. As the popularity of UKR rises, interest in improving the durability of UKR implants has gained traction. One strategy has been to utilize cementless implants to allow for biologic osseointegration and thus improved fixation compared with that of traditional cemented implants. Previous research has shown that cementless UKRs have decreased rates of radiolucent lines and aseptic loosening compared with cemented UKRs2. In the present study, Mohammad et al. sought to further explore the impact of cementless fixation in UKRs while investigating related functional patient-reported outcome measures (PROMs). They utilized data from the National Joint Registry for England, Wales, Northern Ireland and the Isle of Man (NJR) and the Hospital Episode Statistics Patient Reported Outcome Measures (HES-PROMs) database to identify and compare a matched cohort of 3,453 cementless and 3,453 cemented Oxford (Zimmer Biomet) mobile-bearing medial UKRs. This study is an excellent example of the use of both “big data” from registries and propensity score matching to answer questions that would simply not be feasible to investigate by means of a prospective randomized controlled trial. The authors demonstrated improved 10-year cumulative implant survival (93.0% versus 91.3%) and improved PROMs (as measured with use of the Oxford Knee Score [OKS] and the EuroQol-5 Dimension index [EQ-5D]) in favor of the cementless version of the implant. Furthermore, they found significantly lower rates of both aseptic loosening (0.35% versus 1.10%; p < 0.001) and osteoarthritis progression (0.72% versus 1.25%; p = 0.03) in the cementless group. Rates of periprosthetic fracture trended higher in the cementless group (0.23% versus 0.06%), but this difference did not reach significance (p = 0.06). The subgroup analysis in this study is also especially informative. Improved survivorship with cementless implants was noted with UKRs performed by high-volume (≥30 UKRs per year), medium-volume (10 to <30 UKRs per year), and low-volume (<10 UKRs per year) surgeons, although this only reached significance for the high-volume surgeons. Among UKRs performed by medium or high-volume surgeons, greater improvement in the postoperative OKS was demonstrated with cementless fixation. Among UKRs performed by high-volume surgeons, higher postoperative EQ-5D scores were shown with cementless fixation. These findings beg the question: are higher-volume surgeons performing a more technically sound procedure than lower-volume surgeons? In other words, is it when these surgeons use the cementless Oxford UKR that we see the true potential of the implant and procedure, with improved survivorship and improved functional outcomes? Additionally, does the cementless implant, and by extension, the biologic fixation, further enhance the more “natural feel” of the implant? The lack of statistical differences in survivorship and in PROMs between cementless and cemented UKRs performed by low-volume surgeons may reflect the smaller sample size for this subgroup, or it may reflect the absence of a difference in surgeons who perform fewer procedures. The relationship between surgical volume and outcomes in UKR is certainly complex, and one of the limitations of registry studies is the challenge of identifying the many factors, including radiographic alignment, use of technology (e.g., navigation or robotics), and patient factors, that may influence outcomes and survivorship in UKR3,4. Other study designs and data sources will need to be utilized to sift out possible confounders. Other questions remain as well. Will other joint registries demonstrate similar results? Will these findings hold up over longer-term follow-up? Can the superiority of the cementless version of the Oxford UKR implant be replicated with other implants? As noted by the authors, there are data to suggest otherwise, and—as is commonly a disclaimer in implant-related research—one must be cautious when attempting to generalize the results. Regardless, we commend Mohammad et al. on their excellent work, and future research will need to corroborate and complement this study to help answer these questions and those yet to be asked.
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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 | 0,030 | 0,155 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,004 | 0,002 |
| Bibliométrie | 0,003 | 0,004 |
| Études des sciences et des technologies | 0,001 | 0,004 |
| Communication savante | 0,004 | 0,010 |
| Science ouverte | 0,005 | 0,002 |
| Intégrité de la recherche | 0,015 | 0,016 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,015 | 0,004 |
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 ».