OPPORTUNITIES IN TOTAL KNEE ARTHROPLASTY: PERSPECTIVE OF SURGEONS WORLDWIDE
Notice bibliographique
Résumé
Background Total knee arthroplasty (TKA) is a routine, cost-effective treatment for end-stage arthritis. While the evidence for good-to-excellent patient-reported outcomes and objective clinical data is present, approximately 20% of patients continue to be dissatisfied with results of their surgery. Dissatisfaction is strongly correlated with unmet patient expectations, and these patients may experience a higher cost of care due to recurring office and emergency visits. Therefore, this survey asked a large group of United States (U.S) and international surgeons to prioritize areas of opportunity in primary TKA. Specifically, we compared surgeon responses regarding: 1) the top 5 areas needing improvement; which were stratified by: 2) surgeons9 years of experience; and 3) surgical case volume. Methods A total of 418 orthopaedic surgeons were surveyed. Two hundred U.S. surgeons and 218 international surgeons participated from 7 different countries including: The United Kingdom (40), France (40), Germany (43), Italy (40), Spain (38), and Australia (17). To participate, surgeons had to be board certified, in practice for 2 years, spend 60% of their time in clinical practice, and perform a minimum of 25 joint arthroplasties per year. Surgeons were asked to choose the top 5 areas of improvement for TKA from a list of 17 attributes including clinical and functional outcomes, procedural workflow and economic variables. Surgeons were able to specify additional options if needed. Results were stratified by annual case volume (25 to 50; 51 to 100; greater than 100 cases) and years of experience (1 to 10; 11 to 20; greater than 20). Single-tail proportion tests were used to compare results between cohorts, where an alpha of 0.05 was set as significant. Results The most frequently identified opportunity in both groups was functional outcomes, selected by 63% of U.S. surgeons (p=0.001) compared to 71% of international surgeons (p=0.002). In the U.S. cohort, this was followed by cost (47%), which was not identified in the top 5 choices for international surgeons. Cost was followed by implant survivorship (45%), patient satisfaction (42%), and accuracy/precision (39%). In the international cohort, implant survivorship (57%), dynamic joint balancing (40%), accuracy/precision (39%), and patient satisfaction rates (35%) were noted. When stratified by years of experience and case volume, the top area for improvement remained functional outcomes for U.S. and International groups. Conclusion The responses in the international survey demonstrate that functional outcomes, implant survivorship and costs had greater perceived potential for improvement, compared to the specific targeting of post-operative patient satisfaction. Functional outcomes remained a top area for improvement, regardless of years of experience or case volume. As a result, enhancing functional outcomes and implant survivorship may ultimately address patient satisfaction, by more consistently meeting patient expectations. These results serve as baseline data to help guide future improvements in knee arthroplasty.
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 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,005 | 0,004 |
| Science ouverte | 0,000 | 0,002 |
| Intégrité de la recherche | 0,003 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,021 | 0,002 |
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 ».