The impact of patellofemoral joint diseases on functional outcomes and prosthesis survival in patients undergoing unicompartmental knee arthroplasty: a systematic review and meta-analysis
Notice bibliographique
Résumé
BACKGROUND: Patellofemoral joint (PFJ) diseases are chronic degenerative conditions that contribute to knee joint symptoms. Unicompartmental knee arthroplasty (UKA) is widely regarded as an effective treatment for knee osteoarthritis (KOA); however, its specific indications remain a subject of debate. HYPOTHESIS: Patients with PFJ disease are expected to experience outcomes post-UKA comparable to those of patients without PFJ disease. METHODS: We conducted this meta-analysis following the guidelines outlined by the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA). A comprehensive search of PubMed, Embase, and Web of Science databases was conducted for studies examining the association between PFJ disease and UKA, including publications up to September 2024. Extracted data encompassed author, publication year, country, disease type, prosthesis type, sample size, mean patient age, gender distribution, follow-up duration, PFJ disease prevalence at surgery, diagnostic methods, and whether PFJ disease was considered a contraindication for UKA. To maintain objectivity, only studies in which PFJ diseases were visually identifiable were included in the meta-analysis. Statistical analyses were performed using Stata 15.0 and Review Manager 5.4.1. A random-effects meta-analysis was conducted to evaluate the Oxford Knee Score (OKS), Knee Society Score (KSS), flexion range of motion (ROM), Forgotten Joint Score (FJS), Tegner activity score, and prosthesis survival rate, with outcomes stratified by PFJ disease type (PFJ degeneration or patella cartilage injury). Mean differences, confidence intervals, and P values were calculated for comparisons between the PFJ disease and non-PFJ disease groups. The Methodological Index for Non-Randomized Studies (MINORS) criteria and the Newcastle-Ottawa Scale (NOS) were applied to evaluate the risk of bias. To address heterogeneity, sensitivity analyses were performed, and publication bias was assessed using funnel plots and Egger's test. RESULTS: A total of 14,866 knees from 48 relevant studies were included in this systematic review. Methodological quality was assessed using the MINORS criteria, with case series scoring 11.0/16 and cohort studies scoring 18.2/24. PFJ degeneration emerged as the most studied condition, followed by patella cartilage injury. Clinical outcomes assessments indicated that medial PFJ degeneration, anterior knee pain, patella cartilage damage, and patella baja did not significantly impact UKA outcomes or prosthesis survival. However, severe lateral PFJ degeneration, lateral patellar subluxation, lateral trochlear osteophytes, and patellar bone marrow edema did influence results. Fifteen high-quality studies were included in the meta-analysis, involving 6080 patients-1338 in the PFJ disease group and 4,742 in the non-PFJ disease group. With an average NOS score of 7.2, the studies were generally of high quality. Meta-analysis results showed no significant differences between groups in final follow-up OKS, FJS, Tegner activity score, or prosthesis survival rate. However, the PFJ disease group had lower KSS and reduced flexion ROM compared to the non-PFJ disease group. Subgroup analysis further revealed that the PFJ degeneration group scored lower than the patella cartilage injury group on OKS, KSS, and flexion ROM following UKA. CONCLUSION: In summary, PFJ disease was found to have limited impact on UKA outcomes; however, caution is recommended for cases involving severe lateral PFJ degeneration due to potential restrictions in postoperative knee function, particularly affecting flexion ROM in UKA patients.
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 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 | 0,006 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,008 | 0,004 |
| Bibliométrie | 0,002 | 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 ».