Excellent outcomes with Oxford Uni-compartmental knee arthroplasty in anteromedial osteoarthritis patients (≤60 years) at mid-term follow-up

Unicompartmental knee arthroplasty in patients under the age of 60 years provides excellent clinical outcomes and 10-year implant survival: a systematic review : A study performed by the Early Osteoarthritis group of ESSKA-European Knee Associates section

PURPOSE

The purpose of the present study was to systematically review the clinical and functional outcomes following medial unicompartmental knee arthroplasty (UKA) in patients under the age of 60 years old.

METHODS

Using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, studies between 2012 and April 2022, on patients 18-60 years old who have had a unicompartmental knee replacement evaluating patient-reported outcomes measures (PROMs), were included. The Knee Society Scores (KSS) clinical score was considered the primary outcome. Pre- and post-operative range of motion (ROM), PROMs, complications and survival were recorded. Paired sample t testing was performed to compare the pre-operative with post-operative KSS.

RESULTS

Seventeen articles comprising 2083 unicompartmental arthroplasties were included. The follow-up range was between 1 and 15 years. In eligible studies, all reported outcomes were improved following UKA. The mean KSS clinical was significantly improved from 45.5 (SD: 9.6) pre-operatively to 89.4 (SD: 4.4) post-operatively (p = 0.0001). Mean implant survival ranged 86-96.5% at 10 years follow-up. There was no significant difference between mobile and fixed bearing in terms of ROM and KSS clinical. In total, 92 revisions and 7 re-operations with implant retention were reported.

CONCLUSION

Unicompartmental knee arthroplasty for medial osteoarthritis is a safe, reliable and effective treatment option for patients of 60 years or younger. It provides pain relief, satisfactory activity level, excellent clinical outcomes, and up to 96.5% implant survival at 10-year follow-up.

LEVEL OF EVIDENCE

IV.

A radiographic model predicting the status of the anterior cruciate ligament in varus knee with osteoarthritis

Purpose

The study aims to investigate the accuracy of different radiographic signs for predicting functional deficiency of anterior cruciate ligament (ACL) and test whether the prediction model constructed by integrating multiple radiographic signs can improve the predictive ability.

Methods

A total number of 122 patients from January 1, 2018, to September 1, 2021, were enrolled in this study. Among them, 96 patients were classified as the ACL-functional (ACLF) group, while 26 patients as the ACL-deficient (ACLD) group after the assessment of magnetic resonance imaging (MRI) and the Lachman’s test. Radiographic measurements, including the maximum wear point of the proximal tibia% (MWPPT%), tibial spine sign (TSS), coronal tibiofemoral subluxation (CTFS), hip–knee–ankle angle (HKA), mechanical proximal tibial angle (mPTA), mechanical lateral distal femoral angle (mLDFA) and posterior tibial slope (PTS) were measured using X-rays and compared between ACLF and ACLD group using univariate analysis. Significant variables (p < 0.05) in univariate analysis were further analyzed using multiple logistic regression analysis and a logistic regression model was also constructed by multivariable regression with generalized estimating models. Receiver-operating-characteristic (ROC) curve and area under the curve (AUC) were used to determine the cut-off value and the diagnostic accuracy of radiographic measurements and the logistic regression model.

Results

MWPPT% (odds ratio (OR) = 1.383, 95% confidence interval (CI) = 1.193–1.603, p < 0.001), HKA (OR = 1.326, 95%CI = 1.051–1.673, p = 0.017) and PTS (OR = 1.981, 95%CI = 1.207–3.253, p = 0.007) were shown as predictive indicators of ACLD, while age, sex, side, TSS, CTFS, mPTA and mLDFA were not. A predictive model (risk score = -27.147 + [0.342*MWPPT%] + [0.282*HKA] + [0.684*PTS]) of ACLD using the three significant imaging indicators was constructed through multiple logistic regression analysis. The cut-off values of MWPPT%, HKA, PTS and the predictive model were 52.4% (sensitivity:92.3%; specificity:83.3%), 8.5° (sensitivity: 61.5%; specificity: 77.1%), 9.6° (sensitivity: 69.2%; specificity: 78.2%) and 0.1 (sensitivity: 96.2%; specificity: 79.2%) with the AUC (95%CI) values of 0.906 (0.829–0.983), 0.703 (0.574–0.832), 0.740 (0.621–0.860) and 0.949 (0.912–0.986) in the ROC curve.

Conclusion

MWPPT% (> 52.4%), PTS (> 9.6°), and HKA (> 8.5°) were found to be predictive factors for ACLD, and MWPPT% had the highest sensitivity of the three factors. Therefore, MWPPT% can be used as a screening tool, while the model can be used as a diagnostic tool.