Patellar Resurfacing in Primary Total Knee Arthroplasty: A Meta-analysis and Trial Sequential Analysis of 50 Randomized Controlled Trials

Minimum 15-Year Survival of a Biconvex Inlay Patellar Component in Primary Total Knee Arthroplasty: An Analysis of 2,530 Total Knee Arthroplasties From a Single Institution

BACKGROUND

Routine patellar resurfacing during primary total knee arthroplasty (TKA) remains controversial. To our knowledge, there are no studies reporting the long-term performance of a cemented biconvex all-polyethylene inlay component implanted at the time of primary TKA. The purpose of this study was to examine the 15-year survivorship and long-term clinical outcomes of this biconvex inlay patella used at our institution.

METHODS

We retrospectively reviewed our prospectively collected institutional database and identified 2,530 patients who underwent cemented TKA with a single prosthetic design (from 1996 to 2007) where the patella was resurfaced using this cemented biconvex inlay patella. The mean age at surgery was 68 years (range, 29 to 93). The mean body mass index was 33.0 (range, 16.4 to 76.3), with 61.9% women. At the time of analysis, the mean time from surgery was 20.4 years (range, 15 to 26). We used Kaplan-Meier analysis to calculate survivorship at 15 years. We analyzed clinical outcomes using 3 patient-reported outcome measures collected prospectively.

RESULTS

The 15-year survivorship with revision surgery for all causes as the end point was 97.1% (95% confidence interval 96.1 to 98.1%). The 15-year survivorship with revision surgery for a patella-related complication as the end point was 99.7% (95% confidence interval 99.4 to 1.0). At the final follow-up, patients showed significant improvement in scores for the Knee Society Clinical Rating System (P < .001), Western Ontario and McMaster University Osteoarthritis Index (P < .001), and Veterans Rand 12-Item Health Survey physical component (P < .001).

CONCLUSIONS

Routine patellar resurfacing using a biconvex inlay patellar component has excellent survivorship and a low rate of complications at 15 years post-TKA.

When to Do Selective Patellar Resurfacing in Total Knee Arthroplasty: A Decision-Making Algorithm Based on Pre-operative and Intra-operative Findings

Background

Persistent anterior knee pain post total knee arthroplasty (TKA) is a significant cause of patient dissatisfaction. Selective patellar resurfacing is commonly practiced for primary total knee replacement (TKR) but there is a paucity in literature regarding its decision making.

Study Objective

This study aims to develop a decision-making algorithm for selective patellar resurfacing using Hospital for Special Surgery Patello-femoral Assessment score (HSS PFA score), weight-bearing patellofemoral X-ray, and intraoperative cartilage wear assessment based on the Outerbridge classification.

Materials and Methods

This prospective study enrolled 65 patients, assessing preoperative factors including HSS PFA score and Baldini view radiography. Intraoperative cartilage wear was categorized using the Outerbridge classification. Preoperative findings were correlated with intraoperative outcomes through statistical analysis, leading to the development of a predictive algorithm. The efficiency of algorithm was assessed at 3-year follow-up using HSS PFA score.

Results

A significant negative correlation (r = - 0.272, p = 0.029) was observed between HSS PFA score and cartilage wear. However, no significant relationships were established between HSS PFA score and Baldini view observations, including radiological tilt (p = 0.517) and displacement (p = 0.277). Intraoperative cartilage wear versus patellar tilt (p = 0.65) and displacement (p = 0.837) also yielded non-significant results. Three-year follow-up examinations revealed no complications and significant HSS PFA score improvements in all patients.

Conclusion

The requirement for patellar resurfacing can be predicted using a combination of preoperative parameter such as HSS PFA score and the intra-operative cartilage wear. We put forward an algorithm based on above findings to aid in the decision making.