Polyethylene quality affects revision knee liner exchange survivorship

Abstract

Background: Options to treat patients with wear or osteolysis include full revision, partial (tibial or femoral) revision, and isolated polyethylene exchange. It is unclear whether one choice is superior to the other. Polyethylene quality reportedly influences the survivorship of primary TKA, but similar reports are not described for revision TKA.

Questions/purposes: We compared the failure rate for the three procedures and the influence of polyethylene quality on failure.

Patients and methods: We retrospectively evaluated 123 patients with 135 TKAs in which wear or osteolysis was thought to have contributed to the need for surgery. Twenty-five percent had an isolated polyethylene exchange, 39% a single-component revision, and 36% a full revision. We determined survivorship of the revisions. The mean follow-up for the 123 patients was 6.2 years. Fifteen patients (16 knees, or 12%) were lost before 5-year evaluations leaving 108 patients (119 knees, or 88%) for comparison of rerevision rates.

Results: Five-year survivorship was similar for all three procedures: 82% ± 14% for polyethylene exchange, 89% ± 8% for partial revision, and 88% ± 10% for a full revision. Polyethylene sterilization had the strongest influence on rerevision. Survivorship was 73% ± 16% for knees revised with gamma-in-air polyethylene compared to 92% ± 6% for nongamma or gamma-in-barrier sterilization methods.

Conclusions: The survival rates of isolated polyethylene exchange for wear or osteolysis are similar to those of a single-component or full revision when the components are well aligned and well fixed. Polyethylene sterilization influenced revision TKA survivorship in this study and should be reported in future studies.

Fig. 1

Five-year survivorship with rerevision as the end point was lower (p = 0.002) for knees revised with gamma-in-air polyethylene (73% ± 16%) than for knees revised with nongamma or gamma-inert polyethylene (92% ± 6%). Gray lines show confidence intervals.