Epidemiology of Bearing Dislocations After Mobile-Bearing Unicompartmental Knee Arthroplasty: Multicenter Analysis of 67 Bearing Dislocations

Autor: Jong-Min Kim, Kang-Il Kim, Jae Gyoon Kim, Hong Chul Lim, Ji Hoon Bae, Song Lee, Ju Hong Lee, Jong Hun Ji, Seung Yup Lee, Yong In
Rok vydání: 2020
Předmět:
Zdroj: The Journal of Arthroplasty. 35:265-271
ISSN: 0883-5403
Popis: Background This study investigated the epidemiology and causes of bearing dislocations following mobile-bearing unicompartmental knee arthroplasty (MUKA) and determined whether the incidence of primary bearing dislocations decreases as surgeon experience increases. Methods We retrospectively reviewed the bearing dislocations following MUKAs performed by 14 surgeons with variable experience levels. Causes of bearing dislocations were determined based on the surgical records, radiographs, and operator’s suggestion. Using a chi-squared test, the incidence of bearing dislocation was compared between the first 50, the second 50, and the next 100 unicompartmental knee arthroplasties (UKAs) of each surgeon's cohort. Results There were 67 (3.6%) bearing dislocations from 1853 MUKAs. The mean time to bearing dislocations after index MUKAs was 33 months (range, 1-144 months); 55% of the bearing dislocations occurred within 2 years after the index MUKAs. Primary bearing dislocations (n = 58) were the most common, followed by secondary (n = 6) and traumatic dislocations (n = 3). There was no significant difference in the incidence of bearing dislocation between the first 50 and second 50 UKAs for each surgeon. Two surgeons showed a significant decrease in bearing dislocations in their second 100 UKAs, while the other surgeons did not show a difference between their first 100 and second 100 UKAs. Conclusion Most bearing dislocations after MUKAs were related to technical errors such as component malposition or gap imbalance. This study did not confirm that the incidence of bearing dislocations decreases as the number of cases increases. Level of Evidence IV, Case series.
Databáze: OpenAIRE