Journal of orthopaedic surgery and research · 2026
Identifying patients at risk in revision arthroplasty: a comprehensive single-centre analysis.
СтатьяНазвание и аннотация: Перевод в очереди
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Wolf Matthias, Lehner Burkhard, Geisbüsch Andreas, Merle Christian, Walker Tilman, Deisenhofer Julian
Аннотация
BACKGROUND: The demand for revision hip and knee arthroplasty (rTHA/rTKA) is increasing, while they continue to be associated with greater perioperative risks, higher resource demands, and greater variability in outcomes compared with primary procedures. Identifying precise risk factors is essential for effective perioperative management and resource planning.
METHODS: A retrospective analysis of 2,123 revision total hip (rTHA, n = 1,301) and knee arthroplasties (rTKA, n = 822) performed from 2010 to 2019 at a tertiary German centre was conducted. Adverse events (AE), length of hospital stay (LOS), and predictors including age, Elixhauser Comorbidity Index (EI), joint type, and indication were analysed using multivariate regression models.
RESULTS: The overall AE rate was 13.1%, significantly higher in rTHA than in rTKA (12.6% vs. 8.8%; p = 0.008), particularly for infections and mechanical complications. Mean LOS was 19 ± 14 days. Infection, age, EI, joint type, dislocation, and periprosthetic fracture independently predicted AE and LOS. Infection was the strongest predictor overall (AE: OR 5.4; LOS: Coefficient 1.6), with periprosthetic fractures being highly predictive in rTKA (OR 9.8).
CONCLUSIONS: Infection (in all revisions), periprosthetic fractures (in rTKA), advanced age, and high comorbidity burden were critical determinants of perioperative adverse events and hospital utilisation. Focused perioperative care strategies targeting these risk groups are essential to mitigate adverse outcomes and optimise healthcare resources.
METHODS: A retrospective analysis of 2,123 revision total hip (rTHA, n = 1,301) and knee arthroplasties (rTKA, n = 822) performed from 2010 to 2019 at a tertiary German centre was conducted. Adverse events (AE), length of hospital stay (LOS), and predictors including age, Elixhauser Comorbidity Index (EI), joint type, and indication were analysed using multivariate regression models.
RESULTS: The overall AE rate was 13.1%, significantly higher in rTHA than in rTKA (12.6% vs. 8.8%; p = 0.008), particularly for infections and mechanical complications. Mean LOS was 19 ± 14 days. Infection, age, EI, joint type, dislocation, and periprosthetic fracture independently predicted AE and LOS. Infection was the strongest predictor overall (AE: OR 5.4; LOS: Coefficient 1.6), with periprosthetic fractures being highly predictive in rTKA (OR 9.8).
CONCLUSIONS: Infection (in all revisions), periprosthetic fractures (in rTKA), advanced age, and high comorbidity burden were critical determinants of perioperative adverse events and hospital utilisation. Focused perioperative care strategies targeting these risk groups are essential to mitigate adverse outcomes and optimise healthcare resources.