Search

Background: Some surgeons contend that unicompartmental knee arthroplasty (UKA) can easily be revised to a TKA when revision is called for, whereas others believe that this can be complex and technically demanding. There has been little research regarding the efficacy or rationale of using metal augmentation and tibial stem extensions when revising a UKA to a TKA. QUESTION/PURPOSES: (1) Is the use of stem extensions for the tibial component associated with increased survival when revising a UKA to a TKA? (2) Is the addition of modular augments associated with increased survival compared with stem extensions alone? (3) Is TKA design (minimally stabilized versus posterior-stabilized) or (4) tibial fixation (cemented versus cementless) associated with differences in survivorship?Methods: Data from the Australian Orthopaedic Association National Joint Replacement Registry (AOANJRR) were used to analyze implant survival after revision of a UKA to a TKA, comparing results in which tibial components were used with and without modular components. The groups analyzed were TKA without a stem extension, those in which a tibial stem extension was used, and those in which a tibial stem extension was used together with an augment. There were 4438 revisions of UKAs to TKAs available for analysis. The mean duration of followup of patients having the TKA revisions was 5 years (SD, 3.5 years). There were 2901 (65%) procedures in which a tibial stem extension was not used, 870 (20%) procedures with a tibial stem extension, and 667 (15%) with a tibial stem extension and metallic augment. Kaplan-Meier estimates of survivorship were calculated and hazard ratios (HRs) from Cox proportional hazard models, adjusting for age and sex, were used to compare the rate of revision among groups. The overall 10-year cumulative percent revision (CPR) for UKA revised to a TKA was 16%.Results: At 10 years, the CPR was increased when a stem extension was not used (19%; 95% confidence interval [CI],16.5-20.7 without a stem extension compared with 13%; 95% CI, 9.2-17.0 with a stem extension; entire period HR, 1.44; 95% CI, 1.10-1.89; p = 0.007). There was no difference in the 10-year CPR when an augment was used together with a stem extension compared with a stem extension alone (HR, 1.26; 95% CI, 0.85-1.86; p = 0.251). When minimally stabilized and posterior-stabilized TKAs were compared, there was no difference in survivorship. Minimally stabilized TKA designs without stem extensions showed higher CPR compared with when stem extensions were used (HR, 1.77; 95% CI, 1.16-2.70; p = 0.007), whereas posterior-stabilized designs without stem extensions showed higher CPR only when compared with when stem extensions and augments were both used (HR, 2.16; 95% CI, 1.24-3.77; p = 0.006). Cementless fixation of the tibial component resulted in a higher CPR than when cement was used (HR, 1.36; 95% CI 1.08-1.71; p = 0.008).Conclusions: In this registry study, the risk of repeat revision after revision of a UKA to a TKA was lower when a tibial stem extension was used, but no such difference was found with respect to augments. Our study did not account for the degree of bone loss or surgeon preference when considering stems and augments. Further research to establish the degree of bone loss associated with UKA to TKA revision procedures will help clarify these findings.Level Of Evidence: Level III, therapeutic study. [ABSTRACT FROM AUTHOR]

Background and purpose Joint Replacement Registries play a significant role in monitoring arthroplasty outcomes by publishing data on survivorship of individual prostheses or combinations of prostheses. The difference in outcomes can be device- or non-device-related, and these factors can be analyzed separately. Although registry data indicate that most prostheses have similar outcomes, some have a higher than anticipated rate of revision when compared to all other prostheses in their class. This report outlines how the Australian Orthopaedic Association National Joint Replacement Registry (AOANJRR) has developed a method to report prostheses with a higher than expected rate of revision. These are referred to as 'outlier' prostheses. Material and methods Since 2004, the AOANJRR has developed a standardized process for identifying outliers. This is based on a 3-stage process consisting of an automated algorithm, an extensive analysis of individual prostheses or combinations by registry staff, and finally a meeting involving a panel from the Australian Orthopaedic Association Arthroplasty Society. Outlier prostheses are listed in the Annual Report as (1) identified but no longer used in Australia, (2) those that have been re-identified and that are still used, and (3) those that are being identified for the first time. Results 78 prostheses or prosthesis combinations have been identified as being outliers using this approach (AOANJRR 2011 Annual Report). In addition, 5 conventional hip prostheses were initially identified, but after further analysis no longer met the defined criteria. 1 resurfacing hip prosthesis was initially identified, subsequently removed from the list, and then re-identified the following year when further data were available. All unicompartmental and primary total knee prostheses identified as having a higher than expected rate of revision have continued to be re-identified. Interpretation It is important that registries use a transparent and accountable process to identify an outlier prosthesis. This paper describes the development, implementation, assessment, and impact of the approach used by the Australian Registry. [ABSTRACT FROM AUTHOR]

Background: We retrospectively assessed the independent effects of patient and clinical factors on length of stay and all-cause 90-day, one-year, and two-year readmission following elective total joint replacement. We also evaluated the independent association between length of stay and readmission with postoperative five-year mortality. Methods: Longitudinal data from 819 men who had had total joint replacement were integrated with validated hospital morbidity data and mortality records. Length of stay, readmission, and mortality following total joint replacement were each modeled using multivariable proportional hazards regression. Results: Mean age at surgery was 76.3 ± 4.3 years. Median length of stay following total joint replacement decreased by 25% from 12 days in 1997-1998 to nine days in 2005-2007. Age, inhospital complications, total knee replacement, private hospital, and increased body weight were significantly associated with longer stay. A dose-response relationship between weight and length of stay was observed (P = 0.003). Crude 90-day, one-year, and two-year readmission rates were 17.3%, 47.4%, and 65.0%, respectively. Ninety-day readmission was associated with comorbidity, inhospital complications, and treatment in public hospitals. Age, comorbidity, socioeconomic disadvantage, and increased weight significantly increased the risk of one-year and two-year readmission. Patients with a body mass index ≥ 30 kg/m² were 34% more likely to be readmitted within two years compared with those having a body mass index of 18.5-24.9 kg/m². All-cause one-year and two-year readmission rates were significantly higher in patients undergoing a total knee replacement than those undergoing a total hip replacement. No independent associations between length of stay and all-cause readmission or mortality were observed. All-cause 90-day and one-year readmission independently increased the risk of long-term postoperative mortality. Conclusion: After adjusting for confounding factors, including age, comorbidity, obesity, and inhospital complications, length of stay was not independently associated with post-discharge readmission or death. We report that the obese, those having total knee replacement, and the socioeconomically disadvantaged are the highest consumers of hospital resources following elective total joint replacement in elderly men. Our findings may assist clinicians in better selection of elderly patients for surgery, and informing them about their individual level of risk. [ABSTRACT FROM AUTHOR]

Background: Routinely collected data such as hospital morbidity data (HMD) are increasingly used in studying clinical outcomes among patients undergoing total joint replacement (TJR). These data are readily available and cover large populations. However, since these data were not originally collected for the purpose of health research, a rigorous assessment of their quality is required. We assessed the accuracy of the diagnosis of obesity in HMD and evaluated whether the augmentation of HMD with actual weight and height of patients could improve their ability to predict major in-hospital complications following total joint replacement in men. Methods: The electronic records of 857 participants in the Health In Men Study (HIMS) who had had TJR were linked with Western Australia HMD. HMD-recorded diagnosis of obesity was validated using the actual weight and height obtained from HIMS. In-hospital major complications were modelled using multivariable logistic regressions that either included the actual weight and height or HMD-recorded obesity. Model discrimination was calculated using area under ROC curve. Results: The HMD failed to detect 70% of the obese patients. Only 64 patients (7.5%) were recorded in HMD as obese although 216 (25%) were obese [BMI: ≥30kg/m2] (sensitivity: 0.2, positive predictive value: 0.7). Overall, 174 patients (20%) developed an in-hospital major complication which was significantly higher in the overweight and obese comparing with patients with normal weight. HMD-recorded obesity was not independently associated with major complications, whereas a dose-response relationship between weight and these complications was observed (P=0.004). Using the actual weight and height of the participants instead of HMD-recorded diagnosis of obesity improved model discrimination by 9%, with areas under ROC curve of: 0.69, 95% CI: 0.64-0.73 for the model with HMD-recorded obesity compared with 0.75, 95% CI: 0.70-0.79 for the model with actual weight and height, P<0.001. Conclusion: Body weight is an important risk factor for in-hospital complications in patients undergoing TJR. HMD systems do not include weight and height as variables whose recording is mandatory. Augmenting HMD with patients' weight and height may improve prediction of major complications following TJR. Our study suggests making these variables mandatory in any hospital morbidity data system. [ABSTRACT FROM AUTHOR]