Unicompartmental knee arthroplasty (UKA) is associated with a higher risk of revision compared with total knee arthroplasty (TKA). The outcomes of knee arthroplasty are typically presented as implant survival or incidence of revision after a set number of years, which can be difficult for patients and clinicians to conceptualise. We aimed to calculate the ‘lifetime risk’ of revision for UKA as a more relatable estimate of risk projection over a patient's remaining lifetime, and make comparisons to TKA. All primary UKAS performed from 1999 to 2019 (n=13,481) captured by the New Zealand Joint Registry (NZJR) were included. The lifetime risk of revision was calculated and stratified by age, gender and American Society of Anesthesiologists (ASA) status. The lifetime risk of revision for UKA was highest in the youngest patients (46-50 years; 40.4%) and lowest in the oldest patients (86-90 years; 3.7%). Lifetime risk of revision was higher for females (range 4.3%-43.4% cf. males 2.9%-37.4%) and patients with higher ASA status (ASA 3-4 range 8.8%-41.2% cf. ASA 1 1.8%-29.8%), regardless of age. The lifetime risk of UKA was two-fold higher than TKA (ranging from 3.7%-40.4% UKA, 1.6%-22.4% TKA) across all age groups. Increased risk of revision in the younger patients was associated with aseptic loosening in both males and females, and pain in females. Periprosthetic joint infections (PJI) accounted for 4% of all UKA revisions, in contrast to 27% for TKA; risk of PJI was higher for males than females for both procedures. The lifetime risk of revision is a more meaningful measure of arthroplasty outcomes and can aid with patient counselling prior to UKA. Findings from this study show the increased lifetime risk of UKA revision for younger patients, females and those with higher ASA status

Outcomes for guided motion primary total knee arthroplasty (TKA) in obese patients are unknown. 1,684 consecutive patients underwent 2,059 primary TKAs with a second-generation guided motion implant between 2011–2017 at three European and seven US sites. Of 2,003 (97.3%) TKAs in 1,644 patients with BMI data: average age 64.5 years; 58.4% females; average BMI 32.5 kg/m2; 13.4% had BMI ≥ 40 kg/m2. Subjects with BMI ≥ 40 kg/m2 had longest length of hospital stay (LOS) at European sites; LOS similar at US sites. Subjects with BMI ≥ 40 kg/m2 (P=0.0349) had longest surgery duration. BMI ≥ 40 kg/m2 had more re-hospitalizations or post-TKA reoperations than BMI < 40 kg/m2 (12.7% and 9.2% at five-year post-TKA, P<0.0495). Surgery duration and long-term complication rates are higher in patients with BMI ≥ 40 kg/m2, but device revision risk is not elevated

The development of an algorithm that provides accurate individualised estimates of revision risk could help patients make informed surgical treatment choices. This requires building a survival model based on fixed and modifiable risk factors that predict outcome at the individual level. Here we compare different survival models for predicting prosthesis survivorship after hip replacement for osteoarthritis using data from the National Joint Registry for England, Wales, Northern Ireland and the Isle of Man. In this comparative study we implemented parametric and flexible parametric (FP) methods and random survival forests (RSF). The overall performance of the parametric models was compared using Akaike information criterion (AIC). The preferred parametric model and the RSF algorithm were further compared in terms of the Brier score, concordance index (C index) and calibration. The dataset contains 327 238 hip replacements for osteoarthritis carried out in England and Wales between 2003 and 2015. The AIC value for the FP model was the lowest. The averages of survival probability estimates were in good agreement with the observed values for the FP model and the RSF algorithm. The integrated Brier score of the FP model and the RSF approach over 10 years were similar: 0.011 (95% confidence interval: 0.011–0.011). The C index of the FP model at 10 years was 59.4% (95% confidence interval: 59.4%–59.4%). This was 56.2% (56.1%–56.3%) for the RSF method. The FP model outperformed other commonly used survival models across chosen validation criteria. However, it does not provide high discriminatory power at the individual level. Models with more comprehensive risk adjustment may provide additional insights for individual risk

Introduction. Prosthetic joint infection (PJI) is an uncommon but serious complication of hip replacement. A recent systematic review of patient risk factors for PJI identified male gender, smoking status, increasing BMI, steroid use, previous joint surgery and comorbidities of diabetes, rheumatoid arthritis and depression as risk factors for developing PJI. Limitations of the current literature include the short term follow up of most published studies. We investigated the role of patient, surgical and healthcare factors on the risk of revision of a primary hip replacement for PJI at different time-points in the post-operative follow-up. It is important that those risk factors are identified so that patients can be appropriately counselled according to their individual risk profile prior to surgery and modifiable factors can be addressed to reduce the risk of PJI at an individual and healthcare system level. Materials and Methods. Primary hip replacements and subsequent revision procedures performed for PJI from 2003–2014 were identified from the National Joint Registry (NJR). Patient (age, gender, ASA grade, BMI), perioperative (surgical indication, type of anaesthesia, thromboprophylaxis regime, surgical approach, hip replacement and bearing surface and use of femoral or acetabular bone graft) and healthcare system characteristics (surgeon grade, surgical volume) were linked with data from Hospital Episode Statistics to obtain information on specific ethnicity and comorbidities (derived from the Charlson index). Multilevel piecewise exponential non-proportional hazards models were used to estimate their effects at different post-operative periods (0–3 months, 3–6 months, 6–12 months, 12–24 and >24 months post-operation). Results. The index hip replacements consisted of 623,253 primaries with 2,705 subsequently revised for PJI, 14% within 3 months, 8% between 3–6 months, 14% between 6–12 months, 22% between 1–2 years and 42% ≥2 years after the index procedure. Risk factors for revision of PJI included male gender, high BMI, high ASA grade and younger age. Their effects were period-specific. Patients with chronic pulmonary disease, diabetes or dementia had high early risk of revision for PJI, as did patients operated for a fractured neck of femur (<3 months). Metal-on-metal bearings (>12 months) and lateral surgical approach (≥3 months) also influenced the mid- and long-term revision risk for PJI. No or modest associations were found with the operating surgeon grade, surgical volume and hospital surgical volume. Conclusion. The effects of patient, perioperative and healthcare system risk factors for PJI after primary hip replacement are time-dependent. Modifiable risk factors such as the type of surgical approach and bearing surface have also been found