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Background and purpose: This study aims to assess time trends in case-mix and to evaluate the risk of revision and causes following primary THA, TKA, and UKA in private and public hospitals in the Netherlands. Methods: We retrospectively analyzed 476,312 primary arthroplasties (public: n = 413,560 and private n = 62,752) implanted between 2014 and 2023 using Dutch Arthroplasty Register data. We explored patient demographics, procedure details, trends over time, and revisions per hospital type. Adjusted revision risk was calculated for comparable subgroups (ASA I/II, age ≤ 75, BMI ≤ 30, osteoarthritis diagnosis, and moderate–high socioeconomic status (SES). Results: The volume of THAs and TKAs in private hospitals increased from 4% and 9% in 2014, to 18% and 21% in 2022. Patients in private hospitals were younger, had lower ASA classification, lower BMI, and higher SES compared with public hospital patients. In private hospitals, age and ASA II proportion increased over time. Multivariable Cox regression demonstrated a lower revision risk for primary THA (HR 0.7, CI 0.7–0.8), TKA (HR 0.8, CI 0.7–0.9), and UKA (HR 0.8, CI 0.7–0.9) in private hospitals. After initial arthroplasty in private hospitals, 49% of THA and 37% of TKA revisions were performed in public hospitals. Conclusion: Patients in private hospitals were younger, had lower ASA classification, lower BMI, and higher SES com­pared with public hospital patients. The number of arthroplasties increased in private hospitals, with a lower revision risk compared with public hospitals.

Background and purpose: The direct superior approach (DSA) is a modification of the posterolateral approach (PLA) for total hip arthroplasty (THA). Patient-reported outcome measures (PROMs) of the DSA have not been investigated previously using nationwide data. Our aim was to assess PROMs after THA using the DSA compared with the PLA and, secondarily, with the anterior approach (DAA). Patients and methods: In this population-based cohort study we included 37,976 primary THAs performed between 2014 and 2020 (PLA: n = 22,616; DAA: n = 15,017; DSA: n = 343) using Dutch Arthroplasty Registry data. PROMs (NRS pain, EQ-5D, HOOS-PS, and OHS) were measured preoperatively, and at 3 and 12 months postoperatively. Repeated measurements were analyzed using mixed-effects models, adjusted for confounders, to investigate the association between surgical approach and PROMs over time. Results: From baseline to 3 and 12 months, improvements for NRS pain scores, EQ-5D, and OHS were comparable for the DSA compared with the PLA or DAA. No difference was found in HOOS-PS improvement 3 months postoperatively between DSA and PLA (–0.2, 95% confidence interval [CI] –2.4 to 1.9) and between DSA and DAA (–1.7, CI –3.9 to 0.5). At 12 months postoperatively, patients in the DSA group had improved –2.8 points (CI –4.9 to –0.6) more in HOOS-PS compared with the DAA, but not with the PLA group (–1.0, CI –3.2 to 1.1). Conclusion: Our study showed no clinically meaningful differences between the DSA and either PLA or DAA.

Background and purpose: Periprosthetic femoral fracture (PPF) after total hip arthroplasty (THA) is a serious complication, as it often is followed by functional deficits and morbidity. There is no consensus regarding the optimal stem fixation method and whether additional cup replacement is beneficial. The aim of our study was to perform a direct comparison of reasons and risk of re-revision between cemented and uncemented revision THAs following PPF using registry data. Patients and methods: 1,879 patients registered in the Dutch Arthroplasty Registry (LROI) who underwent a first-time revision for PPF between 2007 and 2021 (cemented stem: n = 555; uncemented stem: n = 1,324) were included. Competing risk survival analysis and multivariable Cox proportional hazard analyses were performed. Results: 5- and 10-year crude cumulative incidence of re-revision following revision for PPF was similar between cemented (resp. 13%, 95% CI 10–16 and 18%, CI 13–24) and uncemented (resp. 11%, CI 10–13 and 13%, CI 11–16) revisions. Multivariable Cox regression analysis, adjusting for potential confounders, showed a similar risk of revision for uncemented and cemented revision stems. Finally, we found no difference in risk of re-revision between a total revision (HR 1.2, 0.6–2.1) compared with a stem revision. Conclusion: We found no difference in the risk of re-revision between cemented and uncemented revision stems after revision for PPF.

Background and purpose: The direct superior approach (DSA) is a modification of the classic posterolateral approach (PLA) for total hip arthroplasty (THA), in which the iliotibial band and short external rotators are spared. The revision rate of the DSA has not been investigated previously using arthroplasty registry data. We examined the reasons and risk of revision of the DSA, compared with the direct anterior approach (DAA) and PLA. Patients and methods: In this population-based cohort study we included 175,543 primary THAs performed between 2014 and 2020 (PLA, n = 117,576; DAA, n = 56,626; DSA, n = 1,341). Competing risk survival analysis and multivariable Cox proportional hazard analyses, adjusted for potential confounders, were performed. Results: After 3 years, crude revision rates due to any reason were 2.1% (95% confidence interval [CI] 1.3–3.3) for DSA, and 2.9% (CI 2.8–3.0) for PLA. Crude dislocation revision rates were 0.3% (CI 0.1–0.8) for DSA, versus 1.0% (CI 0.9–1.0) for PLA. Dislocation revision rate for DSA did not differ from DAA (0.3% [CI 0.2–0.3]). Multivariable Cox regression analysis demonstrated no overall difference in revision rates for the DSA (HR 0.6 [CI 0.4–1.09) compared with the PLA. Lower risk of revision due to dislocation was found in patients operated on through the DSA (HR 0.3 [0.1–0.9]) compared with the PLA. Conclusion: Early nationwide results suggest that the DSA for total hip arthroplasty seems to show a tendency towards a lower risk of revision for dislocation but no overall reduced revision risk compared with the PLA.

Background and purpose: In the last decade, the direct anterior approach (DAA) for total hip arthroplasty (THA) has become more popular in the Netherlands. Therefore, we investigated the learning curve and survival rate of the DAA in primary THA, using data from the Dutch Arthroplasty Register (LROI). Patients and methods: We identified all patients who received a primary THA using the DAA in several high-volume centers in the Netherlands between 2007 and 2019 (n = 15,903). Procedures were ordered per surgeon, using date of operation. Using the procedure number, operations were divided into 6 groups based on the number of previous procedures per surgeon (first 25, 26–50, 51–100, 101–150, 151–200, > 200). Data from different surgeons in different hospitals was pooled together. Revision rates were calculated using a multilevel time-to-event analysis. Results: Patients operated on in group 1–25 (hazard ratio [HR] 1.6; 95% CI 1.1–2.4) and 26–50 (HR 1.6; CI 1.1–2.5) had a higher risk for revision compared with patients operated on in group > 200 THAs. Between 50 and 100 procedures the revision risk was increased (HR 1.3; CI 0.9–1.9), albeit not statistically significant. From 100 procedures onwards the HR for revision was respectively 1.0 (CI 0.6–1.6) and 0.8 (CI 0.5–1.4) for patients in operation groups 101–150 and 151–200. Main reasons for revision were loosening of the stem (29%), periprosthetic infection (19%), and dislocation (16%). Interpretation: We found a 64% increased risk of revision for patients undergoing THA using the DAA for the first 50 cases per surgeon. Between 50 and 100 cases, this risk was 30% increased, but not statistically significant. From 100 cases onwards, a steady state had been reached in revision rate. The learning curve for DAA therefore is around 100 cases.

Background: Recently, surgeons introduced a minimally invasive modification on the classic posterolateral approach (PLA) in total hip arthroplasty (THA): the direct superior approach (DSA). We investigated the association between surgeon's experience and the risk of early revision of the DSA in primary THA, using data from the Dutch Arthroplasty Register (LROI). Methods: We retrieved all primary THAs performed using the DSA in 4 hospitals between 2016 and 2022 (n = 1551). Procedures were sorted in 5 groups using the date of operation and number of previous procedures per surgeon: 1–25; 26–50; 51–75; 76–100; >100. Subsequently, data from different surgeons were pooled together and the risk of revision was calculated via a multilevel time-to-event analysis. Results: The overall revision rate was 1.5% after a mean follow-up of 2 years. Patients from the 1–25 group had comparable risks of revision compared to patients in the >100 group (hazard ratio [HR] 1.0 [CI, 0.3–3.2]). The risk for patients in groups 26–50, 51–75 and 75–100 was also not statistically different from the >100 group (resp. HR 1.5 [CI, 0.5–5.0], 1.8 [CI, 0.5–6.4] and 0.5 [CI, 0.1–4.0]). Main reasons of revision were dislocation (0.5%) and infection (0.4%). Conclusions: We did not identify an association between the surgeon's experience and the early risk of revision for the DSA in primary THA in the Netherlands. The DSA seems safe in the early adoption phases with a low risk of revision due to dislocation and revision for all other causes. [ABSTRACT FROM AUTHOR]

Background: Estimating the risk of revision after arthroplasty could inform patient and surgeon decision-making. However, there is a lack of well-performing prediction models assisting in this task, which may be due to current conventional modeling approaches such as traditional survivorship estimators (such as Kaplan-Meier) or competing risk estimators. Recent advances in machine learning survival analysismight improve decision support tools in this setting. Therefore, this study aimed to assess the performance of machine learning compared with that of conventional modeling to predict revision after arthroplasty. Question/purpose: Does machine learning perform better than traditional regression models for estimating the risk of revision for patients undergoing hip or knee arthroplasty?. Methods: Eleven datasets from published studies from the Dutch Arthroplasty Register reporting on factors associated with revision or survival after partial or total knee and hip arthroplasty between 2018 and 2022 were included in our study. The 11 datasets were observational registry studies, with a sample size ranging from 3038 to 218,214 procedures. We developed a set of time-to-event models for each dataset, leading to 11 comparisons. A set of predictors (factors associated with revision surgery) was identified based on the variables that were selected in the included studies. We assessed the predictive performance of two state-of-the-art statistical time-to-event models for 1-, 2-, and 3-year follow-up: a Fine and Gray model (which models the cumulative incidence of revision) and a causespecific Cox model (which models the hazard of revision). These were compared with a machine-learning approach (a random survival forest model, which is a decision tree-based machine-learning algorithm for time-to-event analysis). Performance was assessed according to discriminative ability (time-dependent area under the receiver operating curve), calibration (slope and intercept), and overall prediction error (scaled Brier score). Discrimination, known as the area under the receiver operating characteristic curve, measures the model's ability to distinguish patients who achieved the outcomes from those who did not and ranges from 0.5 to 1.0, with 1.0 indicating the highest discrimination score and 0.50 the lowest. Calibration plots the predicted versus the observed probabilities; a perfect plot has an intercept of 0 and a slope of 1. The Brier score calculates a composite of discrimination and calibration, with 0 indicating perfect prediction and 1 the poorest. A scaled version of the Brier score, 1 - (model Brier score/null model Brier score), can be interpreted as the amount of overall prediction error. Results: Using machine learning survivorship analysis, we found no differences between the competing risks estimator and traditional regression models for patients undergoing arthroplasty in terms of discriminative ability (patients who received a revision compared with those who did not). We found no consistent differences between the validated performance (time-dependent area under the receiver operating characteristic curve) of different modeling approaches because these values ranged between -0.04 and 0.03 across the 11 datasets (the time-dependent area under the receiver operating characteristic curve of the models across 11 datasets ranged between 0.52 to 0.68). In addition, the calibration metrics and scaled Brier scores produced comparable estimates, showing no advantage of machine learning over traditional regression models. Conclusion: Machine learning did not outperform traditional regression models. Clinical Relevance: Neither machine learning modeling nor traditional regression methods were sufficiently accurate in order to offer prognostic information when predicting revision arthroplasty. The benefit of these modeling approaches may be limited in this context. [ABSTRACT FROM AUTHOR]

Background and purpose — Alternative bearing surfaces such as ceramics and highly crosslinked polyethylene (HXLPE) were developed in order to further improve implant performance of total hip arthroplasties (THAs). Whether these alternative bearing surfaces result in increased longevity is subject to debate. Patients and methods — Using the Dutch Arthroplasty Register (LROI), we identified all patients with a primary, non-metal-on-metal THA implanted in the Netherlands in the period 2007–2016 (n = 209,912). Cumulative incidence of revision was calculated to determine differences in survivorship of THAs according to bearing type: metal-on-polyethylene (MoPE), metal-on-HXLPE (MoHXLPE), ceramic-on-polyethylene (CoPE), ceramic-on-HXLPE (CoHXLPE), ceramic-on-ceramic (CoC), and oxidized-zirconium-on-(HXL)polyethylene (Ox(HXL)PE). Multivariable Cox proportional hazard regression ratios (HRs) were used for comparisons. Results — After adjustment for confounders, CoHXLPE, CoC, and Ox(HXL)PE resulted in a statistically significantly lower risk of revision compared with MoPE after 9 years follow-up (HR =0.8–0.9 respectively, compared with HR =1.0). For small (22–28 mm) femoral head THAs, lower revision rates were found for CoPE and CoHXLPE (HR =0.9). In the 36 mm femoral head subgroup, CoC-bearing THAs had a lower HR compared with MoHXLPE (HR =0.7 versus 1.0). Crude revision rates in young patients (< 60 years) for CoHXLPE, CoC, and Ox(HXL)PE (HR =0.7) were lower than MoPE (HR =1.0). However, after adjustment for case mix and confounders these differences were not statistically significant. Interpretation — We found a mid-term lower risk of revision for CoHXLPE, CoC, and Ox(HXL)PE bearings compared with traditional MoPE-bearing surfaces.

An international, multiple-code benchmark test (BMT) study is being conducted within the international DECOVALEX project to analyse coupled thermal, hydrological, mechanical and chemical (THMC) processes in the excavation disturbed zone (EDZ) around emplacement drifts of a nuclear waste repository. This BMT focuses on mechanical responses and long-term chemo-mechanical effects that may lead to changes in mechanical and hydrological properties in the EDZ. This includes time-de-pendent processes such as creep, and subcritical crack, or healing of fractures that might cause "weakening" or "hardening" of the rock over the long term. Five research teams are studying this BMT using a wide range of model approaches, including boundary element, finite element, and finite difference, particle mechanics, and elasto-plastic cellular automata methods. This paper describes the definition of the problem and preliminary simulation results for the initial model inception part, in which time dependent effects are not yet included.

Background and purpose — Combining components from different manufacturers in total hip arthroplasty (THA) is common practice worldwide. We determined the proportion of THAs used in the Netherlands that consist of components from different manufacturers, and compared the revision rates of these mixed THAs with those of non-mixed THAs. Patients and methods — Data on primary and revision hip arthroplasty are recorded in the LROI, the nationwide population-based arthroplasty register in the Netherlands. We selected all 163,360 primary THAs that were performed in the period 2007–2014. Based on the manufacturers of the components, 4 groups were discerned: non-mixed THAs with components from the same manufacturer (n = 142,964); mixed stem-head THAs with different manufacturers for the femoral stem and head (n = 3,663); mixed head-cup THAs with different head and cup manufacturers (n = 12,960), and mixed stem-head-cup THAs with different femoral stem, head, and cup manufacturers (n = 1,773). Mixed prostheses were defined as THAs (stem, head, and cup) composed of components made by different manufacturers. Results — 11% of THAs had mixed components (n = 18,396). The 6-year revision rates were similar for mixed and non-mixed THAs: 3.4% (95% CI: 3.1w–3.7) for mixed THAs and 3.5% (95% CI: 3.4–3.7) for non-mixed THAs. Revision of primary THAs due to loosening of the acetabulum was more common in mixed THAs (16% vs. 12%). Interpretation — Over an 8-year period in the Netherlands, 11% of THAs had mixed components—with similar medium-term revision rates to those of non-mixed THAs.