Choice of Bearings Influences the Implant Survival of Total Hip Arthroplasty in Patients Who Have Osteoarthritis Aged 55 Years or More: Results of 158,044 Patients from the Nordic Arthroplasty Register Association from 2005 to 2017.

BACKGROUND: The aim of our study was to compare implant survival rates of different total hip arthroplasty (THA) bearings in the Nordic Arthroplasty Register Association. METHODS: All conventional primary THAs performed between 2005 and 2017 in patients over 55 years of age who had primary osteoarthritis were studied. Metal-on-highly crosslinked polyethylene (MoXLP), ceramic-on-highly crosslinked polyethylene (CoXLP), ceramic-on-ceramic (CoC), and metal-on-metal (MoM) bearings were included. The outcome was a revision. Kaplan-Meier (KM) estimates were calculated at 5 and 10 years. The risk for revision was analyzed using a flexible parametric survival model (FPSM) adjusted for nation, age, sex, femoral head size, and femoral fixation. RESULTS: A total of 158,044 THAs were included. The 5-year KM estimates were 95.9% (95% confidence interval [CI] 95.8 to 96.1) in MoXLP, 95.8% (95.6 to 96.1) in CoXLP, 96.7% (96.4 to 97.0) in CoC, and 93.9% (93.5 to 94.4) in MoM. The 10-year KM estimates were 94.2% (94.0 to 94.5) in MoXLP, 94.3% (93.9 to 94.8) in CoXLP, 95.4% (95.0 to 95.9) in CoC, and 85.5% (84.9 to 86.2) in MoM. Compared with MoXLP, the adjusted risk for revision was lower in CoC (hazard ratio [HR] 0.6, CI 0.5 to 0.6), similar in CoXLP (1.0, 0.9 to 1.0), and higher in MoM (1.3, 1.2 to 1.4). CONCLUSIONS: We found that MoXLP, CoXLP, and CoC bearings evinced comparably high implant survival rates up to 10 years, and they can all be regarded as safe options in this patient group. The MoM bearings were associated with clearly lower survivorship. The CoC bearings had the highest implant survival and a lower adjusted risk for revision compared with XLP bearings.

A Comprehensive Approach to PROMs in Elective Orthopedic Surgery: Comparing Effect Sizes across Patient Subgroups.

Background: There is limited knowledge regarding the comparative patient-reported outcomes (PROMs) and effect sizes (ESs) across orthopedic elective surgery. Methods: All patient data between January 2020 and December 2022 were collected, and treatment outcomes assessed as a PROM difference between baseline and one-year follow-up. The cohort was divided into subgroups (hand, elbow, shoulder, spine, hip, knee, and foot/ankle). The PROM ESs were calculated for each patient separately, and patients with ES > 0.5 were considered responders. Results: In total, 7695 patients were operated on. The mean ES across all patient groups was 1.81 (SD 1.41), and the largest ES was observed in shoulder patients and the smallest in hand patients. Overall, shoulder, hip, and knee patients had a larger ES compared to hand, spine, and foot/ankle patients (p < 0.0001). The proportion of positive responders ranged between 91-94% in the knee, shoulder, and hip, and 69-70% in the hand, spine, and foot/ankle subgroups. Conclusions: The ESs are generally high throughout elective orthopedic surgery. However, based on our institutional observations, shoulder, hip, and knee patients experience larger treatment effects compared to hand, spine, and foot/ankle patients, among whom there are also more non-responders. The expected treatment outcomes should be clearly communicated to patients when considering elective surgery. Because of the study limitations, the results should be approached with some caution.

Prediction of Early Adverse Events After THA: A Comparison of Different Machine-Learning Strategies Based on 262,356 Observations From the Nordic Arthroplasty Register Association (NARA) Dataset.

OBJECTIVE: Preoperative risk prediction models can support shared decision-making before total hip arthroplasties (THAs). Here, we compare different machine-learning (ML) approaches to predict the six-month risk of adverse events following primary THA to obtain accurate yet simple-to-use risk prediction models. METHODS: We extracted data on primary THAs (N = 262,356) between 2010 and 2018 from the Nordic Arthroplasty Register Association dataset. We benchmarked a variety of ML algorithms in terms of the area under the receiver operating characteristic curve (AUROC) for predicting the risk of revision caused by periprosthetic joint infection (PJI), dislocation or periprosthetic fracture (PPF), and death. All models were internally validated against a randomly selected test cohort (one-third of the data) that was not used for training the models. RESULTS: The incidences of revisions because of PJI, dislocation, and PPF were 0.8%, 0.4%, and 0.3%, respectively, and the incidence of death was 1.2%. Overall, Lasso regression with stable iterative variable selection (SIVS) produced models using only four to five input variables but with AUROC comparable to more complex models using all 32 variables available. The SIVS-based Lasso models based on age, sex, preoperative diagnosis, bearing couple, fixation, and surgical approach predicted the risk of revisions caused by PJI, dislocations, and PPF, as well as death, with AUROCs of 0.61, 0.67, 0.76, and 0.86, respectively. CONCLUSION: Our study demonstrates that satisfactory predictive potential for adverse events following THA can be reached with parsimonious modeling strategies. The SIVS-based Lasso models may serve as simple-to-use tools for clinical risk assessment in the future.

Periprosthetic Joint Infection After Total Knee Arthroplasty With or Without Antibiotic Bone Cement.

Importance: Despite increased use of antibiotic-loaded bone cement (ALBC) in joint arthroplasty over recent decades, current evidence for prophylactic use of ALBC to reduce risk of periprosthetic joint infection (PJI) is insufficient. Objective: To compare the rate of revision attributed to PJI following primary total knee arthroplasty (TKA) using ALBC vs plain bone cement. Design, Setting, and Participants: This international cohort study used data from 14 national or regional joint arthroplasty registries in Australia, Denmark, Finland, Germany, Italy, New Zealand, Norway, Romania, Sweden, Switzerland, the Netherlands, the UK, and the US. The study included primary TKAs for osteoarthritis registered from January 1, 2010, to December 31, 2020, and followed-up until December 31, 2021. Data analysis was performed from April to September 2023. Exposure: Primary TKA with ALBC vs plain bone cement. Main Outcomes and Measures: The primary outcome was risk of 1-year revision for PJI. Using a distributed data network analysis method, data were harmonized, and a cumulative revision rate was calculated (1 - Kaplan-Meier), and Cox regression analyses were performed within the 10 registries using both cement types. A meta-analysis was then performed to combine all aggregated data and evaluate the risk of 1-year revision for PJI and all causes. Results: Among 2 168 924 TKAs included, 93% were performed with ALBC. Most TKAs were performed in female patients (59.5%) and patients aged 65 to 74 years (39.9%), fully cemented (92.2%), and in the 2015 to 2020 period (62.5%). All participating registries reported a cumulative 1-year revision rate for PJI of less than 1% following primary TKA with ALBC (range, 0.21%-0.80%) and with plain bone cement (range, 0.23%-0.70%). The meta-analyses based on adjusted Cox regression for 1 917 190 TKAs showed no statistically significant difference at 1 year in risk of revision for PJI (hazard rate ratio, 1.16; 95% CI, 0.89-1.52) or for all causes (hazard rate ratio, 1.12; 95% CI, 0.89-1.40) among TKAs performed with ALBC vs plain bone cement. Conclusions and Relevance: In this study, the risk of revision for PJI was similar between ALBC and plain bone cement following primary TKA. Any additional costs of ALBC and its relative value in reducing revision risk should be considered in the context of the overall health care delivery system.