Aims. A substantial fraction of patients undergoing knee arthroplasty (KA) or hip arthroplasty (HA) do not achieve an improvement as high as the minimal clinically important difference (MCID), i.e. do not achieve a meaningful improvement. Using three patient-reported outcome measures (PROMs), our aim was: 1) to assess machine learning (ML), the simple pre-surgery PROM score, and logistic-regression (LR)-derived performance in their prediction of whether patients undergoing HA or KA achieve an improvement as high or higher than a calculated MCID; and 2) to test whether ML is able to outperform LR or pre-surgery PROM scores in predictive performance. Methods. MCIDs were derived using the change difference method in a sample of 1,843 HA and 1,546 KA patients. An artificial neural network, a gradient boosting machine, least absolute shrinkage and selection operator (LASSO) regression, ridge regression, elastic net, random forest, LR, and pre-surgery PROM scores were applied to predict MCID for the following PROMs: EuroQol five-dimension, five-level questionnaire (EQ-5D-5L), EQ visual analogue scale (EQ-VAS), Hip disability and Osteoarthritis Outcome Score-Physical Function Short-form (HOOS-PS), and Knee injury and Osteoarthritis Outcome Score-Physical Function Short-form (KOOS-PS). Results. Predictive performance of the best models per outcome ranged from 0.71 for HOOS-PS to 0.84 for EQ-VAS (HA sample). ML statistically significantly outperformed LR and pre-surgery PROM scores in two out of six cases. Conclusion. MCIDs can be predicted with reasonable performance. ML was able to outperform traditional methods, although only in a minority of cases. Cite this article: Bone Joint Res 2023;12(9):512–521

Objectives

We aimed first to summarise minimal clinically important differences (MCIDs) after total hip (THR) or knee replacement (TKR) in health-related quality of life (HRQoL), measured using the Short-Form 36 (SF-36). Secondly, we aimed to improve the precision of MCID estimates by means of meta-analysis.

Aims. The aim of this study was to report the meaningful values of the EuroQol five-dimension three-level questionnaire (EQ-5D-3L) and EuroQol visual analogue scale (EQ-VAS) in patients undergoing primary knee arthroplasty (KA). Methods. This is a retrospective study of patients undergoing primary KA for osteoarthritis in a university teaching hospital (Royal Infirmary of Edinburgh) (1 January 2013 to 31 December 2019). Pre- and postoperative (one-year) data were prospectively collected for 3,181 patients (median age 69.9 years (interquartile range (IQR) 64.2 to 76.1); females, n = 1,745 (54.9%); median BMI 30.1 kg/m. 2. (IQR 26.6 to 34.2)). The reliability of the EQ-5D-3L was measured using Cronbach’s alpha. Responsiveness was determined by calculating the anchor-based minimal clinically important difference (MCID), the minimal important change (MIC) (cohort and individual), the patient-acceptable symptom state (PASS) predictive of satisfaction, and the minimal detectable change at 90% confidence intervals (MDC-90). Results. The EQ-5D-3L demonstrated good internal consistency with an overall Cronbach alpha of 0.75 (preoperative) and 0.88 (postoperative), respectively. The MCID for the Index score was 0.085 (95% confidence interval (CI) 0.042 to 0.127) and EQ-VAS was 6.41 (95% CI 3.497 to 9.323). The MIC. COHORT. was 0.289 for the EQ-5D and 5.27 for the EQ-VAS. However, the MIC. INDIVIDUAL. for both the EQ-5D-3L Index (0.105) and EQ-VAS (-1) demonstrated poor-to-acceptable reliability. The MDC-90 was 0.023 for the EQ-5D-3L Index and 1.0 for the EQ-VAS. The PASS for the postoperative EQ-5D-3L Index and EQ-VAS scores predictive of patient satisfaction were 0.708 and 77.0, respectively. Conclusion. The meaningful values of the EQ-5D-3L Index and EQ-VAS scores can be used to measure clinically relevant changes in health-related quality of life in patients undergoing primary KA. Cite this article: Bone Joint Res 2022;11(9):619–628

Aims. To identify the responsiveness, minimal clinically important difference (MCID), minimal clinical important change (MIC), and patient-acceptable symptom state (PASS) thresholds in the 36-item Short Form Health Survey questionnaire (SF-36) (v2) for each of the eight dimensions and the total score following total knee arthroplasty (TKA). Methods. There were 3,321 patients undergoing primary TKA with preoperative and one-year postoperative SF-36 scores. At one-year patients were asked how satisfied they were and “How much did the knee arthroplasty surgery improve the quality of your life?”, which was graded as: great, moderate, little (n = 277), none (n = 98), or worse. Results. Physical function, role limitations due to physical problems (‘role physical’), bodily pain, and the total score SF-36 scores demonstrated the greatest effect sizes (> 0.9). The MCID for each of SF-36 dimensions ranged from 1.7 for role emotional to 6.4 for bodily pain. The MICs for a cohort of patients ranged from -1.0 for general health to 11.1 for bodily pain. The MICs for an individual patient were marginally greater (one to two points) compared to those for a cohort, and ranging from 0.0 for general and mental health to 13.5 for physical function. The lowest PASS score threshold was associated with physical function (> 34 points) whereas the greatest threshold (> 69 points) was associated with mental health. Conclusion. The SF-36 is a responsive tool, and the estimates for MCID, MIC, and PASS thresholds that can be used to power studies, assess whether there has been a meaningful change in patients’ health-related quality of life, and can be used as a marker of achieving patient satisfaction following TKA. Cite this article: Bone Joint Res 2022;11(7):477–483

The use of artificial intelligence (AI) is rapidly growing across many domains, of which the medical field is no exception. AI is an umbrella term defining the practical application of algorithms to generate useful output, without the need of human cognition. Owing to the expanding volume of patient information collected, known as ‘big data’, AI is showing promise as a useful tool in healthcare research and across all aspects of patient care pathways. Practical applications in orthopaedic surgery include: diagnostics, such as fracture recognition and tumour detection; predictive models of clinical and patient-reported outcome measures, such as calculating mortality rates and length of hospital stay; and real-time rehabilitation monitoring and surgical training. However, clinicians should remain cognizant of AI’s limitations, as the development of robust reporting and validation frameworks is of paramount importance to prevent avoidable errors and biases. The aim of this review article is to provide a comprehensive understanding of AI and its subfields, as well as to delineate its existing clinical applications in trauma and orthopaedic surgery. Furthermore, this narrative review expands upon the limitations of AI and future direction.

Cite this article: Bone Joint Res 2023;12(7):447–454.

Outcomes following different types of surgical intervention for femoroacetabular impingement (FAI) are well reported individually but comparative data are deficient. The purpose of this study was to conduct a systematic review (SR) and meta-analysis to analyze the outcomes following surgical management of FAI by hip arthroscopy (HA), anterior mini open approach (AMO), and surgical hip dislocation (SHD). This SR was registered with PROSPERO. An electronic database search of PubMed, Medline, and EMBASE for English and German language articles over the last 20 years was carried out according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. We specifically analyzed and compared changes in patient-reported outcome measures (PROMs), α-angle, rate of complications, rate of revision, and conversion to total hip arthroplasty (THA). A total of 48 articles were included for final analysis with a total of 4,384 hips in 4,094 patients. All subgroups showed a significant correction in mean α angle postoperatively with a mean change of 28.8° (95% confidence interval (CI) 21 to 36.5; p < 0.01) after AMO, 21.1° (95% CI 15.1 to 27; p < 0.01) after SHD, and 20.5° (95% CI 16.1 to 24.8; p < 0.01) after HA. The AMO group showed a significantly higher increase in PROMs (3.7; 95% CI 3.2 to 4.2; p < 0.01) versus arthroscopy (2.5; 95% CI 2.3 to 2.8; p < 0.01) and SHD (2.4; 95% CI 1.5 to 3.3; p < 0.01). However, the rate of complications following AMO was significantly higher than HA and SHD. All three surgical approaches offered significant improvements in PROMs and radiological correction of cam deformities. All three groups showed similar rates of revision procedures but SHD had the highest rate of conversion to a THA. Revision rates were similar for all three revision procedures.

Aims

The primary aim of this study was to compare the hip-specific functional outcome of robotic assisted total hip arthroplasty (rTHA) with manual total hip arthroplasty (mTHA) in patients with osteoarthritis (OA). Secondary aims were to compare general health improvement, patient satisfaction, and radiological component position and restoration of leg length between rTHA and mTHA.

Patient-reported outcome measures (PROMs) are being used increasingly in total knee arthroplasty (TKA). We conducted a systematic review aimed at identifying psychometrically sound PROMs by appraising their measurement properties. Studies concerning the development and/or evaluation of the measurement properties of PROMs used in a TKA population were systematically retrieved via PubMed, Web of Science, Embase, and Scopus. Ratings for methodological quality and measurement properties were conducted according to updated COnsensus-based Standards for the selection of health Measurement INstruments (COSMIN) methodology. Of the 155 articles on 34 instruments included, nine PROMs met the minimum requirements for psychometric validation and can be recommended to use as measures of TKA outcome: Oxford Knee Score (OKS); OKS–Activity and Participation Questionnaire (OKS-APQ); 12-item short form Knee Injury and Osteoarthritis Outcome (KOOS-12); KOOS Physical function Short form (KOOS-PS); Western Ontario and McMaster Universities Arthritis Index-Total Knee Replacement function short form (WOMAC-TKR); Lower Extremity Functional Scale (LEFS); Forgotten Joint Score (FJS); Patient’s Knee Implant Performance (PKIP); and University of California Los Angeles (UCLA) activity score. The pain and function subscales in WOMAC, as well as the pain, function, and quality of life subscales in KOOS, were validated psychometrically as standalone subscales instead of as whole instruments. However, none of the included PROMs have been validated for all measurement properties. Thus, further studies are still warranted to evaluate those PROMs. Use of the other 25 scales and subscales should be tempered until further studies validate their measurement properties.

Cite this article: Bone Joint Res 2021;10(3):203–217.

Aims

The primary aim of the study was to compare the knee-specific functional outcome of robotic unicompartmental knee arthroplasty (rUKA) with manual total knee arthroplasty (mTKA) for the management of isolated medial compartment osteoarthritis. Secondary aims were to compare length of hospital stay, general health improvement, and satisfaction between rUKA and mTKA.

Objectives

The primary aim of this study was to assess the reproducibility of the recalled preoperative Oxford Hip Score (OHS) and Oxford Knee Score (OKS) one year following arthroplasty for a cohort of patients. The secondary aim was to assess the reliability of a patient’s recollection of their own preoperative OHS and OKS one year following surgery.

Objectives

The purpose of this study was to evaluate the existing literature from 2005 to 2016 reporting on the efficacy of surgical management of patients with femoroacetabular impingement (FAI) secondary to slipped capital femoral epiphysis (SCFE).

Objectives

Preservation of posterior condylar offset (PCO) has been shown to correlate with improved functional results after primary total knee arthroplasty (TKA). Whether this is also the case for revision TKA, remains unknown. The aim of this study was to assess the independent effect of PCO on early functional outcome after revision TKA.

Objectives

The Kaplan-Meier estimation is widely used in orthopedics to calculate the probability of revision surgery. Using data from a long-term follow-up study, we aimed to assess the amount of bias introduced by the Kaplan-Meier estimator in a competing risk setting.