Aims. The primary aim was to assess whether preoperative health-related quality of life (HRQoL) was associated with postoperative mortality following total hip arthroplasty (THA) and knee arthroplasty (KA). Secondary aims were to assess whether patient demographics/comorbidities and/or joint-specific function were associated with postoperative mortality. Methods. Patients undergoing THA (n = 717) and KA (n = 742) during a one-year period were identified retrospectively from an arthroplasty register. Patient demographics, comorbidities, Oxford score, and EuroQol five-dimension (EQ-5D) were recorded preoperatively. Patients were followed up for a minimum of seven years and their mortality status was obtained. Cox regression analysis was used to adjust for confounding. Results. During the study period, 111 patients (15.5%) undergoing THA and 135 patients (18.2%) undergoing KA had died at a mean follow-up of 7.5 years (7 to 8). When adjusting for confounding, the preoperative EQ-5D was associated with postoperative mortality, and for each 0.1 difference in the utility there was an associated change in mortality risk of 6.7% (p = 0.048) after THA, and 6.8% (p = 0.047) after KA. Comorbidities of connective tissue disease (p ≤ 0.026) and diabetes (p ≤ 0.028) were associated with mortality after THA, whereas MI (p ≤ 0.041), diabetes (p ≤ 0.009), and pain in other joints (p ≤ 0.050) were associated with mortality following KA. The preoperative Oxford score was associated with mortality, and for each one-point change in the score there was an associated change in mortality risk of 2.7% (p = 0.025) after THA and 4.3% (p = 0.003) after KA. Conclusion. Worse preoperative HRQoL and joint specific function were associated with an increased risk of postoperative mortality. Both HRQoL and joint-specific function decline with longer waiting times to surgery for THA and KA and therefore may result in an increased postoperative mortality risk than would have been expected if surgery had been undertaken earlier. Cite this article: Bone Jt Open 2022;3(12):933–940

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

Aims. The aims were to assess whether preoperative joint-specific function (JSF) and health-related quality of life (HRQoL) were associated with level of clinical frailty in patients waiting for a primary total hip arthroplasty (THA) or knee arthroplasty (KA). Methods. Patients waiting for a THA (n = 100) or KA (n = 100) for more than six months were prospectively recruited from the study centre. Overall,162 patients responded to the questionnaire (81 THA; 81 KA). Patient demographics, Oxford score, EuroQol five-dimension (EQ-5D) score, EuroQol visual analogue score (EQ-VAS), Rockwood Clinical Frailty Score (CFS), and time spent on the waiting list were collected. Results. There was a significant correlation between CFS and the Oxford score (THA r = −0.838; p < 0.001, KA r = −0.867; p < 0.001), EQ-5D index (THA r = −0.663, p =< 0.001; KA r = −0.681; p =< 0.001), and EQ-VAS (THA r = −0.414; p < 0.001, KA r = −0.386; p < 0.001). Confounding variables (demographics and waiting time) where adjusted for using multiple regression analysis. For each 8.5 (THA, 95% CI 7.1 to 10.0; p < 0.001) and 9.9 (KA, 95% CI 8.4 to 11.4; p < 0.001) point change in the Oxford score, there was an associated change in level of the CFS. For each 0.16 (THA, 95% CI 0.10 to 0.22; p < 0.001) and 0.20 (KA, 95% CI 0.12 to 0.27; p < 0.001) utility change in EQ-5D, there was an associated change in level of the CFS. EQ-VAS (THA, B = −11.5; p < 0.001, KA B = −7.9; p = 0.005) was also associated with CFS. Conclusion. JSF and HRQoL in patients awaiting THA or KA for more than six months, were independently associated with level of clinical frailty. With further prospective studies, clinical frailty may prove to be a useful metric to assist in the prioritization of arthroplasty waiting lists. Cite this article: Bone Jt Open 2023;4(4):241–249

Introduction. Knee arthroplasty (KA), encompassing Total Knee Replacement (TKR) and Unicompartmental Knee Replacement (UKR), is one of the most common orthopedic procedures, aimed at alleviating severe knee arthritis. Postoperative KA management, especially radiographic imaging, remains a substantial financial burden and lacks standardised protocols for its clinical utility during follow-up. Method. In this retrospective multicentre cohort study, data were analysed from January 2014 to March 2020 for adult patients undergoing primary KA at Imperial NHS Trust. Patients were followed over a five-year period. Four machine learning models were developed to evaluate if post-operative X-ray frequency can predict revision surgery. The best-performing model was used to assess the risk of revision surgery associated with different number of X-rays. Result. The study assessed 289 knees with a 2.4% revision rate. The revision group had more X-rays on average than the primary group. The best performing model was Logistic Regression (LR), which indicated that each additional X-ray raised the revision risk by 52% (p<0.001). Notably, having four or more X-rays was linked to a three-fold increase in risk of revision (OR=3.02; p<0.001). Our results align with the literature that immediate post-operative X-rays have limited utility, making the 2nd post-operative X-ray of highest importance in understanding the patient's trajectory. These insights can enhance management by improving risk stratification for patients at higher revision surgery risk. Despite LR being the best-performing model, it is limited by the dataset's significant class imbalance. Conclusion. X-ray frequency can independently predict revision surgery. This study provides insights that can guide surgeons in evidence-based post-operative decision-making. To use those findings and influence post-operative management, future studies should build on this predictive model by incorporating a more robust dataset, surgical indications, and X-ray findings. This will allow early identification of high-risk patients, allowing for personalised post-operative recommendations

The aims were to assess whether preoperative joint-specific function (JSF) and health-related quality of life (HRQoL) were associated with level of clinical frailty in patients waiting for a primary total hip arthroplasty (THA) or knee arthroplasty (KA). Patients waiting for a THA (n=100) or KA (n=100) for more than six months were prospectively recruited from the study centre. Overall, 162 patients responded to the questionnaire (81 THA; 81 KA). Patient demographics, Oxford score, EuroQol five dimension (EQ-5D) score, EuroQol visual analogue score (EQ-VAS), Rockwood Clinical Frailty Score (CFS), and time spent on the waiting list were collected. There was a significant correlation between CFS and the Oxford score (THA r=ˆ’0.838; p<0.001, KA r=ˆ’0.867; p<0.001), EQ-5D index (THA r=ˆ’0.663, p<0.001; KA r=ˆ’0.681; p< 0.001), and EQ-VAS (THA r=ˆ’0.414; p<0.001, KA r=ˆ’0.386; p<0.001). Confounding variables (demographics and waiting time) where adjusted for using multiple regression analysis. For each 8.5 (THA, 95% CI 7.1 to 10.0; p<0.001) and 9.9 (KA, 95% CI 8.4 to 11.4; p<0.001) point change in the Oxford score, there was an associated change in level of the CFS. For each 0.16 (THA, 95% CI 0.10 to 0.22; p<0.001) and 0.20 (KA, 95% CI 0.12 to 0.27; p<0.001) utility change in EQ-5D, there was an associated change in level of the CFS. EQ-VAS (THA, B=ˆ’11.5; p<0.001, KA B=ˆ’7.9; p=0.005) was also associated with CFS. JSF and HRQoL in patients awaiting THA or KA for more than six months, were independently associated with level of clinical frailty. With further prospective studies, clinical frailty may prove to be a useful metric to assist in the prioritization of arthroplasty waiting lists

Abstract. Introduction. The Wells score is commonly used to assess the risk of proximal Deep Vein Thrombosis (DVT) following Knee Arthroplasty (KA). The National Institute for Health and Care Excellence (NICE) guidelines recommend an Ultrasound scan in patients with a Wells score of 2 points or more. We wanted to assess how often this protocol resulted in a scan being done and how many were negative. Methodology. Details of all postoperative Ultrasound scans performed up to 90 days were audited in a high-volume unit between 1st January 2016 and 31st December 2020. This included all Lower Limb Arthroplasty patients. Results. Out of a total of 4955 KA (4506 Total Knee Arthroplasty, 449 Unilateral Knee Arthroplasty), 449 (9.1%) had a total of 561 scans, with 17 (3.0%) scans demonstrating a proximal DVT. Thus 97.0% of Ultrasound scans were negative. Conclusion. The present NICE guidelines with the two-Level DVT Wells score are inappropriate for the management of suspected proximal DVT following KA. We propose that swelling that fails to reduce after 4 hours of elevation, or new swelling after a period of recumbent rest, would be more appropriate indications for a scan and negative scans should not be repeated without a change in symptoms. Unless there are pressing clinical indications, therapeutic anticoagulation should not commence in the absence of a diagnosis

Aims. The aim of this study was to assess the quality of life of patients on the waiting list for a total hip (THA) or knee arthroplasty (KA) during the COVID-19 pandemic. Secondary aims were to assess whether length of time on the waiting list influenced quality of life and rate of deferral of surgery. Methods. During the study period (August and September 2020) 843 patients (THA n = 394, KA n = 449) from ten centres in the UK reported their EuroQol five dimension (EQ-5D) scores and completed a waiting list questionnaire (2020 group). Patient demographic details, procedure, and date when listed were recorded. Patients scoring less than zero for their EQ-5D score were defined to be in a health state “worse than death” (WTD). Data from a retrospective cohort (January 2014 to September 2017) were used as the control group. Results. The 2020 group had a significantly worse EQ-5D score compared to the control group for both THA (p < 0.001) and KA (p < 0.001). Over one-third (35.0%, n = 138/394) of patients waiting for a THA and nearly a quarter (22.3%, n = 100/449) for KA were in a health state WTD, which was significantly greater than the control group (odds ratio 2.30 (95% confidence interval (CI) 1.83 to 2.93) and 2.08 (95% CI 1.61 to 2.70), respectively; p < 0.001). Over 80% (n = 680/843) of the 2020 group felt that their quality of life had deteriorated while waiting. Each additional month spent on the waiting list was independently associated with a decrease in quality of life (EQ-5D: -0.0135, p = 0.004). There were 117 (13.9%) patients who wished to defer their surgery and the main reason for this was health concerns for themselves and or their family (99.1%, n = 116/117). Conclusion. Over one-third of patients waiting for THA and nearly one-quarter waiting for a KA were in a state WTD, which was approaching double that observed prior to the pandemic. Increasing length of time on the waiting list was associated with decreasing quality of life. Level of evidence: Level III retrospective case control study. Cite this article: Bone Joint J 2021;103-B(4):672–680

Introduction. Automated identification of arthroplasty implants could aid in pre-operative planning and is a task which could be facilitated through artificial intelligence (AI) and deep learning. The purpose of this study was to develop and test the performance of a deep learning system (DLS) for automated identification and classification of knee arthroplasty (KA) on radiographs. Methods. We collected 237 AP knee radiographs with equal proportions of native knees, total KA (TKA), and unicompartmental KA (UKA), as well as 274 radiographs with equal proportions of Smith & Nephew Journey and Zimmer NexGen TKAs. Data augmentation was used to increase the number of images available for DLS development. These images were used to train, validate, and test deep convolutional neural networks (DCNN) to 1) detect the presence of TKA; 2) differentiate between TKA and UKA; and 3) differentiate between the 2 TKA models. Receiver operating characteristic (ROC) curves were generated with area under the curve (AUC) calculated to assess test performance. Results. The DCNNs trained to detect KA and to distinguish between TKA and UKA both achieved AUC of 1. In both cases, heatmap analysis demonstrated appropriate emphasis of the KA components in decision-making. The DCNN trained to distinguish between the 2 TKA models also achieved AUC of 1. Heatmap analysis of this DCNN showed emphasis of specific unique features of the TKA model designs for decision making, such as the anterior flange shape of the Zimmer NexGen TKA (Figure 1) and the tibial baseplate/stem shape of the Smith & Nephew Journey TKA (Figure 2). Conclusion. DCNNs can accurately identify presence of TKA and distinguish between specific designs. The proof-of-concept of these DCNNs may set the foundation for DCNNs to identify other prosthesis models and prosthesis-related complications. For any figures or tables, please contact the authors directly

Introduction. Knee arthroplasty (KA) is a highly effective surgical procedure. However, research suggests that a considerable number of patients continue to experience substantial pain and functional loss following surgical recovery. We aimed to estimate pain and function outcome trajectories for persons undergoing KA depicting the outcome, the relationship between the pain and function trajectory types, and pre-surgery predictors of trajectory type (i.e., good versus poor). Methods. Participants included 384 patients who took part in the Knee Arthroplasty Skills Training (KASTPain) clinical trial. Pain and function was assessed at 2-week pre- and 2-, 6-, and 12-month post-surgery using the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) Pain and Function Scales. Piecewise latent class growth models were used to estimate pain and function trajectories. Dumenci's latent kappa was used to estimate the chance-corrected agreement between pain and function trajectory types. Pre-surgery variables were used to predict trajectory types. Results. There was strong evidence for two trajectory types, labeled as good and poor, for both WOMAC pain and function scores. Model estimated rates of the poor trajectory type were 18% for both pain and function. Dumenci's latent kappa between pain and function trajectory types was 0.71 (95% CI: 0.61 – 0.80). Most pre-surgery variables were not significant predictors of the trajectory types. Conclusions. Among adults with moderate to severe pain catastrophizing undergoing KA, approximately one-fifth of patients continue to have persistent pain, poor function, or both, which is similar to the rate of poor reported outcomes in the TKA population overall. Although the poor pain and function trajectory types tend to go together within persons, a significant number of patients experience either poor pain or function but not both, suggesting heterogeneity among persons who do not fully benefit from KA. For figures, tables, or references, please contact authors directly

Purpose. The Oxford Knee Score (OKS) is a validated and widely used PROM that has been successfully used in assessing the outcome of knee arthroplasty (KA). It has been adopted as the nationally agreed outcome measure for this procedure and is now routinely collected. Increasingly, it is being used on an individual patient basis as a pre-operative measure of osteoarthritis and the need for joint replacement, despite not being validated for this use. The aim of this paper is to present evidence that challenges this new role for the OKS. Method. We have analysed pre-operative and post-operative OKS data from 3 large cohorts all undergoing KA, totalling over 3000 patients. In addition we have correlated the OKS to patient satisfaction scores. We have validated our findings using data published from the UK NJR. Results. Our data confirms of the effectiveness of the OKS in assessing the results of KA in populations of patients. Nearly all patients who undergo KA have an improvement in their OKS, regardless of the pre-operative score. However, we have found that the pre-operative OKS cannot predict a poor outcome after KA and patients with the best pre-operative OKS have the best outcome as measured by patient satisfaction. Conclusion. These data suggest that the OKS remains an excellent tool for assessing the outcome of knee arthroplasty in cohorts of patients, but further evidence is required of its validity for decisions regarding individual patients. Great care should be taken in using the pre-operative OKS to predict outcome after KA and its use in ranking patients need for surgery cannot be supported

A 5 year review of factors instigating malpractice claims and likely to result in a payout. Possible lessons for the future. Background. During 2002-2007 over 300,000 patients underwent knee arthroplasty (KA) in England and Wales, from which 204 cases of litigation were processed costing in excess of £5million. The complications associated with primary KA are well documented, however those instigating litigation in the UK are not known. This study assessed trends in litigation over the past 5 years identifying instigating factors and success rates to highlight areas for further improvement in patient information and surgical management. Methods. Data from the NHS Litigation Authority on claims following KA unrelated to trauma between 2002 and 2007 were obtained and analysed. Results. 246 claims were made, 171 (70%) were settled of which 81 (47%) resulted in a successful claim. The total cost to the NHS was £5,257,228. The number of claims has increased from 26 in 2002 to 67 in 2007, while the rate of successful claims decreased from 58% to 9%. The three most common instigating factors were ongoing pain(24%), operator error(23%) and infection(10%). The factors with greatest successful claims were operator error(80%), vascular injuries(75%), failure of post-operative care(55%). Conclusion. Litigation claims following KA are increasing, although there rate of success is decreasing. Operator error, vascular injuries and failure of post-operative care are predictors of a successful claim. However failure to consent adequately, adhere to policies and standard practice can result in a successful claim. Protecting patients intra-operatively and maintaining high technical expertise while implementing policies and informed consent decreases the litigation burden to the NHS

Introduction. We examined the effect on blood loss of two standardised intravenous bolus doses of 500 mg of Tranexamic Acid, a fibrinolytic inhibitor that reduces blood loss following Knee Arthroplasty (KA). Materials and Methods. Our study included one hundred consecutive patients undergoing primary cemented KA, who received two standarised bolus doses of 500 mg of Tranexamic Acid. The first dose was administered at induction to anaesthetic and the second dose was administered just before the closure. Data, which included Haemoglobin (Hb), Haematocrit (Hct), Length of Hospital Stay (LOS) and complications, was collected prospectively by an independent observer. Routine blood tests were done on the 1. st. or 2. nd. post-operative day. Results. Out of 100 patients aged from 49 to 92 years old (mean age of 69 years), 39 were male and 48 underwent a right KA. The mean LOS was 4.73 days with a standard deviation (SD) of 3.07 days. The mean drop of Hb was 2.04 g/dl (15.5%) with a SD of 0.89 g/dl (6.2%). The mean drop of Hct was 0.096 (16.7%) with a SD of 0.325 (10.0%). Only 2 patients had developed symptoms of anaemia and were transfused with 2 units of red blood cells each. Ultrasound scan was used to investigate patients with possible Deep Venous Thrombosis (DVT). Indications were calf pain and swelling of the lower limb. 10 patients were investigated, out of which in only 3 patients the diagnosis of DVT was confirmed, whereas in 2 patients DVT could not be excluded because of obesity. Conclusions. We believe that the use of two standardised intravenous bolus doses of 500 mg of Tranexamic Acid reduces peri-operative blood loss, reducing the need for transfusion, without increasing the risk of thromboembolic complications

Aims

The aim of this study was to determine satisfaction rates after hip and knee arthroplasty in patients who did not respond to postoperative patient-reported outcome measures (PROMs), characteristics of non-responders, and contact preferences to maximize response rates.