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 June 2024 Knee Roundup³⁶⁰ looks at: The estimated lifetime risk of revision after primary knee arthroplasty influenced by age, sex, and indication; Should high-risk patients seek out care from high-volume surgeons?; Stability and fracture rates in medial unicondylar knee arthroplasties; Rethinking antibiotic prophylaxis for dental procedures post-arthroplasty; Evaluating DAIR: a viable alternative for acute periprosthetic joint infection; The characteristics and predictors of mortality in periprosthetic fractures around the knee; Patient health-related quality of life deteriorates significantly while waiting six to 12 months for total hip or knee arthroplasty; The importance of looking for diversity in knee implants.

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

Aims

The primary aim was to assess change in health-related quality of life (HRQoL) of patients as they waited from six to 12 months for a total hip (THA) or total or partial knee arthroplasty (KA). Secondary aims were to assess change in joint-specific function, mental health, quality of sleep, number living in a state worse than death (WTD), wellbeing, and patient satisfaction with their healthcare.

The October 2023 Knee Roundup³⁶⁰ looks at: Cementless total knee arthroplasty is associated with more revisions within a year; Kinematically and mechanically aligned total knee arthroplasties: long-term follow-up; Aspirin thromboprophylaxis following primary total knee arthroplasty is associated with a lower rate of early periprosthetic joint infection compared with other agents; The impact of a revision arthroplasty network on patient outcomes; Re-revision knee arthroplasty in a tertiary centre: how does infection impact on outcomes?; Does the knee joint have its own microbiome?; Revision knee surgery provision in Scotland; Aspirin is a safe and effective thromboembolic prophylaxis after total knee arthroplasty: a systematic review and meta-analysis; Patellar resurfacing and kneeling ability after total knee arthroplasty: a systematic review.

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

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

The primary aim of this study was to assess whether patients waiting six months or more for a total hip (THA) or knee (KA) arthroplasty had a deterioration in their health-related quality of life (HRQoL). Secondary aims were to assess changes in frailty and the number of patients living in a state considered to be worse than death (WTD), and factors associated with changes in HRQoL and frailty.

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 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.

Aims. The aim of this study was to determine the long-term mortality rate, and to identify factors associated with this, following primary and revision knee arthroplasty (KA). Methods. Data from the Scottish Arthroplasty Project (1998 to 2019) were retrospectively analyzed. Patient mortality data were linked from the National Records of Scotland. Analyses were performed separately for the primary and revised KA cohorts. The standardized mortality ratio (SMR) with 95% confidence intervals (CIs) was calculated for the population at risk. Multivariable Cox proportional hazards were used to identify predictors and estimate relative mortality risks. Results. At a median 7.4 years (interquartile range (IQR) 4.0 to 11.6) follow-up, 27.8% of primary (n = 27,474/98,778) and 31.3% of revision (n = 2,611/8,343) KA patients had died. Both primary and revision cohorts had lower mortality rates than the general population (SMR 0.74 (95% CI 0.73 to 0.74); p < 0.001; SMR 0.83 (95% CI 0.80 to 0.86); p < 0.001, respectively), which persisted for 12 and eighteight years after surgery, respectively. Factors associated with increased risk of mortality after primary KA included male sex (hazard ratio (HR) 1.40 (95% CI 1.36 to 1.45)), increasing socioeconomic deprivation (HR 1.43 (95% CI 1.36 to 1.50)), inflammatory polyarthropathy (HR 1.79 (95% CI 1.68 to 1.90)), greater number of comorbidities (HR 1.59 (95% CI 1.51 to 1.68)), and periprosthetic joint infection (PJI) requiring revision (HR 1.92 (95% CI 1.57 to 2.36)) when adjusting for age. Similarly, male sex (HR 1.36 (95% CI 1.24 to 1.49)), increasing socioeconomic deprivation (HR 1.31 (95% CI 1.12 to 1.52)), inflammatory polyarthropathy (HR 1.24 (95% CI 1.12 to 1.37)), greater number of comorbidities (HR 1.64 (95% CI 1.33 to 2.01)), and revision for PJI (HR 1.35 (95% 1.18 to 1.55)) were independently associated with an increased risk of mortality following revision KA when adjusting for age. Conclusion. The SMR of patients undergoing primary and revision KA was lower than that of the general population and remained so for several years post-surgery. However, approximately one in four patients undergoing primary and one in three patients undergoing revision KA died within tenten years of surgery. Several patient and surgical factors, including PJI, were associated with the risk of mortality within ten years of primary and revision surgery. Cite this article: Bone Joint J 2022;104-B(1):45–52

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

Aims

The aim of this study was to give estimates of the incidence of component incompatibility in hip and knee arthroplasty and to test the effect of an online, real-time compatibility check.

Infection is a leading indication for revision arthroplasty. Established criteria used to diagnose prosthetic joint infection (PJI) include a range of laboratory tests. Leucocyte esterase (LE) is widely used on a colorimetric reagent strip for the diagnosis of urinary tract infections. This inexpensive test may be used for the diagnosis or exclusion of PJI. Aspirates from 30 total hip arthroplasties (THAs) and 79 knee arthroplasties (KA) were analysed for LE activity. Semi-quantitative reagent strip readings of 15, 70, 125 and 500 white blood cells (WBC) were validated against a manual synovial white cell count (WCC). A receiver operating characteristic (ROC) curve was constructed to determine the optimal cut-off point for the semi-quantitative results. Based on established criteria, six THAs and 15 KAs were classified as infected. The optimal cut-off point for the diagnosis of PJI was 97 WBC. The closest semi-quantitative reading for a positive result was 125 WBC, achieving a sensitivity of 81% and a specificity of 93%. The positive and negative predictive values of the LE test strip were 74% and 95% respectively. The LE reagent strip had a high specificity and negative predictive value. A negative result may exclude PJI and negate the need for further diagnostic tests. Cite this article: Bone Joint J 2015;97-B:1232–6

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