Aims. To identify variables independently associated with same-day discharge (SDD) of patients following revision total knee arthroplasty (rTKA) and to develop machine learning algorithms to predict suitable candidates for outpatient rTKA. Methods. Data were obtained from the American College of Surgeons National Quality Improvement Programme (ACS-NSQIP) database from the years 2018 to 2020. Patients with elective, unilateral rTKA procedures and a total hospital length of stay between zero and four days were included. Demographic, preoperative, and intraoperative variables were analyzed. A multivariable logistic regression (MLR) model and various machine learning techniques were compared using area under the curve (AUC), calibration, and decision curve analysis. Important and significant variables were identified from the models. Results. Of the 5,600 patients included in this study, 342 (6.1%) underwent SDD. The random forest (RF) model performed the best overall, with an internally validated AUC of 0.810. The ten crucial factors favoring SDD in the RF model include operating time, anaesthesia type, age, BMI, American Society of Anesthesiologists grade, race, history of diabetes, rTKA type, sex, and smoking status. Eight of these variables were also found to be significant in the MLR model. Conclusion. The RF model displayed excellent accuracy and identified clinically important variables for determining candidates for SDD following rTKA. Machine learning techniques such as RF will allow clinicians to accurately risk-stratify their patients preoperatively, in order to optimize resources and improve patient outcomes. Cite this article: Bone Jt Open 2023;4(6):399–407

Aims. Day-case arthroplasty is gaining popularity in Europe. We report outcomes from the first 12 months following implementation of a day-case pathway for unicompartmental knee arthroplasty (UKA) and total hip arthroplasty (THA) in an NHS hospital. Methods. A total of 47 total hip arthroplasty (THA) and 24 unicompartmental knee arthroplasty (UKA) patients were selected for the day-case arthroplasty pathway, based on preoperative fitness and agreement to participate. Data were likewise collected for a matched control group (n = 58) who followed the standard pathway three months prior to the implementation of the day-case pathway. We report same-day discharge (SDD) success, reasons for delayed discharge, and patient-reported outcomes. Overall length of stay (LOS) for all lower limb arthroplasty was recorded to determine the wider impact of implementing a day-case pathway. Results. Patients on the day-case pathway achieved SDD in 47% (22/47) of THAs and 67% (16/24) of UKAs. The most common reasons for failed SDD were nausea, hypotension, and pain, which were strongly associated with the use of fentanyl in the spinal anaesthetic. Complications and patient-reported outcomes were not significantly different between groups. Following the introduction of the day-case pathway, the mean LOS reduced significantly by 0.7, 0.6, and 0.5 days respectively in THA, UKA, and total knee arthroplasty cases (p < 0.001). Conclusion. Day-case pathways are feasible in an NHS set-up with only small changes required. We do not recommend fentanyl in the spinal anaesthetic for day-case patients. An important benefit seen in our unit is the so-called ‘day-case effect’, with a significant reduction in mean LOS seen across all lower limb arthroplasty. Cite this article: Bone Jt Open 2021;2(11):900–908

Aims. The volume of ambulatory total hip arthroplasty (THA) procedures is increasing due to the emphasis on value-based care. The purpose of the study is to identify the causes for failed same-day discharge (SDD) and perioperative factors leading to failed SDD. Methods. This retrospective cohort study followed pre-selected patients for SDD THA from 1 August 2018 to 31 December 2020. Inclusion criteria were patients undergoing unilateral THA with appropriate social support, age 18 to 75 years, and BMI < 37 kg/m. 2. Patients with opioid dependence, coronary artery disease, and valvular heart disease were excluded. Demographics, comorbidities, and perioperative data were collected from the electronic medical records. Possible risk factors for failed SDD were identified using multivariate logistic regression. Results. In all, 278 patients were identified with a mean age of 57.1 years (SD 8.1) and a mean BMI of 27.3 kg/m. 2. (SD 4.5). A total of 96 patients failed SDD, with the most common reasons being failure to clear physical therapy (26%), dizziness (22%), and postoperative nausea and vomiting (11%). Risk factors associated with failed SDD included smokers (odds ratio (OR) 6.24; p = 0.009), a maximum postoperative pain score > 8 (OR 4.76; p = 0.004), and procedures starting after 11 am (OR 2.28; p = 0.015). A higher postoperative tolerable pain goal (numerical rating scale 4 to 10) was found to be associated with successful SDD (OR 2.7; p = 0.001). Age, BMI, surgical approach, American Society of Anesthesiologists grade, and anaesthesia type were not associated with failed SDD. Conclusion. SDD is a safe and viable option for pre-selected patients interested in rapid recovery THA. The most common causes for failure to launch were failing to clear physical thereapy and patient symptomatology. Risk factors associated with failed SSD highlight the importance of preoperative counselling regarding smoking cessation and postoperative pain to set reasonable expectations. Future interventions should aim to improve patient postoperative mobilization, pain control, and decrease symptomatology. Cite this article: Bone Jt Open 2022;3(9):684–691

Aims. This study aimed to evaluate whether an enhanced recovery protocol (ERP) for arthroplasty established during the COVID-19 pandemic at a safety net hospital can be associated with a decrease in hospital length of stay (LOS) and an increase in same-day discharges (SDDs) without increasing acute adverse events. Methods. A retrospective review of 124 consecutive primary arthroplasty procedures performed after resuming elective procedures on 11 May 2020 were compared to the previous 124 consecutive patients treated prior to 17 March 2020, at a single urban safety net hospital. Revision arthroplasty and patients with < 90-day follow-up were excluded. The primary outcome measures were hospital LOS and the number of SDDs. Secondary outcome measures included 90-day complications, 90-day readmissions, and 30day emergency department (ED) visits. Results. The mean LOS was significantly reduced from 2.02 days (SD 0.80) in the pre-COVID cohort to 1.03 days (SD 0.65) in the post-COVID cohort (p < 0.001). No patients in the pre-COVID group were discharged on the day of surgery compared to 60 patients (48.4%) in the post-COVID group (p < 0.001). There were no significant differences in 90-day complications (13.7% (n = 17) vs 9.7% (n = 12); p = 0.429), 30-day ED visits (1.6% (n = 2) vs 3.2% (n = 4); p = 0.683), or 90-day readmissions (2.4% (n = 3) vs 1.6% (n = 2); p = 1.000) between the pre-COVID and post-COVID groups, respectively. Conclusion. Through use of an ERP, arthroplasty procedures were successfully resumed at a safety net hospital with a shorter LOS and increased SDDs without a difference in acute adverse events. The resulting increase in healthcare value therefore may be considered a ‘silver lining’ to the moratorium on elective arthroplasty during the COVID-19 pandemic. These improved efficiencies are expected to continue in post-pandemic era. Cite this article: Bone Jt Open 2021;2(10):871–878

Aims

The rate of day-case total knee arthroplasty (TKA) in the UK is currently approximately 0.5%. Reducing length of stay allows orthopaedic providers to improve efficiency, increase operative throughput, and tackle the rising demand for joint arthroplasty surgery and the COVID-19-related backlog. Here, we report safe delivery of day-case TKA in an NHS trust via inpatient wards with no additional resources.

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.

Aims

Total hip arthroplasty (THA) is a common procedure to address pain and enhance function in hip disorders such as osteoarthritis. Despite its success, postoperative patient recovery exhibits considerable heterogeneity. This study aimed to investigate whether patients follow distinct pain trajectories following THA and identify the patient characteristics linked to suboptimal trajectories.

Aims

COVID-19-related patient care delays have resulted in an unprecedented patient care backlog in the field of orthopaedics. The objective of this study is to examine orthopaedic provider preferences regarding the patient care backlog and financial recovery initiatives in response to the COVID-19 pandemic.

Aims

In 2020, the COVID-19 pandemic meant that proceeding with elective surgery was restricted to minimize exposure on wards. In order to maintain throughput of elective cases, our hospital (St Michaels Hospital, Toronto, Canada) was forced to convert as many cases as possible to same-day procedures rather than overnight admission. In this retrospective analysis, we review the cases performed as same-day arthroplasty surgeries compared to the same period in the previous 12 months.

Aims

Open reduction in developmental dysplasia of the hip (DDH) is regularly performed despite screening programmes, due to failure of treatment or late presentation. A protocol for open reduction of DDH has been refined through collaboration between surgical, anaesthetic, and nursing teams to allow same day discharge. The objective of this study was to determine the safety and feasibility of performing open reduction of DDH as a day case.

Total knee arthroplasty (TKA) is a major orthopaedic intervention. The length of a patient's stay has been progressively reduced with the introduction of enhanced recovery protocols: day-case surgery has become the ultimate challenge.

This narrative review shows the potential limitations of day-case TKA. These constraints may be social, linked to patient’s comorbidities, or due to surgery-related adverse events (e.g. pain, post-operative nausea and vomiting, etc.).

Using patient stratification, tailored surgical techniques and multimodal opioid-sparing analgesia, day-case TKA might be achievable in a limited group of patients. The younger, male patient without comorbidities and with an excellent social network around him might be a candidate.

Demographic changes, effective recovery programmes and less invasive surgical techniques such as unicondylar knee arthroplasty, may increase the size of the group of potential day-case patients.

The cost reduction achieved by day-case TKA needs to be balanced against any increase in morbidity and mortality and the cost of advanced follow-up at a distance with new technology. These factors need to be evaluated before adopting this ultimate ‘fast-track’ approach.

Cite this article: Bone Joint J 2015;97-B(10 Suppl A):40–4.

Objectives

Patient function after arthroplasty should ideally quickly improve. It is not known which peri-operative function assessments predict length of stay (LOS) and short-term functional recovery. The objective of this study was to identify peri-operative functions assessments predictive of hospital LOS and short-term function after hospital discharge in hip or knee arthroplasty patients.