Aims. The use of technology to assess balance and alignment during total knee surgery can provide an overload of numerical data to the surgeon. Meanwhile, this quantification holds the potential to clarify and guide the surgeon through the surgical decision process when selecting the appropriate bone recut or soft tissue adjustment when balancing a total knee. Therefore, this paper evaluates the potential of deploying supervised machine learning (ML) models to select a surgical correction based on patient-specific intra-operative assessments. Methods. Based on a clinical series of 479 primary total knees and 1,305 associated surgical decisions, various ML models were developed. These models identified the indicated surgical decision based on available, intra-operative alignment, and tibiofemoral load data. Results. With an associated area under the receiver-operator curve ranging between 0.75 and 0.98, the optimized ML models resulted in good to excellent predictions. The best performing model used a random forest approach while considering both alignment and intra-articular load readings. Conclusion. The presented model has the potential to make experience available to surgeons adopting new technology, bringing expert opinion in their operating theatre, but also provides insight in the surgical decision process. More specifically, these promising outcomes indicated the relevance of considering the overall limb alignment in the coronal and sagittal plane to identify the appropriate surgical decision

Aims. As the peak of the COVID-19 pandemic passes, the challenge shifts to safe resumption of routine medical services, including elective orthopaedic surgery. Protocols including pre-operative self-isolation, COVID-19 testing, and surgery at a non-COVID-19 site have been developed to minimize risk of transmission. Despite this, it is likely that many patients will want to delay surgery for fear of contracting COVID-19. The aim of this study is to identify the number of patients who still want to proceed with planned elective orthopaedic surgery in this current environment. Methods. This is a prospective, single surgeon study of 102 patients who were on the waiting list for an elective hip or knee procedure during the COVID-19 pandemic. Baseline characteristics including age, ASA grade, COVID-19 risk, procedure type, surgical priority, and admission type were recorded. The primary outcome was patient consent to continue with planned surgical care after resumption of elective orthopaedic services. Subgroup analysis was also performed to determine if any specific patient factors influenced the decision to proceed with surgery. Results. Overall, 58 patients (56.8%) wanted to continue with planned surgical care at the earliest possibility. Patients classified as ASA I and ASA II were more likely to agree to surgery (60.5% and 60.0%, respectively) compared to ASA III and ASA IV patients (44.4% and 0.0%, respectively) (p = 0.01). In addition, patients undergoing soft tissue knee surgery were more likely to consent to surgery (90.0%) compared to patients undergoing primary hip arthroplasty (68.6%), primary knee arthroplasty (48.7%), revision hip or knee arthroplasty (0.0%), or hip and knee injections (43.8%) (p = 0.03). Conclusion. Restarting elective orthopaedic services during the COVID-19 pandemic remains a significant challenge. Given the uncertain environment, it is unsurprising that only 56% of patients were prepared to continue with their planned surgical care upon resumption of elective services. Cite this article: Bone Joint Open 2020;1-6:267–271

Aims

The COVID-19 pandemic drastically affected elective orthopaedic services globally as routine orthopaedic activity was largely halted to combat this global threat. Our institution (University College London Hospital, UK) previously showed that during the first peak, a large proportion of patients were hesitant to be listed for their elective lower limb procedure. The aim of this study is to assess if there is a patient perception change towards having elective surgery now that we have passed the peak of the second wave of the pandemic.

Aims

The exact risk to patients undergoing surgery who develop COVID-19 is not yet fully known. This study aims to provide the current data to allow adequate consent regarding the risks of post-surgery COVID-19 infection and subsequent COVID-19-related mortality.