Aims. Patient-reported outcome measures have become an important part of routine care. The aim of this study was to determine if Patient-Reported Outcomes Measurement Information System (PROMIS) measures can be used to create patient subgroups for individuals seeking orthopaedic care. Methods. This was a cross-sectional study of patients from Duke University Department of Orthopaedic Surgery clinics (14 ambulatory and four hospital-based). There were two separate cohorts recruited by convenience sampling (i.e. patients were included in the analysis only if they completed PROMIS measures during a new patient visit). Cohort #1 (n = 12,141; December 2017 to December 2018,) included PROMIS short forms for eight domains (Physical Function, Pain Interference, Pain Intensity, Depression, Anxiety, Sleep Quality, Participation in Social Roles, and Fatigue) and Cohort #2 (n = 4,638; January 2019 to August 2019) included PROMIS
Aims. The increase in prescription opioid misuse and dependence is now a public health crisis in the UK. It is recognized as a whole-person problem that involves both the medical and the psychosocial needs of patients. Analyzing aspects of pathophysiology, emotional health, and social wellbeing associated with persistent opioid use after injury may inform safe and effective alleviation of pain while minimizing risk of misuse or dependence. Our objectives were to investigate patient factors associated with opioid use two to four weeks and six to nine months after an upper limb fracture. Methods. A total of 734 patients recovering from an isolated upper limb fracture were recruited in this study. Opioid prescription was documented retrospectively for the period preceding the injury, and prospectively at the two- to four-week post-injury visit and six- to nine-month post-injury visit. Bivariate and multivariate analysis sought factors associated with opioid prescription from demographics, injury-specific data, Patient Reported Outcome Measurement Instrumentation System (PROMIS), Depression
The principles of evidence-based medicine (EBM) are the foundation of modern medical practice. Surgeons are familiar with the commonly used statistical techniques to test hypotheses, summarize findings, and provide answers within a specified range of probability. Based on this knowledge, they are able to critically evaluate research before deciding whether or not to adopt the findings into practice. Recently, there has been an increased use of artificial intelligence (AI) to analyze information and derive findings in orthopaedic research. These techniques use a set of statistical tools that are increasingly complex and may be unfamiliar to the orthopaedic surgeon. It is unclear if this shift towards less familiar techniques is widely accepted in the orthopaedic community. This study aimed to provide an exploration of understanding and acceptance of AI use in research among orthopaedic surgeons. Semi-structured in-depth interviews were carried out on a sample of 12 orthopaedic surgeons. Inductive thematic analysis was used to identify key themes.Aims
Methods
Disorders of bone integrity carry a high global disease burden, frequently requiring intervention, but there is a paucity of methods capable of noninvasive real-time assessment. Here we show that miniaturized handheld near-infrared spectroscopy (NIRS) scans, operated via a smartphone, can assess structural human bone properties in under three seconds. A hand-held NIR spectrometer was used to scan bone samples from 20 patients and predict: bone volume fraction (BV/TV); and trabecular (Tb) and cortical (Ct) thickness (Th), porosity (Po), and spacing (Sp).Aims
Methods
The aim of this study was to develop and evaluate machine-learning-based computerized adaptive tests (CATs) for the Oxford Hip Score (OHS), Oxford Knee Score (OKS), Oxford Shoulder Score (OSS), and the Oxford Elbow Score (OES) and its subscales. We developed CAT algorithms for the OHS, OKS, OSS, overall OES, and each of the OES subscales, using responses to the full-length questionnaires and a machine-learning technique called regression tree learning. The algorithms were evaluated through a series of simulation studies, in which they aimed to predict respondents’ full-length questionnaire scores from only a selection of their item responses. In each case, the total number of items used by the CAT algorithm was recorded and CAT scores were compared to full-length questionnaire scores by mean, SD, score distribution plots, Pearson’s correlation coefficient, intraclass correlation (ICC), and the Bland-Altman method. Differences between CAT scores and full-length questionnaire scores were contextualized through comparison to the instruments’ minimal clinically important difference (MCID).Aims
Methods
This study assesses patient barriers to successful telemedicine care in orthopaedic practices in a large academic practice in the COVID-19 era. In all, 381 patients scheduled for telemedicine visits with three orthopaedic surgeons in a large academic practice from 1 April 2020 to 12 June 2020 were asked to participate in a telephone survey using a standardized Institutional Review Board-approved script. An unsuccessful telemedicine visit was defined as patient-reported difficulty of use or reported dissatisfaction with teleconferencing. Patient barriers were defined as explicitly reported barriers of unsatisfactory visit using a process-based satisfaction metric. Statistical analyses were conducted using analysis of variances (ANOVAs), ranked ANOVAs, post-hoc pairwise testing, and chi-squared independent analysis with 95% confidence interval.Aims
Methods
There is little published on the outcomes after restarting elective orthopaedic procedures following cessation of surgery due to the COVID-19 pandemic. During the pandemic, the reported perioperative mortality in patients who acquired SARS-CoV-2 infection while undergoing elective orthopaedic surgery was 18% to 20%. The aim of this study is to report the surgical outcomes, complications, and risk of developing COVID-19 in 2,316 consecutive patients who underwent elective orthopaedic surgery in the latter part of 2020 and comparing it to the same, pre-pandemic, period in 2019. A retrospective service evaluation of patients who underwent elective surgical procedures between 16 June 2020 and 12 December 2020 was undertaken. The number and type of cases, demographic details, American society of Anesthesiologists (ASA) grade, BMI, 30-day readmission rates, mortality, and complications at one- and six-week intervals were obtained and compared with patients who underwent surgery during the same six-month period in 2019.Aims
Methods
The coronavirus 2019 (COVID-19) global pandemic has had a significant impact on trauma and orthopaedic (T&O) departments worldwide. To manage the peak of the epidemic, orthopaedic staff were redeployed to frontline medical care; these roles included managing minor injury units, forming a “proning” team, and assisting in the intensive care unit (ICU). In addition, outpatient clinics were restructured to facilitate virtual consultations, elective procedures were cancelled, and inpatient hospital admissions minimized to reduce nosocomial COVID-19 infections. Urgent operations for fractures, infection and tumours went ahead but required strict planning to ensure patient safety. Orthopaedic training has also been significantly impacted during this period. This article discusses the impact of COVID-19 on T&O in the UK and highlights key lessons learned that may help to proactively prepare for the next global pandemic. Cite this article:
Europe has found itself at the epicentre of the COVID-19 pandemic. Naturally, this has placed added strain onto healthcare systems internationally. It was feared that the impact of the COVID-19 pandemic could overrun the Irish healthcare system. As such, the Irish government opted to introduce a national lockdown on the 27 March 2020 in an attempt to stem the flow of admissions to hospitals. Similar lockdowns in the UK and New Zealand have resulted in reduced emergency department presentations and trauma admissions. The aim of this study is to assess the effect of the national lockdown on trauma presentations to a model-3 hospital in Dublin, Ireland. A retrospective study was conducted. All emergency department presentations between 27 March 2019 to 27 April 2020 and 27 March 2020 to 27 April 2020 were cross-referenced against the National Integrated Medical Imaging System-Picture Archiving Communication System (NIMIS-PACS) radiology system to identify those with radiologically proven skeletal trauma. These patients were grouped according to sex, age, discharge outcome, mechanism of injury, and injury location.Aims
Methods
Virtual encounters have experienced an exponential rise amid the current COVID-19 crisis. This abrupt change, seen in response to unprecedented medical and environmental challenges, has been forced upon the orthopaedic community. However, such changes to adopting virtual care and technology were already in the evolution forecast, albeit in an unpredictable timetable impeded by regulatory and financial barriers. This adoption is not meant to replace, but rather augment established, traditional models of care while ensuring patient/provider safety, especially during the pandemic. While our department, like those of other institutions, has performed virtual care for several years, it represented a small fraction of daily care. The pandemic required an accelerated and comprehensive approach to the new reality. Contemporary literature has already shown equivalent safety and patient satisfaction, as well as superior efficiency and reduced expenses with musculoskeletal virtual care (MSKVC) versus traditional models. Nevertheless, current literature detailing operational models of MSKVC is scarce. The current review describes our pre-pandemic MSKVC model and the shift to a MSKVC pandemic workflow that enumerates the conceptual workflow organization (patient triage, from timely care provision based on symptom acuity/severity to a continuum that includes future follow-up). Furthermore, specific setup requirements (both resource/personnel requirements such as hardware, software, and network connectivity requirements, and patient/provider characteristics respectively), and professional expectations are outlined. MSKVC has already become a pivotal element of musculoskeletal care, due to COVID-19, and these changes are confidently here to stay. Readiness to adapt and evolve will be required of individual musculoskeletal clinical teams as well as organizations, as established paradigms evolve. Cite this article:
