Background. The advent of value-based conscientiousness and rapid-recovery discharge pathways presents surgeons, hospitals, and payers with the challenge of providing the same total hip arthroplasty episode of care in the safest and most economic fashion for the same fee, despite patient differences. Various predictive analytic techniques have been applied to medical risk models, such as sepsis risk scores, but none have been applied or validated to the elective primary total hip arthroplasty (THA) setting for key payment-based metrics. The objective of this study was to develop and validate a predictive machine learning model using preoperative patient demographics for length of stay (LOS) after primary THA as the first step in identifying a patient-specific payment model (PSPM). Methods. Using 229,945 patients undergoing primary THA for osteoarthritis from an administrative database between 2009– 16, we created a naïve Bayesian model to forecast LOS after primary THA using a 3:2 split in which 60% of the available patient data “built” the algorithm and the remaining 40% of patients were used for “testing.” This process was iterated five times for algorithm refinement, and model performance was determined using the area under the receiver operating characteristic curve (AUC), percent accuracy, and positive predictive value. LOS was either grouped as 1–5 days or greater than 5 days. Results. The machine learning model algorithm required age, race, gender, and two comorbidity scores (“risk of illness” and “risk of morbidity”) to demonstrate excellent validity, reliability, and responsiveness with an AUC of 0.87 after five iterations. Hospital stays of greater than 5 days for THA were most associated with increased risk of illness and risk of comorbidity scores during admission compared to 1–5 days of stay. Conclusions. Our machine learning model derived from administrative big data demonstrated excellent validity, reliability, and responsiveness after primary THA while accurately predicting LOS and identifying two comorbidity scores as key value-based metrics. Predictive data has the potential to engender a risk-based PSPM prior to primary THA and other elective orthopaedic procedures

The extent and depth of routine health care data are growing at an ever-increasing rate, forming huge repositories of information. These repositories can answer a vast array of questions. However, an understanding of the purpose of the dataset used and the quality of the data collected are paramount to determine the reliability of the result obtained.

This Editorial describes the importance of adherence to sound methodological principles in the reporting and publication of research using ‘big’ data, with a suggested reporting framework for future Bone & Joint Journal submissions.

Cite this article: Bone Joint J 2014;96-B:1575–7.

The objectives of this study are to evaluate the impact of the CoVID-19 pandemic on the development of relevant emerging digital healthcare trends and to explore which digital healthcare trend does the health industry need most to support HCPs. A web survey using 39 questions facilitating Five-Point Likert scales was performed from 1.8.2020 – 31.10.2020. Of 260 participants invited, 90 participants answered the questionnaire. The participants were located in the Hospital/HCP sector in 11.9%, in other healthcare sectors in 22.2%, in the pharmaceutical sector in 11.1%, in the medical device and equipment industry in 43.3%. The Five-Point Likert scales were in all cases fashioned as from 1 (strongly disagree) to 5 (strongly agree). As the top 3 most impacted digital health care trends strongly impacted by CoVID-19, respondents named:. - remote management of patients by telemedicine, mean answer 4.44. - shared data governance under patient control, mean answer 3.80. - new virtual interaction between HCP´s and medical industry, mean answer 3.76. Respondents were asked which level of readiness of the healthcare system currently possess to cope with the current trend impacted by CoVID-19. - Digital and efficient healthcare logistics, mean answer 1.54. - Integrated health care, mean answer 1.73. - Use of big data and artificial intelligence, mean answer 2.03. Asked if collaborative research in the form of digital data platforms for research data sharing and increasing collaboration with multi-centric consortia would have a positive impact on the healthcare sector, the agreement was high with a value of mean 4.10 on the scale. We can conclude that the impact of COVID-19 appears to be a high agreement of necessary advances in digitalization in the health care sector and in the collaboration of HCPs with the health care industry. Health care professional are unsure, in how far the national health care sector is capable of transformation in healthcare logistics and integrated health care

The tendency towards using inertial sensors for remote monitoring of the patients at home is increasing. One of the most important characteristics of the sensors is sampling rate. Higher sampling rate results in higher resolution of the sampled signal and lower amount of noise. However, higher sampling frequency comes with a cost. The main aim of our study was to determine the validity of measurements performed by low sampling frequency (12.5 Hz) accelerometers (SENS) in patients with knee osteoarthritis compared to standard sensor-based motion capture system (Xsens). We also determined the test-retest reliability of SENS accelerometers. Participants were patients with unilateral knee osteoarthritis. Gait analysis was performed simultaneously by using Xsens and SENS sensors during two repetitions of over-ground walking at a self-selected speed. Gait data from Xsens were used as an input for AnyBody musculoskeletal modeling software to measure the accelerations at the exact location of two defined virtual sensors in the model (VirtualSENS). After preprocessing, the signals from SENS and VirtualSENS were compared in different coordinate axes in time and frequency domains. ICC for SENS data from first and second trials were calculated to assess the repeatability of the measurements. We included 32 patients (18 females) with median age 70.1[48.1 – 85.4]. Mean height and weight of the patients were 173.2 ± 9.6 cm and 84.2 ± 14.7 kg respectively. The correlation between accelerations in time domain measured by SENS and VirtualSENS in different axes was r = 0.94 in y-axis (anteroposterior), r = 0.91 in x-axis (vertical), r = 0.83 in z-axis (mediolateral), and r = 0.89 for the magnitude vector. In frequency domain, the value and the power of fundamental frequencies (F. 0. ) of SENS and VirtualSENS signals demonstrated strong correlation (r = 0.98 and r = 0.99 respectively). The result of test-retest evaluation showed excellent repeatability for acceleration measurement by SENS sensors. ICC was between 0.89 to 0.94 for different coordinate axes. Low sampling frequency accelerometers can provide valid and reliable measurements especially for home monitoring of the patients, in which handling big data and sensors cost and battery lifetime are among important issues

Aims

Achilles tendon re-rupture (ATRR) poses a significant risk of postoperative complication, even after a successful initial surgical repair. This study aimed to identify risk factors associated with Achilles tendon re-rupture following operative fixation.

The August 2023 Hip & Pelvis Roundup³⁶⁰ looks at: Using machine learning to predict venous thromboembolism and major bleeding events following total joint arthroplasty; Antibiotic length in revision total hip arthroplasty; Preoperative colonization and worse outcomes; Short stem cemented total hip arthroplasty; What are the outcomes of one- versus two-stage revisions in the UK?; To cement or not to cement? The best approach in hemiarthroplasty; Similar re-revisions in cemented and cementless femoral revisions for periprosthetic femoral fractures in total hip arthroplasty; Are hip precautions still needed?

The OpenAI chatbot ChatGPT is an artificial intelligence (AI) application that uses state-of-the-art language processing AI. It can perform a vast number of tasks, from writing poetry and explaining complex quantum mechanics, to translating language and writing research articles with a human-like understanding and legitimacy. Since its initial release to the public in November 2022, ChatGPT has garnered considerable attention due to its ability to mimic the patterns of human language, and it has attracted billion-dollar investments from Microsoft and PricewaterhouseCoopers. The scope of ChatGPT and other large language models appears infinite, but there are several important limitations. This editorial provides an introduction to the basic functionality of ChatGPT and other large language models, their current applications and limitations, and the associated implications for clinical practice and research.

Cite this article: Bone Joint J 2023;105-B(6):587–589.

The February 2024 Knee Roundup³⁶⁰ looks at: Do patients with hypoallergenic total knee arthroplasty implants for metal allergy do worse? An analysis of healthcare utilizations and patient-reported outcome measures; Defining a successful total knee arthroplasty; Incidence, microbiological studies, and factors associated with periprosthetic joint infection after total knee arthroplasty; A modified Delphi consensus statement on patellar instability; Cause for concern? Significant cement coverage in retrieved metaphyseal cones after revision total knee arthroplasty; Prevalence of post-traumatic osteoarthritis after anterior cruciate ligament injury remains high despite advances in surgical techniques; Cost-effectiveness of arthroscopic partial meniscectomy versus physical therapy for traumatic meniscal tears in patients aged under 45 years.

The February 2023 Oncology Roundup³⁶⁰ looks at: Is the number of national database research studies in musculoskeletal sarcoma increasing, and are these studies reliable?; Re-excision after unplanned excision of soft-tissue sarcoma is associated with high morbidity; Adjuvant radiation in atypical lipomatous tumours; The oncological outcomes of isolated limb perfusion and neoadjuvant radiotherapy in soft-tissue sarcoma patients - a nationwide multicentre study; Can low-grade chondrosarcoma be treated with intralesional curettage and cryotherapy?; Efficacy and safety of carbon ion radiotherapy for bone sarcomas: a systematic review and meta-analysis; Doxorubicin-polymeric meshes prevent local recurrence after sarcoma resection while avoiding cardiotoxicity; How important are skip lesions in Ewing’s sarcoma?; Improving outcomes for amputees: the health-related quality of life and cost utility analysis of osseointegration prosthetics in transfemoral amputees.

The February 2023 Spine Roundup³⁶⁰ looks at: S2AI screws: At what cost?; Just how good is spinal deformity surgery?; Is 80 years of age too late in the day for spine surgery?; Factors affecting the accuracy of pedicle screw placement in robot-assisted surgery; Factors causing delay in discharge in patients eligible for ambulatory lumbar fusion surgery; Anterior cervical discectomy or fusion and selective laminoplasty for cervical spondylotic myelopathy; Surgery for cervical radiculopathy: what is the complication burden?; Hypercholesterolemia and neck pain; Return to work after surgery for cervical radiculopathy: a nationwide registry-based observational study.

The April 2023 Shoulder & Elbow Roundup³⁶⁰ looks at: Arthroscopic Bankart repair in athletes: in it for the long run?; Functional outcomes and the Wrightington classification of elbow fracture-dislocations; Hemiarthroplasty or ORIF intra-articular distal humerus fractures in older patients; Return to sport after total shoulder arthroplasty and hemiarthroplasty; Readmissions after shoulder arthroplasty; Arthroscopic Bankart repair in the longer term; Bankart repair with(out) remplissage or the Latarjet procedure? A systematic review and meta-analysis; Regaining motion among patients with shoulder pathology: are all exercises equal?

The December 2023 Wrist & Hand Roundup³⁶⁰ looks at: Volar locking plate for distal radius fractures with patient-reported outcomes in older adults; Total joint replacement or trapeziectomy?; Replantation better than revision amputation in traumatic amputation?; What factors are associated with revision cubital tunnel release within three years?; Use of nerve conduction studies in carpal tunnel syndrome; Surgical site infection following surgery for hand trauma: a systematic review and meta-analysis; Association between radiological and clinical outcomes following distal radial fractures; Reducing the carbon footprint in carpal tunnel surgery inside the operating room with a lean and green model: a comparative study.

The December 2023 Shoulder & Elbow Roundup³⁶⁰ looks at: Clavicle fractures: is the evidence changing practice?; Humeral shaft fractures, and another meta-analysis…let’s wait for the trials now!; Hemiarthroplasty or total elbow arthroplasty for distal humeral fractures…what does the registry say?; What to do with a first-time shoulder dislocation?; Deprivation indices and minimal clinically important difference for patient-reported outcomes after arthroscopic rotator cuff repair; Prospective randomized clinical trial of arthroscopic repair versus debridement for partial subscapularis tears; Long-term follow-up following closed reduction and early movement for simple dislocation of the elbow; Sternoclavicular joint reconstruction for traumatic acute and chronic anterior and posterior instability.

The February 2024 Trauma Roundup³⁶⁰ looks at: Posterior malleolus fractures: what about medium-sized fragments?; Acute or delayed total hip arthroplasty after acetabular fracture fixation?; Intrawound antibiotics reduce the risk of deep infections in fracture fixation; Does the VANCO trial represent real world patients?; Can a restrictive transfusion protocol be effective beyond initial resuscitation?; What risk factors result in avascular necrosis of the talus?; Pre-existing anxiety and mood disorders have a role to play in complex regional pain syndrome; Three- and four-part proximal humeral fractures at ten years.

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.