Artificial Intelligence and Arthroplasty at a Single Institution: Real-World Applications of Machine Learning to Big Data,Value-Based Care,Mobile Health,and Remote Patient Monitoring

BackgroundDriven by the recent ubiquity of big data and computing power, we established the Machine Learning Arthroplasty Laboratory (MLAL) to examine and apply artificial intelligence (AI) to musculoskeletal medicine.MethodsIn this review, we discuss the 2 core objectives of the MLAL as they relate to the practice and progress of orthopedic surgery: (1) patient-specific, value-based care and (2) human movement.ResultsWe developed and validated several machine learning-based models for primary lower extremity arthroplasty that preoperatively predict patient-specific, risk-adjusted value metrics, including cost, length of stay, and discharge disposition, to provide improved expectation management, preoperative planning, and potential financial arbitration. Additionally, we leveraged passive, ubiquitous mobile technologies to build a small data registry of human movement surrounding TKA that permits remote patient monitoring to evaluate therapy compliance, outcomes, opioid intake, mobility, and joint range of motion.ConclusionThe rapid rate with which we in arthroplasty are acquiring and storing continuous data, whether passively or actively, demands an advanced processing approach: AI. By carefully studying AI techniques with the MLAL, we have applied this evolving technique as a first step that may directly improve patient outcomes and practice of orthopedics.     

Cardioprotection Acquired Through Exercise: The Role of Ischemic Preconditioning

A great bulk of evidence supports the concept that regular exercise training can reduce the incidence of coronary events and increase survival chances after myocardial infarction. These exercise-induced beneficial effects on the myocardium are reached by means of the reduction of several risk factors relating to cardiovascular disease, such as high cholesterol, hypertension, obesity etc. Furthermore, it has been demonstrated that exercise can reproduce the “ischemic preconditioning” (IP), which refers to the capacity of short periods of ischemia to render the myocardium more resistant to subsequent ischemic insult and to limit infarct size during prolonged ischemia. However, IP is a complex phenomenon which, along with infarct size reduction, can also provide protection against arrhythmia and myocardial stunning due to ischemia-reperfusion. Several clues demonstrate that preconditioning may be directly induced by exercise, thus inducing a protective phenotype at the heart level without the necessity of causing ischemia. Exercise appears to act as a physiological stress that induces beneficial myocardial adaptive responses at cellular level. The purpose of the present paper is to review the latest data on the role played by exercise in triggering myocardial preconditioning.     

Development of an automated individual tree detection model using point cloud LiDAR data for accurate tree counts in a Pinus radiata plantation

We develop and evaluate a new individual tree detection (ITD) algorithm to automatically locate and estimate the number of individual trees within a Pinus radiata plantation from relatively sparse airborne LiDAR point cloud data. The area of interest comprised stands covering a range of age classes and stocking levels. Our approach is based on local maxima (LM) filtering that tackles the issue of selecting the optimal search radius from the LiDAR point cloud for every potential LM using metrics derived from local neighbourhood data points; thus, it adapts to the local conditions, irrespective of canopy variability. This was achieved through two steps: (i) logistic regression model development using simulated stands composed of individual trees derived from real LiDAR point cloud data and (ii) application testing of the model using real plantation LiDAR point cloud data and geolocated, tree-level reference crowns that were manually identified in the LiDAR imagery. Our ITD algorithm performed well compared with previous studies, producing RMSE of 5.7% and a bias of only ?2.4%. Finally, we suggest that the ITD algorithm can be used for accurately estimating stocking and tree mapping, which in turn could be used to derive the plot-level metrics for an area-based approach for enhancing estimates of stand-level inventory attributes based on plot imputation.     

The Transformation of Diabetes Care Through the Use of Person-Centered Data

The health care industry is undergoing a major transformation. Despite spending more on health care than any other country, the United States has not seen a commensurate improvement in the quality of care. Chronic disease management puts the greatest burden on the health care system with estimates suggesting that 3 of 4 health care dollars are spent on managing chronic disease. Moreover, the number of older patients with chronic conditions, like diabetes, is rising as expected, which only serves to worsen the physician shortage problem we are currently experiencing, and further increase health care costs. Unless new models of health care are established for these patients, they simply will not be served. Consistent with the message above, there are generally 3 universal health care needs, (1) improved outcomes, (2) expanded access, and (3) optimized cost and efficiency. It is likely the future state will involve value-based health care, with payment based on outcomes, not services rendered, and incentives tied more directly to the value delivered. Medical device providers will be held more accountable for positive outcomes, and to ensure success, they will need to create better solutions with their therapies. Instead of the touch point with patients being solely at the time of a procedure or sale of the device, it is likely companies will need to drive toward a more comprehensive partnership with patients, providers, and payers, extending the scope of services and interactions to provide a continuum of care. In general, companies will need to start to think of their most important customers as people living with a condition, as opposed to patients needing immediate medical devices. In this article, I discuss the challenges of health care today and present some of the opportunities to revamp health care delivery in diabetes by leveraging the pervasive use of mobile technologies and digital data.     

All is Not Lost: Utilizing Continuous Remote ILR Monitoring to Diagnose Syncope

A 63‐year‐old man with frequent unexplained syncope was implanted with a second generation remotely monitored implantable loop recorder for continuous electrocardiogram (ECG) monitoring. He had a subsequent syncopal episode and despite accidental destruction of his patient activator, vital ECG data from the event were transmitted wirelessly, enabling a cardiac arrhythmia to be excluded. This case highlights the benefit of remote monitoring in syncope assessment, as well as a transmission system that ensures prompt analysis of the ECG data and therefore rapid optimal patient management. (PACE 2010; 33:763–765)     

The effect of remote peer support on stigma in patients after breast cancer surgery during the COVID-19 pandemic: A protocol for systematic review and meta-analysis

Background:Patients after breast cancer surgery have a high sense of stigma due to the formation of surgical scars, loss of breast shape or other reasons, leading to anxiety, depression, and other adverse mental health problems, thus reducing their quality of life. Remote peer support intervention based on telephone, internet or email is low-cost and easy to spread, and protects patients’ privacy, solves the barriers to access that many patients face when attending face-to-face programs. Therefore, remote peer support may be an effective way to reduce stigma and improve mental health in patients after breast cancer surgery during the coronavirus disease 2019 (COVID-19) pandemic.Methods:Eight databases (PubMed, Embase, Cochrane Library, CNKI, PsycNET, MEDLINE, Psychology & Behavioral Sciences Collection and Web of Science) will be used to select eligible studies that were published from inception to May, 2021. The eligible studies will be screened, extracted and then the methodological quality will be evaluated independently by 2 reviewers. Review manager software version 5.3 software and Stata version 14.0 software will be used for meta-analysis.Results:The results of this study will show the effect of remote peer support on stigma, depression and anxiety in patients after breast cancer surgery during the COVID-19 pandemic and will be submitted to a peer-reviewed journal for publication.Conclusion:The results of this study will provide evidence for the effectiveness of remote peer support in patients after breast cancer surgery during the COVID-19 pandemic.PROSPERO registration number:CRD42021255971.     

Successes in sexual health communications development,programmatic implementation and evaluation in the Torres Strait region 2006 to 2012

Objective: To evaluate the Indigenous sexual health promotion program in the Torres Strait 2006–2012 that culminated in an education‐entertainment radio drama, Kasa Por Yarn (KPY). Methods: A mixed methods approach applied to unpublished program documents and program‐derived peer‐reviewed publications was utilised. Results: Early initiatives established a strong partnership with Torres Strait Islander stakeholders. Significant community engagement throughout ensured a positive process. Telephone survey data (n=100, TSI, 15–24 years) found: 95% had heard of KPY and 80% listened to 2 or more episodes (reach); 86% recalled storylines/characters (recall); and 54% talked about KPY to family/friends (resonance). There was improvement in sexual health knowledge scores (p<0.00) in the 15–19‐year‐old Torres Strait Islander population between 2007 and 2012. The 2012 15–24‐year‐old population exposed to KPY had higher sexual health knowledge scores compared with those unexposed (p=0.02). Conclusions: This is an uncommon comprehensive evaluation of population‐based sexual health communications strategies delivered over years in a remote Australian setting. The findings are encouraging but demonstrate that positive shifts take time and are incremental. Implications: In addition to clinical strategies, strategic and sustained investment in sexual health promotion expertise that leads community partnership and program development is required to reduce youth risk and prevent HIV/AIDS in remote populations.