Necessary Products for the Prevention and Treatment of Pressure Injuries: Lessons Learned That Translate Beyond the COVID-19 Pandemic.

OBJECTIVE: To identify the challenges encountered in obtaining the required support surfaces and products to meet pressure injury (PrI) prevention and treatment needs during COVID-19. METHODS: The authors used SurveyMonkey to gather data on healthcare perceptions and the challenges experienced regarding specific product categories deemed necessary for PrI prevention and treatment in US acute care settings during the pandemic. They created three anonymous surveys for the target populations of supply chain personnel and healthcare workers. The surveys addressed healthcare workers' perceptions, product requests, and the ability to fulfill product requests and meet facility protocols without substitution in the categories of support surfaces and skin and wound care supplies. RESULTS: Respondents answered one of the three surveys for a total sample of 174 respondents. Despite specific instructions, nurses responded to the surveys designed for supply chain personnel. Their responses and comments were interesting and capture their perspectives and insights. Three themes emerged from the responses and general comments: (1) expectations differed between supply chain staff and nurses for what was required for PrI prevention and treatment; (2) inappropriate substitution with or without proper staff education occurred; and (3) preparedness. CONCLUSIONS: It is important to identify experiences and challenges in the acquisition and availability of appropriate equipment and products for PrI prevention and treatment. To foster ideal PrI prevention and treatment outcomes, a proactive approach is required to face daily issues or the next crisis.

Driver Vigilance Decrement is More Severe During Automated Driving than Manual Driving.

OBJECTIVE: The present study compared the performance, workload, and stress associated with driver vigilance in two types of vehicle: a traditional, manually operated vehicle, and a partially automated vehicle. BACKGROUND: Drivers of partially automated vehicles must monitor for hazards that constitute automation failures and the need for human intervention, but recent research indicates that a driver's ability to do so declines as a function of time. That research lacked a comparison measure of driving without vehicle automation, so it is unknown to what degree these effects are specific symptoms of monitoring the roadway during an automated drive. Drivers in manual control of their vehicle must similarly monitor for hazards and may suffer similar vigilance decrements. METHOD: Participants completed a simulated 40-minute drive while monitoring for hazards. Half of participants completed the drive with an automated driving system that maintained speed and lane position; the remaining half manually controlled the vehicle's speed and lane position. RESULTS: Driver sensitivity to hazards decreased and tendency to make false alarms increased over time in the automated control condition, but not in the manual control condition. Drivers in both conditions detected fewer hazards as the drive progressed. Ratings of workload and task-induced stress were elevated similarly in both conditions. CONCLUSION: Partially automated driving appears to uniquely impair driver vigilance by reducing the ability to discriminate between benign and dangerous events in the driving environment as the drive progresses. APPLICATION: Applied interventions should target improvements in driver sensitivity to hazardous situations that signal potential automation failures.

Maximal dose-response of vitamin-K2 (menaquinone-4) on undercarboxylated osteocalcin in women with osteoporosis.

Low concentrations of serum vitamin K accompany high concentrations of undercarboxylated osteocalcin (ucOC) and osteoporotic fractures. Although vitamin K2 (MK-4) is approved as a therapeutic agent for the treatment of osteoporosis in some countries, the dose-response is unknown. The objective of this study was to assess the improvement in carboxylation of osteocalcin (OC) in response to escalating doses of MK-4 supplementation. A nine-week, open-labeled, prospective cohort study was conducted in 29 postmenopausal women who suffered hip or vertebral compression fractures. Participants took low-dose MK-4 (0.5 mg) for 3 weeks (until the second visit), then medium-dose MK-4 (5 mg) for 3 weeks (until the third visit), then high-dose MK-4 (45 mg) for 3 weeks. The mean ± SD age of the participants was 69 ± 9 years. MK-4 dose (p < 0.0001), but neither age nor other relevant medications (e.g. bisphosphonates) correlated with improvement in %ucOC. As compared to baseline concentrations (geometric mean ± SD) of 16.8 ± 2.4, 0.5 mg supplementation halved %ucOC to 8.7 ± 2.2 (p < 0.0001) and the 5-mg dose halved %ucOC again (to 3.9 ± 2.2; p = 0.0002 compared to 0.5-mg dose). However, compared to 5 mg/day, there was no additional benefit of 45 mg/day (%ucOC 4.6; p = NS vs. 5-mg dose). MK-4 supplementation resulted in borderline increases in γ-carboxylated osteocalcin (glaOC; p = 0.07). There were no major side effects of MK-4 supplementation. In postmenopausal women with osteoporotic fractures, supplementation with either 5 or 45 mg/day of MK-4 reduces ucOC to concentrations typical of healthy, pre-menopausal women.

Cannabidiol or CBD Oil: Help, Hope, and Hype for Psychiatric and Neurologic Conditions.

OBJECTIVE: This article presents proven, promising, and potential therapeutic uses for cannabidiol (CBD) in the treatment of psychiatric and neurologic conditions and diseases. It presents popular, but scientifically unproven health and therapeutic claims of CBD supporting the beneficial homeostatic effects of the intrinsic or endogenous cannabinoid system. It includes a review of cannabinoid pharmacology; it compares properties and the legal status of CBD and THC (delta 9-tetrahydrocannabinol) as well as the hemp and marijuana varieties of Cannabis, and it reviews the historic 2018 U.S. Food and Drug Administration approval of Epidiolex, an oral solution of cannabidiol for two rare treatment-resistant childhood epilepsies, as the first Cannabis-derived drug. METHOD: We reviewed literature on cannabidiol, CBD, the endocannabinoid neuropharmacology system, and hemp and marijuana varieties of Cannabis sativa. RESULTS: The proven and promising medical uses and deficiencies of unproven health claims for CBD, legal implications for Cannabis-derived drugs, and comparisons of CBD and THC and hemp and marijuana are summarized objectively with pertinent references. CONCLUSION: CBD and CBD and THC combinations have potential to provide safe, effective therapy for several psychiatric and neurologic conditions and diseases. However, such achievement will require a uniform standard of CBD purity and strength, and corroboration from adequately large and rigorously controlled clinical research studies.

Driver Vigilance in Automated Vehicles: Effects of Demands on Hazard Detection Performance.

OBJECTIVE: The current study investigated driver vigilance in partially automated vehicles to determine whether increased task demands reduce a driver's ability to monitor for automation failures and whether the vigilance decrement associated with hazard detections is due to driver overload. BACKGROUND: Drivers of partially automated vehicles are expected to monitor for signs of automation failure. Previous research has shown that a driver's ability to perform this duty declines over time. One possible explanation for this vigilance decrement is that the extreme demands of vigilance causes overload and leads to depletion of limited attentional resources required for vigilance. METHOD: Participants completed a 40-min drive in a simulated partially automated vehicle and were tasked with monitoring for hazards that represented potential automation failures. Two factors were manipulated to test the impact of monitoring demands on performance: Spatial uncertainty and event rate. RESULTS: As predicted, hazard detection performance was poorer when monitoring demands were increased, and performance declined as a function of time on task. Subjective reports also indicated high workload and task-induced stress. CONCLUSION: Drivers of partially automated vehicles are impaired by the vigilance decrement and elevated task demands, meaning that safe operation becomes less likely when the demands associated with monitoring automation increase and as a drive extends in duration. This study also supports the notion that vigilance performance in partially automated vehicles is likely due to driver overload. APPLICATION: Developers of automation technologies should consider countermeasures that attenuate a driver's cognitive load when tasked with monitoring automation.

Driver Vigilance in Automated Vehicles: Hazard Detection Failures Are a Matter of Time.

OBJECTIVE: The primary aim of the current study was to determine whether monitoring the roadway for hazards during automated driving results in a vigilance decrement. BACKGROUND: Although automated vehicles are relatively novel, the nature of human-automation interaction within them has the classic hallmarks of a vigilance task. Drivers must maintain attention for prolonged periods of time to detect and respond to rare and unpredictable events, for example, roadway hazards that automation may be ill equipped to detect. Given the similarity with traditional vigilance tasks, we predicted that drivers of a simulated automated vehicle would demonstrate a vigilance decrement in hazard detection performance. METHOD: Participants "drove" a simulated automated vehicle for 40 minutes. During that time, their task was to monitor the roadway for roadway hazards. RESULTS: As predicted, hazard detection rate declined precipitously, and reaction times slowed as the drive progressed. Further, subjective ratings of workload and task-related stress indicated that sustained monitoring is demanding and distressing and it is a challenge to maintain task engagement. CONCLUSION: Monitoring the roadway for potential hazards during automated driving results in workload, stress, and performance decrements similar to those observed in traditional vigilance tasks. APPLICATION: To the degree that vigilance is required of automated vehicle drivers, performance errors and associated safety risks are likely to occur as a function of time on task. Vigilance should be a focal safety concern in the development of vehicle automation.

A web-based intervention to support self-management of patients with type 2 diabetes mellitus: effect on self-efficacy, self-care and diabetes distress.

BACKGROUND: Management of diabetes mellitus is complex and involves controlling multiple risk factors that may lead to complications. Given that patients provide most of their own diabetes care, patient self-management training is an important strategy for improving quality of care. Web-based interventions have the potential to bridge gaps in diabetes self-care and self-management. The objective of this study was to determine the effect of a web-based patient self-management intervention on psychological (self-efficacy, quality of life, self-care) and clinical (blood pressure, cholesterol, glycemic control, weight) outcomes. METHODS: For this cohort study we used repeated-measures modelling and qualitative individual interviews. We invited patients with type 2 diabetes to use a self-management website and asked them to complete questionnaires assessing self-efficacy (primary outcome) every three weeks for nine months before and nine months after they received access to the website. We collected clinical outcomes at three-month intervals over the same period. We conducted in-depth interviews at study conclusion to explore acceptability, strengths and weaknesses, and mediators of use of the website. We analyzed the data using a qualitative descriptive approach and inductive thematic analysis. RESULTS: Eighty-one participants (mean age 57.2 years, standard deviation 12) were included in the analysis. The self-efficacy score did not improve significantly more than expected after nine months (absolute change 0.12; 95% confidence interval -0.028, 0.263; p = 0.11), nor did clinical outcomes. Website usage was limited (average 0.7 logins/month). Analysis of the interviews (n = 21) revealed four themes: 1) mediators of website use; 2) patterns of website use, including role of the blog in driving site traffic; 3) feedback on website; and 4) potential mechanisms for website effect. CONCLUSIONS: A self-management website for patients with type 2 diabetes did not improve self-efficacy. Website use was limited. Although its perceived reliability, availability of a blog and emailed reminders drew people to the website, participants' struggles with type 2 diabetes, competing priorities in their lives, and website accessibility were barriers to its use. Future interventions should aim to integrate the intervention seamlessly into the daily routine of end users such that it is not seen as yet another chore.

User-centered design of a web-based self-management site for individuals with type 2 diabetes - providing a sense of control and community.

BACKGROUND: To design and test a web-based self-management tool for patients with type 2 diabetes for its usability and feasibility. METHODS: An evidence-based, theory-driven website was created for patients with type 2 diabetes. Twenty-three patients with type 2 diabetes aged ≥ 25 years were recruited from 2 diabetes care centers in Toronto, Canada. We employed focus group methodology to assess acceptability, sustainability, strengths and weaknesses of the self-management website. Based on these results, revisions were made to the website. Three cycles of individual usability testing sessions using cognitive task analysis were conducted with patients with type 2 diabetes. Revisions to the website were made based on results from this testing. RESULTS: We identified five themes concerning participants' experiences of health care and related unmet needs: 1) Desire for information and for greater access to timely and personalized care to gain a sense of control of their disease; 2) Desire for community (sharing experiences with others) to fulfill practical and emotional needs; 3) Potential roles of an online self-management website in self-empowerment, behavior change, self-management and health care delivery; 4) Importance of a patient-centered perspective in presenting content (e.g. common assumptions, medical nomenclature, language, messaging, sociocultural context); 5) Barriers and facilitators to use of a self-management website (including perceived relevance of content, incorporation into usual routine, availability for goal-directed use, usability issues). CONCLUSIONS: Participants outlined a series of unmet health care needs, and stated that they wanted timely access to tailored knowledge about their condition, mechanisms to control and track their disease, and opportunities to share experiences with other patients. These findings have implications for patients with type 2 diabetes of diverse ages, socioeconomic backgrounds, and disease severity, as well as to the design of other computer-based resources for chronic disease management.

Ebbinghaus illusions with disc figures: effects of contextual size, separation, and lightness.

The Ebbinghaus illusion was produced using figures with four small or large contextual discs located either near or far from the central disc. For similar figures, the discs were either all black or all white; for dissimilar figures, black and white contextual and central discs were used in opposition. 48 observers, in equal numbers, were assigned to one of the four crossings of size and separation of the contextual discs and, using the converging method of limits, illusion magnitude scores for each Ebbinghaus configuration were obtained. The central disc appeared larger when bounded by small contextual discs and smaller when the contextual discs were more distant. Contrary to size contrast theory, uniformly colored discs did not generate greater illusions; instead, white central discs appeared larger than black ones regardless of contextual color. Collectively, the results indicated that contour interactions play a prominent role in producing the Ebbinghaus illusion.

Value-Based Health Care in Perioperative Medicine: Process Maps and Costing to Determine Best Practices.

Perioperative care in the United States is largely based on current fee-for-service models. Fee-for-service models are not based on the true cost of services provided, charges do not equal costs, and reimbursement varies based on insurer. Value-based health care is defined as patient-centered outcomes over cost of providing these services. Process mapping and time-driven activity-based costing can be used to define actual cost of services provided. Outcomes after discharge can be measured, so that the overall value of care provided can be assessed and improved based on the outcomes and costs identified.

A Comparison of Arterial Input Function Interpolation Methods for Patlak Plot Analysis of 68Ga-PSMA-11 PET Prostate Cancer Studies.

Positron emission tomography (PET) imaging enables quantitative assessment of tissue physiology. Dynamic pharmacokinetic analysis of PET images requires accurate estimation of the radiotracer plasma input function to derive meaningful parameter estimates, and small discrepancies in parameter estimation can mimic subtle physiologic tissue variation. This study evaluates the impact of input function interpolation method on the accuracy of Patlak kinetic parameter estimation through simulations modeling the pharmacokinetic properties of [68Ga]-PSMA-11. This study evaluated both trained and untrained methods. Although the mean kinetic parameter accuracy was similar across all interpolation models, the trained node weighting interpolation model estimated accurate kinetic parameters with reduced overall variability relative to standard linear interpolation. Trained node weighting interpolation reduced kinetic parameter estimation variance by a magnitude approximating the underlying physiologic differences between normal and diseased prostatic tissue. Overall, this analysis suggests that trained node weighting improves the reliability of Patlak kinetic parameter estimation for [68Ga]-PSMA-11 PET.

Real-world data of radiofrequency catheter ablation in paroxysmal atrial fibrillation: Short- and long-term clinical outcomes from the prospective multicenter REAL-AF Registry.

BACKGROUND: The safety and long-term efficacy of radiofrequency (RF) catheter ablation (CA) of paroxysmal atrial fibrillation (PAF) has been well established. Contemporary techniques to optimize ablation delivery, reduce fluoroscopy use, and improve clinical outcomes have been developed. OBJECTIVE: The purpose of this study was to assess the contemporary real-world practice approach and short and long-term outcomes of RF CA for PAF through a prospective multicenter registry. METHODS: Using the REAL-AF (Real-world Experience of Catheter Ablation for the Treatment of Symptomatic Paroxysmal and Persistent Atrial Fibrillation; ClincalTrials.gov Identifier: NCT04088071) Registry, patients undergoing RF CA to treat PAF across 42 high-volume institutions and 79 experienced operators were evaluated. The procedures were performed using zero or reduced fluoroscopy, contact force sensing catheters, wide area circumferential ablation, and ablation index as a guide with a target of 380-420 for posterior and 500-550 for anterior lesions. The primary efficacy outcome was freedom from all-atrial arrhythmia recurrence at 12 months. RESULTS: A total of 2470 patients undergoing CA from January 2018 to December 2022 were included. Mean age was 65.2 ±11.14 years, and 44% were female. Most procedures were performed without fluoroscopy (71.5%), with average procedural and total RF times of 95.4 ± 41.7 minutes and 22.1±11.8 minutes, respectively. At 1-year follow-up, freedom from all-atrial arrhythmias was 81.6% with 89.7% of these patients off antiarrhythmic drugs. No significant difference was identified comparing pulmonary vein isolation vs pulmonary vein isolation plus ablation approaches. The complication rate was 1.9%. CONCLUSION: Refinement of RF CA to treat PAF using contemporary tools, standardized protocols, and electrophysiology laboratory workflows resulted in excellent short- and long-term clinical outcomes.

Development of a framework for recovery in older people with mental disorder.

OBJECTIVE: To evaluate whether a conceptual framework of recovery developed for working age adults holds value for users of older people's mental health services, including those with dementia. METHOD: Thirty-eight qualitative interviews were undertaken with service users and carers from an older people's mental health service in South London and were analysed using grounded theory methods. RESULTS: Components of recovery, which appear to be meaningful to older people with mental disorder include the following: (i) the impact of illness, (ii) the significance of personal responsibility, and (iii) specific coping strategies. Unlike their younger peers, older people did not aspire to a new and revised sense of identity, nor did they seek peer support from others with lived experience of mental illness. Three components of recovery were identified as being distinct to older people: the significance of an established and enduring sense of identity; coping strategies, which provide continuity and reinforce identity; and the associated impact of physical illness. Finally, two additional components of recovery were identified for people with dementia: (i) the changing experience over time and (ii) support from others. CONCLUSION: Mental health policy is increasingly framed in terms of 'recovery'. This paper provides empirical evidence of how it applies to users of older people's mental health services. Practice implications include the need to focus on the maintenance of identity, and embed the values of empowerment, agency and self-management within service delivery.

The EXO70 inhibitor Endosidin2 alters plasma membrane protein composition in Arabidopsis roots.

To sustain normal growth and allow rapid responses to environmental cues, plants alter the plasma membrane protein composition under different conditions presumably by regulation of delivery, stability, and internalization. Exocytosis is a conserved cellular process that delivers proteins and lipids to the plasma membrane or extracellular space in eukaryotes. The octameric exocyst complex contributes to exocytosis by tethering secretory vesicles to the correct site for membrane fusion; however, whether the exocyst complex acts universally for all secretory vesicle cargo or just for specialized subsets used during polarized growth and trafficking is currently unknown. In addition to its role in exocytosis, the exocyst complex is also known to participate in membrane recycling and autophagy. Using a previously identified small molecule inhibitor of the plant exocyst complex subunit EXO70A1, Endosidin2 (ES2), combined with a plasma membrane enrichment method and quantitative proteomic analysis, we examined the composition of plasma membrane proteins in the root of Arabidopsis seedlings, after inhibition of the ES2-targetted exocyst complex, and verified our findings by live imaging of GFP-tagged plasma membrane proteins in root epidermal cells. The abundance of 145 plasma membrane proteins was significantly reduced following short-term ES2 treatments and these likely represent candidate cargo proteins of exocyst-mediated trafficking. Gene Ontology analysis showed that these proteins play diverse functions in cell growth, cell wall biosynthesis, hormone signaling, stress response, membrane transport, and nutrient uptake. Additionally, we quantified the effect of ES2 on the spatial distribution of EXO70A1 with live-cell imaging. Our results indicate that the plant exocyst complex mediates constitutive dynamic transport of subsets of plasma membrane proteins during normal root growth.

Co-occurrences of fall-related factors in adults aged 60 to 85 years in the United States National Health and Nutrition Examination Survey.

A broad set of factors are associated with falling (e.g., age, sex, physical activity, vision, health), but their co-occurrence is understudied. Our objectives were to quantify the number and pattern of co-occurring fall-related factors. Data were obtained from the U.S. National Health and Nutrition Examination Survey (N = 1,957, 60-85 years). Twenty fall-related factors were included (based on previous research), covering a wide range including cognitive, motor, sensory, health, and physical activity measures. The number and pattern of co-occurring fall-related factors were quantified with logistic regression and cluster analyses, respectively. Most participants (59%) had ≥4 fall-risk factors, and each additional risk factor increased the odds of reporting difficulty with falling by 1.28. The identified clusters included: (1) healthy, (2) cognitive and sensory impaired, and (3) health impaired. The mean number of co-occurring fall-related factors was 3.7, 3.8, and 7.2, for clusters 1, 2, and 3, respectively (p<0.001). These observations indicate that co-occurrence of multiple fall-risk factors was common in this national sample of U.S. older adults and the factors tended to aggregate into distinct clusters. The findings support the protective effect of physical activity on fall-risk, the association between gait speed and falls, and the detrimental effect of health-related factors on difficulty with falls (e.g., arthritis, prescription medications). Cluster analyses revealed a complex interplay between sex and BMI that may alter the role of BMI in the etiology of falls. Cluster analyses also revealed a large detrimental effect of health-related factors in cluster 3; it is important to extend current fall interventions (typically focused on balance, flexibility, strength, cognitive, fear factors) to include health-related interventions that target factors such as BMI and arthritis.

Feature Selection Techniques for a Machine Learning Model to Detect Autonomic Dysreflexia.

Feature selection plays a crucial role in the development of machine learning algorithms. Understanding the impact of the features on a model, and their physiological relevance can improve the performance. This is particularly helpful in the healthcare domain wherein disease states need to be identified with relatively small quantities of data. Autonomic Dysreflexia (AD) is one such example, wherein mismanagement of this neurological condition could lead to severe consequences for individuals with spinal cord injuries. We explore different methods of feature selection needed to improve the performance of a machine learning model in the detection of the onset of AD. We present different techniques used as well as the ideal metrics using a dataset of thirty-six features extracted from electrocardiograms, skin nerve activity, blood pressure and temperature. The best performing algorithm was a 5-layer neural network with five relevant features, which resulted in 93.4% accuracy in the detection of AD. The techniques in this paper can be applied to a myriad of healthcare datasets allowing forays into deeper exploration and improved machine learning model development. Through critical feature selection, it is possible to design better machine learning algorithms for detection of niche disease states using smaller datasets.

WikiBuild: a new online collaboration process for multistakeholder tool development and consensus building.

BACKGROUND: Production of media such as patient education tools requires methods that can integrate multiple stakeholder perspectives. Existing consensus techniques are poorly suited to design of visual media, can be expensive and logistically demanding, and are subject to caveats arising from group dynamics such as participant hierarchies. OBJECTIVE: Our objective was to develop a method that enables multistakeholder tool building while averting these difficulties. METHODS: We developed a wiki-inspired method and tested this through the collaborative design of an asthma action plan (AAP). In the development stage, we developed the Web-based tool by (1) establishing AAP content and format options, (2) building a Web-based application capable of representing each content and format permutation, (3) testing this tool among stakeholders, and (4) revising this tool based on stakeholder feedback. In the wiki stage, groups of participants used the revised tool in three separate 1-week "wiki" periods during which each group collaboratively authored an AAP by making multiple online selections. RESULTS: In the development stage, we recruited 16 participants (9/16 male) (4 pulmonologists, 4 primary care physicians, 3 certified asthma educators, and 5 patients) for system testing. The mean System Usability Scale (SUS) score for the tool used in testing was 72.2 (SD 10.2). In the wiki stage, we recruited 41 participants (15/41 male) (9 pulmonologists, 6 primary care physicians, 5 certified asthma educators, and 21 patients) from diverse locations. The mean SUS score for the revised tool was 75.9 (SD 19.6). Users made 872, 466, and 599 successful changes to the AAP in weeks 1, 2, and 3, respectively. The site was used actively for a mean of 32.0 hours per week, of which 3.1 hours per week (9.7%) constituted synchronous multiuser use (2-4 users at the same time). Participants averaged 23 (SD 33) minutes of login time and made 7.7 (SD 15) changes to the AAP per day. Among participants, 28/35 (80%) were satisfied with the final AAP, and only 3/34 (9%) perceived interstakeholder group hierarchies. CONCLUSION: Use of a wiki-inspired method allowed for effective collaborative design of content and format aspects of an AAP while minimizing logistical requirements, maximizing geographical representation, and mitigating hierarchical group dynamics. Our method faced unique software and hardware challenges, and raises certain questions regarding its effect on group functioning. Potential uses of our method are broad, and further studies are required.

Machine Learning Driven Contouring of High-Frequency Four-Dimensional Cardiac Ultrasound Data.

Automatic boundary detection of 4D ultrasound (4DUS) cardiac data is a promising yet challenging application at the intersection of machine learning and medicine. Using recently developed murine 4DUS cardiac imaging data, we demonstrate here a set of three machine learning models that predict left ventricular wall kinematics along both the endo- and epi-cardial boundaries. Each model is fundamentally built on three key features: (1) the projection of raw US data to a lower dimensional subspace, (2) a smoothing spline basis across time, and (3) a strategic parameterization of the left ventricular boundaries. Model 1 is constructed such that boundary predictions are based on individual short-axis images, regardless of their relative position in the ventricle. Model 2 simultaneously incorporates parallel short-axis image data into their predictions. Model 3 builds on the multi-slice approach of model 2, but assists predictions with a single ground-truth position at end-diastole. To assess the performance of each model, Monte Carlo cross validation was used to assess the performance of each model on unseen data. For predicting the radial distance of the endocardium, models 1, 2, and 3 yielded average R2 values of 0.41, 0.49, and 0.71, respectively. Monte Carlo simulations of the endocardial wall showed significantly closer predictions when using model 2 versus model 1 at a rate of 48.67%, and using model 3 versus model 2 at a rate of 83.50%. These finding suggest that a machine learning approach where multi-slice data are simultaneously used as input and predictions are aided by a single user input yields the most robust performance. Subsequently, we explore the how metrics of cardiac kinematics compare between ground-truth contours and predicted boundaries. We observed negligible deviations from ground-truth when using predicted boundaries alone, except in the case of early diastolic strain rate, providing confidence for the use of such machine learning models for rapid and reliable assessments of murine cardiac function. To our knowledge, this is the first application of machine learning to murine left ventricular 4DUS data. Future work will be needed to strengthen both model performance and applicability to different cardiac disease models.

Rare case: Ureteropelvic junction complication presenting with bilateral labial abscesses and urosepsis requiring nephrectomy.

Ureteropelvic junction obstruction (UPJO) is the most common cause of urinary tract obstruction in pediatric patients. Debates in management include ureteral stent versus nephrostomy tube placement prior to surgical correction if intervention is warranted. We present a female patient with left UPJO, diagnosed at 15-years-old, treated with ureteral stent placement. Stent removal two years later resulted in extensive complications, including retroperitoneal infection, labial abscesses, and nephrectomy. Management of UPJO in the pediatric population prior to surgical correction is not well-standardized. The severity of complications following the removal of the two-year-old stent suggests caution for placing ureteral stents without proper follow-up.

Development of a prototype clinical decision support tool for osteoporosis disease management: a qualitative study of focus groups.

BACKGROUND: Osteoporosis affects over 200 million people worldwide, and represents a significant cost burden. Although guidelines are available for best practice in osteoporosis, evidence indicates that patients are not receiving appropriate diagnostic testing or treatment according to guidelines. The use of clinical decision support systems (CDSSs) may be one solution because they can facilitate knowledge translation by providing high-quality evidence at the point of care. Findings from a systematic review of osteoporosis interventions and consultation with clinical and human factors engineering experts were used to develop a conceptual model of an osteoporosis tool. We conducted a qualitative study of focus groups to better understand physicians' perceptions of CDSSs and to transform the conceptual osteoporosis tool into a functional prototype that can support clinical decision making in osteoporosis disease management at the point of care. METHODS: The conceptual design of the osteoporosis tool was tested in 4 progressive focus groups with family physicians and general internists. An iterative strategy was used to qualitatively explore the experiences of physicians with CDSSs; and to find out what features, functions, and evidence should be included in a working prototype. Focus groups were conducted using a semi-structured interview guide using an iterative process where results of the first focus group informed changes to the questions for subsequent focus groups and to the conceptual tool design. Transcripts were transcribed verbatim and analyzed using grounded theory methodology. RESULTS: Of the 3 broad categories of themes that were identified, major barriers related to the accuracy and feasibility of extracting bone mineral density test results and medications from the risk assessment questionnaire; using an electronic input device such as a Tablet PC in the waiting room; and the importance of including well-balanced information in the patient education component of the osteoporosis tool. Suggestions for modifying the tool included the addition of a percentile graph showing patients' 10-year risk for osteoporosis or fractures, and ensuring that the tool takes no more than 5 minutes to complete. CONCLUSIONS: Focus group data revealed the facilitators and barriers to using the osteoporosis tool at the point of care so that it can be optimized to aid physicians in their clinical decision making.