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BackgroundA composite metric for the quality of glycemia from continuous glucose monitor (CGM) tracings could be useful for assisting with basic clinical interpretation of CGM data.MethodsWe assembled a data set of 14-day CGM tracings from 225 insulin-treated adults with diabetes. Using a balanced incomplete block design, 330 clinicians who were highly experienced with CGM analysis and interpretation ranked the CGM tracings from best to worst quality of glycemia. We used principal component analysis and multiple regressions to develop a model to predict the clinician ranking based on seven standard metrics in an Ambulatory Glucose Profile: very low-glucose and low-glucose hypoglycemia; very high-glucose and high-glucose hyperglycemia; time in range; mean glucose; and coefficient of variation.ResultsThe analysis showed that clinician rankings depend on two components, one related to hypoglycemia that gives more weight to very low-glucose than to low-glucose and the other related to hyperglycemia that likewise gives greater weight to very high-glucose than to high-glucose. These two components should be calculated and displayed separately, but they can also be combined into a single Glycemia Risk Index (GRI) that corresponds closely to the clinician rankings of the overall quality of glycemia (r = 0.95). The GRI can be displayed graphically on a GRI Grid with the hypoglycemia component on the horizontal axis and the hyperglycemia component on the vertical axis. Diagonal lines divide the graph into five zones (quintiles) corresponding to the best (0th to 20th percentile) to worst (81st to 100th percentile) overall quality of glycemia. The GRI Grid enables users to track sequential changes within an individual over time and compare groups of individuals.ConclusionThe GRI is a single-number summary of the quality of glycemia. Its hypoglycemia and hyperglycemia components provide actionable scores and a graphical display (the GRI Grid) that can be used by clinicians and researchers to determine the glycemic effects of prescribed and investigational treatments.

Diabetes Technology Society hosted its annual Diabetes Technology Meeting on November 4 to November 6, 2021. This meeting brought together speakers to discuss various developments within the field of diabetes technology. Meeting topics included blood glucose monitoring, continuous glucose monitoring, novel sensors, direct-to-consumer telehealth, metrics for glycemia, software for diabetes, regulation of diabetes technology, diabetes data science, artificial pancreas, novel insulins, insulin delivery, skin trauma, metabesity, precision diabetes, diversity in diabetes technology, use of diabetes technology in pregnancy, and green diabetes. A live demonstration on a mobile app to monitor diabetic foot wounds was presented.

The coronavirus disease 2019 (COVID-19) pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus has rapidly involved the entire world and exposed the pressing need for collaboration between public health and other stakeholders from the clinical, scientific, regulatory, pharmaceutical, and medical device and technology communities. To discuss how to best protect people with diabetes from serious outcomes from COVID-19, Diabetes Technology Society, in collaboration with Sansum Diabetes Research Institute, hosted the "International COVID-19 and Diabetes Virtual Summit" on August 26-27, 2020. This unique, unprecedented real-time conference brought together physicians, scientists, government officials, regulatory experts, industry representatives, and people with diabetes from six continents to review and analyze relationships between COVID-19 and diabetes. Over 800 attendees logged in. The summit consisted of five sessions: (I) Keynotes, (II) Preparedness, (III) Response, (IV) Recovery, and (V) Surveillance; eight parts: (A) Background, (B) Resilience, (C) Outpatient Care, (D) Inpatient Care, (E) Resources, (F) High-Risk Groups, (G) Regulation, and (H) The Future; and 24 sections: (1) Historic Pandemics and Impact on Society, (2) Pathophysiology/Risk Factors for COVID-19, (3) Social Determinants of COVID-19, (4) Preparing for the Future, (5) Medications and Vaccines, (6) Psychology of Patients and Caregivers, (7) Outpatient Treatment of Diabetes Mellitus and Non-Pharmacologic Intervention, (8) Technology and Telehealth for Diabetes Outpatients, (9) Technology for Inpatients, (10) Management of Diabetes Inpatients with COVID-19, (11) Ethics, (12) Accuracy of Diagnostic Tests, (13) Children, (14) Pregnancy, (15) Economics of Care for COVID-19, (16) Role of Industry, (17) Protection of Healthcare Workers, (18) People with Diabetes, (19) International Responses to COVID-19, (20) Government Policy, (21) Regulation of Tests and Treatments, (22) Digital Health Technology, (23) Big Data Statistics, and 24) Patient Surveillance and Privacy. The two keynote speeches were entitled (1) COVID-19 and Diabetes-Meeting the Challenge and (2) Knowledge Gaps and Research Opportunities for Diabetes and COVID-19. While there was an emphasis on diabetes and its interactions with COVID-19, the panelists also discussed the COVID-19 pandemic in general. The meeting generated many novel ideas for collaboration between experts in medicine, science, government, and industry to develop new technologies and disease treatment paradigms to fight this global pandemic.

Foreign language syndrome (FLS) is a rare phenomenon described as transient fixation on a second language following anesthesia administration. There have only been 12 previously reported cases of FLS and none involving female patients or oral and maxillofacial surgery (OMS). While volatile anesthetics were administered during at least 2 cases, at minimum 5 cases occurred without volatile anesthetics - instead manifesting with IV sedation medications commonly used with OMS outpatient procedures (ie, midazolam, fentanyl, and propofol). In our case, a healthy 21-year-old female underwent extraction of wisdom teeth under general anesthesia and developed FLS. Our purpose is not to elucidate the poorly understood pathophysiology of FLS but raise awareness of its potential following OMS procedures. FLS may be difficult to diagnose but appears to be self-limiting and typically resolves within approximately 24 hours. No stroke workup is warranted, and discharge home is likely appropriate with phone follow-up the following day. [ABSTRACT FROM AUTHOR]

Conventional power-integrated wireless neural recording devices suffer from bulky, rigid batteries in head-mounted configurations, hindering the precise interpretation of the subject's natural behaviors. These power sources also pose risks of material leakage and overheating. We present the direct printing of a power-integrated wireless neural recording system that seamlessly conforms to the cranium. A quasi-solid-state Zn-ion microbattery was 3D-printed as a built-in power source geometrically synchronized to the shape of a mouse skull. Soft deep-brain neural probes, interconnections, and auxiliary electronics were also printed using liquid metals on the cranium with high resolutions. In vivo studies using mice demonstrated the reliability and biocompatibility of this wireless neural recording system, enabling the monitoring of neural activities across extensive brain regions without notable heat generation. This all-printed neural interface system revolutionizes brain research, providing bio-conformable, customizable configurations for improved data quality and naturalistic experimentation. [ABSTRACT FROM AUTHOR]

We report a laboratory experiment that enables us to estimate parametric models of ambiguity aversion at the level of the individual subject. We use two main specifications, a “kinked” specification that nests Maxmin Expected Utility, Choquet Expected Utility, α-Maxmin Expected Utility, and Contraction Expected Utility and a “smooth” specification that nests the various theories referred to collectively as Recursive Expected Utility. Our subjects solved a series of portfolio-choice problems. The assets are Arrow securities corresponding to three states of nature, where the probability of one state is known and the remaining two are ambiguous. The sample exhibits considerable heterogeneity in preferences, as captured by parameter estimates. Nonetheless, there exists a strong tendency to equalize the demands for the securities that pay off in the ambiguous states, a feature more easily accommodated by the kinked specification than by the smooth specification. We also find that a large number of subjects are well described by the ambiguity-neutral Subjective Expected Utility model.

Given limited funding for school-based science education, non-school-based programs have been developed at colleges and universities to increase the number of students entering science- and health-related careers and address critical workforce needs. However, few evaluations of such programs have been conducted. We report the design and methods of a controlled trial to evaluate the Stanford Medical Youth Science Program's Summer Residential Program (SRP), a 25-year-old university-based biomedical pipeline program. This 5-year matched cohort study uses an annual survey to assess educational and career outcomes among four cohorts of students who participate in the SRP and a matched comparison group of applicants who were not chosen to participate in the SRP. Matching on sociodemographic and academic background allows control for potential confounding. This design enables the testing of whether the SRP has an independent effect on educational- and career-related outcomes above and beyond the effects of other factors such as gender, ethnicity, socioeconomic background, and pre-intervention academic preparation. The results will help determine which curriculum components contribute most to successful outcomes and which students benefit most. After 4 years of follow-up, the results demonstrate high response rates from SRP participants and the comparison group with completion rates near 90%, similar response rates by gender and ethnicity, and little attrition with each additional year of follow-up. This design and methods can potentially be replicated to evaluate and improve other biomedical pipeline programs, which are increasingly important for equipping more students for science- and health-related careers.

The effects of locally applied zinc chloride (ZnCl2) on early and late‐stage parameters of fracture healing were evaluated in a diabetic rat model. Type 1 Diabetes has been shown to negatively impact mechanical parameters of bone as well as biologic markers associated with bone healing. Zinc treatments have been shown to reverse those outcomes in tests of nondiabetic and diabetic animals. This study is the first to assess the efficacy of a noncarrier mediated ZnCl2 on bony healing in diabetic animals. This is a promising basic science approach which may lead to benefits for diabetic patients in the future. Treatment and healing were assessed through quantification of callus zinc, radiographic scoring, microcomputed tomography (µCT), histomorphometry, and mechanical testing. Local ZnCl2 treatment increased callus zinc levels at 1 and 3 days after fracture (p ≤ 0.025). Femur fractures treated with ZnCl2 showed increased mechanical properties after 4 and 6 weeks of healing. Histomorphometry of the ZnCl2‐treated fractures found increased callus cartilage area at Day 7 (p = 0.033) and increased callus bone area at Day 10 (p = 0.038). In contrast, callus cartilage area was decreased (p < 0.01) after 14 days in the ZnCl2‐treated rats. µCT analysis showed increased bone volume in the fracture callus of ZnCl2‐treated rats at 6 weeks (p = 0.0012) with an associated increase in the proportion of µCT voxel axial projections (Z‐rays) spanning the fracture site. The results suggest that local ZnCl2 administration improves callus chondrogenesis leading to greater callus bone formation and improved fracture healing in diabetic rats. [ABSTRACT FROM AUTHOR]