A scoping review of artificial intelligence in medical education: BEME Guide No. 84.

BACKGROUND: Artificial Intelligence (AI) is rapidly transforming healthcare, and there is a critical need for a nuanced understanding of how AI is reshaping teaching, learning, and educational practice in medical education. This review aimed to map the literature regarding AI applications in medical education, core areas of findings, potential candidates for formal systematic review and gaps for future research. METHODS: This rapid scoping review, conducted over 16 weeks, employed Arksey and O'Malley's framework and adhered to STORIES and BEME guidelines. A systematic and comprehensive search across PubMed/MEDLINE, EMBASE, and MedEdPublish was conducted without date or language restrictions. Publications included in the review spanned undergraduate, graduate, and continuing medical education, encompassing both original studies and perspective pieces. Data were charted by multiple author pairs and synthesized into various thematic maps and charts, ensuring a broad and detailed representation of the current landscape. RESULTS: The review synthesized 278 publications, with a majority (68%) from North American and European regions. The studies covered diverse AI applications in medical education, such as AI for admissions, teaching, assessment, and clinical reasoning. The review highlighted AI's varied roles, from augmenting traditional educational methods to introducing innovative practices, and underscores the urgent need for ethical guidelines in AI's application in medical education. CONCLUSION: The current literature has been charted. The findings underscore the need for ongoing research to explore uncharted areas and address potential risks associated with AI use in medical education. This work serves as a foundational resource for educators, policymakers, and researchers in navigating AI's evolving role in medical education. A framework to support future high utility reporting is proposed, the FACETS framework.

The Need for Data Standards and Implementation Policies to Integrate CGM Data into the Electronic Health Record.

The current lack of continuous glucose monitor (CGM) data integration into the electronic health record (EHR) is holding back the use of this wearable technology for patient-generated health data (PGHD). This failure to integrate with other healthcare data inside the EHR disrupts workflows, removes the data from critical patient context, and overall makes the CGM data less useful than it might otherwise be. Many healthcare organizations (HCOs) are either struggling with or delaying designing and implementing CGM data integrations. In this article, the current status of CGM integration is reviewed, goals for integration are proposed, and a consensus plan to engage key stakeholders to facilitate integration is presented.

Retained Diabetes Devices-A Literature Review.

BACKGROUND: Diabetes management and treatment requires the use of many devices that frequently must puncture the skin, creating a risk of unintentional retention in the body as a retained diabetes device. In this article, we reviewed case studies about retained diabetes devices and presented analyses of the success rate of current imaging techniques in identifying retained devices and the success rate of device removal. METHODS: PubMed and Google Scholar were searched for articles about retained diabetes devices. Relevant articles that included sufficient details about discovery and removal of the device were included. The success rate of identification and the success rate of removal of retained devices were both calculated as percentages. RESULTS: Sixteen case studies of retained diabetes devices were identified. These devices included parts of continuous glucose monitors and infusion sets, a lancet, and various types of needles for insulin injection. Each case is presented with details about the year of publication, the retained diabetes device, the company that produced the device, the age and gender of the patient, the type of diabetes that the patient had, the location of the device, the reason for initial discovery of the retained device, the process of locating the device, the success rate for removal of the device, and the removal procedure of the device. Analysis revealed a 100% success rate for the use of imaging technology including X-rays and computed tomography to identify a retained diabetes device. The patients with retained diabetes devices had a 62.5% success rate for eventual removal of the device. CONCLUSIONS: With the increasing use of injected, inserted, and implanted diabetes wearables for digital health, it is likely that some of the devices will detach, break apart, or otherwise become retained in the body. It is important to be aware of available technologies to identify retained diabetes devices so that it will be possible in most cases to surgically remove these devices if they detach or become retained.

Use of Continuous Glucose Monitors by People Without Diabetes: An Idea Whose Time Has Come?

BACKGROUND: Continuous glucose monitor (CGM) systems were originally intended only for people with diabetes. Recently, there has been interest in monitoring glucose concentrations in a variety of other situations. As data accumulate to support the use of CGM systems in additional states unrelated to diabetes, the use of CGM systems is likely to increase accordingly. METHODS: PubMed and Google Scholar were searched for articles about the use of CGM in individuals without diabetes. Relevant articles that included sufficient details were queried to identify what cohorts of individuals were adopting CGM use and to define trends of use. RESULTS: Four clinical user cases were identified: (1) metabolic diseases related to diabetes with a primary dysregulation of the insulin-glucose axis, (2) metabolic diseases without a primary pathophysiologic derangement of the insulin-glucose axis, (3) health and wellness, and (4) elite athletics. Seven trends in the use of CGM systems in people without diabetes were idenfitied which pertained to both FDA-cleared medical grade products as well as anticipated future products, which may be regulated differently based on intended populations and indications for use. CONCLUSIONS: Wearing a CGM has been used not only for diabetes, but with a goal of improving glucose patterns to avoid diabetes, improving mental or physical performance, and promoting motivate healthy behavioral changes. We expect that clinicians will become increasingly aware of (1) glycemic patterns from CGM tracings that predict an increased risk of diabetes, (2) specific metabolic glucotypes from CGM tracings that predict an increased risk of diabetes, and (3) new genetic and genomic biomarkers in the future.

Six Digital Health Technologies That Will Transform Diabetes.

The digital health revolution is transforming the landscape of medicine through innovations in sensor data, software, and wireless communication tools. As one of the most prevalent chronic diseases in the United States, diabetes is particularly impactful as a model disease for which to apply innovation. As with any other newly developed technologies, there are three key questions to consider: 1) How can the technology benefit people with diabetes?, 2) What barriers must be overcome to further advance the technology?, and 3) How will the technology be applied in the future?. In this article, we highlight six areas of innovation that have the potential to reduce the burden of diabetes for individuals living with the condition and their families as well as provide measurable benefits for all stakeholders involved in diabetes care. The six technologies which have the potential to transform diabetes care are (i) telehealth, (ii) incorporation of diabetes digital data into the electronic health record, (iii) qualitative hypoglycemia alarms, (iv) artificial intelligence, (v) cybersecurity of diabetes devices, and (vi) diabetes registries. To be successful, a new digital health technology must be accessible and affordable. Furthermore, the people and communities that would most likely benefit from the technology must be willing to use the innovation in their management of diabetes.

Continuous Subcutaneous Infusion Versus Multiple Daily Injections of Insulin for Pregestational Diabetes in Pregnancy: A Systematic Review and Meta-Analysis.

BACKGROUND: The use of continuous subcutaneous insulin infusion (CSII) therapy in pregnancies affected by pregestational diabetes mellitus (DM) has generated mixed outcome data worthy of further investigation. This systematic review and meta-analysis aims to evaluate clinical outcomes associated with CSII versus multiple daily injections (MDIs) in pregnant persons with pregestational DM. METHODS: A predefined, systematic, librarian-assisted search of MEDLINE (PubMed), Embase, Cochrane Library, Scopus, ClinicalTrials.gov, and World Health Organization International Clinical Trial Registry Platform (published from 2010 to 2022) yielded 3003 studies describing pregnancy outcomes associated with CSII and/or MDI for pregestational DM. The primary exposure was mode of insulin administration, with cesarean delivery and neonatal hypoglycemia as the primary maternal and neonatal outcomes, respectively. Secondary outcomes included hypertensive disorders of pregnancy, first and third-trimester glycemic control, large-for-gestational age (LGA) neonate, preterm birth, neonatal intensive care unit admission, need for respiratory support, hyperbilirubinemia, 5-minute Apgar <7, shoulder dystocia, and perinatal mortality. We calculated pooled odds ratios (OR) with 95% confidence intervals (CI) using random-effects models. RESULTS: Among 39 eligible studies, 39% of the 5518 pregnancies included were exposed to CSII. Odds of cesarean delivery were higher with CSII (20 studies: 63% vs 56%, odds ratio [OR] 1.3 [95% confidence interval (CI) 1.2-1.5]), but we did not identify a difference in the odds of neonatal hypoglycemia (23 studies: 31% vs 34%, OR 1.1 [95% CI 0.9-1.5]). Among secondary outcomes, only the odds of LGA (20 studies: 47% vs 38%, OR 1.4 [95% CI 1.2-1.6]) were higher in individuals using CSII versus MDI. CONCLUSIONS: Use of CSII (vs MDI) for pregestational DM in pregnancy is associated with higher odds of cesarean delivery and delivery of an LGA neonate. Further evaluation of how CSII use may influence neonatal size and delivery route is warranted.

Diabetes Research and Resource Sharing During the COVID-19 Pandemic: A Systematic Review and Experience from an Academic/Non-Profit Resource Website.

BACKGROUND: The magnitude of the response of the diabetes professional community to the COVID-19 pandemic is not known. We aimed to examine diabetes technology research trends and resources offered by professional organizations during this period. METHODS: We explored patterns of the response from the professional diabetes community to the pandemic by (1) systematically searching for articles related to diabetes, COVID-19, and diabetes technologies; (2) examining publication trends of research protocols (clinicaltrials.gov) and preprints (medRxiv); and (3) reviewing online resources from professional organizations including our website (COVIDinDiabetes.org; an Emory University-Diabetes Technology Society collaboration). RESULTS: We identified 492 articles published between December 2019 and December 2022 meeting our inclusion criteria. Telemedicine and continuous glucose monitoring were the most common reported technologies from most parts of the world. The largest number of preprint articles was published in 2020, with a decline in 2021 and 2022. The number of research protocols related to COVID-19 was the highest in 2020 and declined in 2021 and 2022. Resources from organizations included protocols adapted to treat patients with diabetes and COVID-19, training programs, emergency preparedness, and literature on diabetes and COVID-19. On our website (COVIDinDiabetes.org), there were 12 236 visits and 18 149 pageviews, with 1.6 actions per visits, with most visits coming from North America (N = 7233, 54.2%), South America (N = 2663, 21.8%), and Europe (N = 1219). CONCLUSIONS: We conclude that the COVID-19 pandemic promoted unprecedented global research productivity related to diabetes and COVID-19 and that the transition to the use of technology resources has been evident during this period.

A Glycemia Risk Index (GRI) of Hypoglycemia and Hyperglycemia for Continuous Glucose Monitoring Validated by Clinician Ratings.

BACKGROUND: A 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. METHODS: We 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. RESULTS: The 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. CONCLUSION: The 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.

Spinal Cord Stimulation for Painful Diabetic Neuropathy.

Spinal cord stimulation (SCS) technology has been recently approved by the US Food and Drug Administration (FDA) for painful diabetic neuropathy (PDN). The treatment involves surgical implantation of electrodes and a power source that delivers electrical current to the spinal cord. This treatment decreases the perception of pain in many chronic pain conditions, such as PDN. The number of patients with PDN treated with SCS and the amount of data describing their outcomes is expected to increase given four factors: (1) the large number of patients with this diagnosis, (2) the poor results that have been obtained for pain relief with pharmacotherapy and noninvasive non-pharmacotherapy, (3) the results to date with investigational SCS technology, and (4) the recent FDA approval of systems that deliver this treatment. Whereas traditional SCS replaces pain with paresthesias, a new form of SCS, called high-frequency 10-kHz SCS, first used for pain in 2015, can relieve PDN pain without causing paresthesias, although not all patients experience pain relief by SCS. This article describes (1) an overview of SCS technology, (2) the use of SCS for diseases other than diabetes, (3) the use of SCS for PDN, (4) a comparison of high-frequency 10-kHz and traditional SCS for PDN, (5) other SCS technology for PDN, (6) deployment of SCS systems, (7) barriers to the use of SCS for PDN, (8) risks of SCS technology, (9) current recommendations for using SCS for PDN, and (10) future developments in SCS.

Painful Diabetic Neuropathy: The Need for New Approaches.

Painful diabetic neuropathy is a common vexing problem for people with diabetes and a costly problem for society. The pathophysiology is not well understood, and no safe and effective mechanistically-based treatment has been identified. Poor glycemic control is a risk factor for painful diabetic neuropathy. Excessive intraneuronal glucose in people with diabetes can be shunted away from physiological glycolysis into multiple pathological pathways associated with neuropathy and pain. The first three treatments that are traditionally offered consist of risk factor reduction, lifestyle modifications, and pharmacological therapy, which includes only three drugs that are approved for this indication by the United States Food and Drug Administration. All of these traditional treatments are often inadequate for relieving neuropathic pain, and thus, new approaches are needed. Modern devices based on neuromodulation technology, which act directly on the nervous system, have been recently cleared by the United States Food and Drug Administration for painful diabetic neuropathy and offer promise as next-in-line therapy when traditional therapies fail.

Improving the Patient Experience With Longer Wear Infusion Sets Symposium Report.

Continuous subcutaneous insulin infusion (CSII) therapy is becoming increasingly popular. CSII provides convenient insulin delivery, precise dosing, easy adjustments for physical activity, stress, or illness, and integration with continuous glucose monitors in hybrid or other closed-loop systems. However, even as insulin pump hardware and software have advanced, technology for insulin infusion sets (IISs) has stayed relatively stagnant over time and is often referred to as the "Achilles heel" of CSII. To discuss barriers to insulin pump therapy and present information about advancements in, and results from clinical trials of extended wear IISs, Diabetes Technology Society virtually hosted the "Improving the Patient Experience with Longer Wear Infusion Sets Symposium" on December 1, 2021. The symposium featured experts in the field of IISs, including representatives from Steno Diabetes Center Copenhagen, University of California San Francisco, Stanford University, Medtronic Diabetes, and Science Consulting in Diabetes. The webinar's seven speakers covered (1) advancements in insulin pump therapy, (2) efficacy of longer wear infusion sets, and (3) innovations to reduce plastics and insulin waste.

Green Diabetes Summit 2021.

On July 21, 2021, Diabetes Technology Society convened the virtual Green Diabetes Summit. The event consisted of 23 representatives from key stakeholder groups based in both the United States and Europe. The purposes of the summit were to (1) provide background on the complexity of addressing sustainability-related issues, including waste management, of diabetes devices from many different perspectives along the products' life cycle stages, and (2) determine the feasibility and role of a coalition of stakeholders to find solutions, particularly in the design, use, and proper disposal of diabetes devices used in home care that no one stakeholder can resolve on their own.

Deconvoluting signals downstream of growth and immune receptor kinases by phosphocodes of the BSU1 family phosphatases.

Hundreds of leucine-rich repeat receptor kinases (LRR-RKs) have evolved to control diverse processes of growth, development and immunity in plants, but the mechanisms that link LRR-RKs to distinct cellular responses are not understood. Here we show that two LRR-RKs, the brassinosteroid hormone receptor BRASSINOSTEROID INSENSITIVE 1 (BRI1) and the flagellin receptor FLAGELLIN SENSING 2 (FLS2), regulate downstream glycogen synthase kinase 3 (GSK3) and mitogen-activated protein (MAP) kinases, respectively, through phosphocoding of the BRI1-SUPPRESSOR1 (BSU1) phosphatase. BSU1 was previously identified as a component that inactivates GSK3s in the BRI1 pathway. We surprisingly found that the loss of the BSU1 family phosphatases activates effector-triggered immunity and impairs flagellin-triggered MAP kinase activation and immunity. The flagellin-activated BOTRYTIS-INDUCED KINASE 1 (BIK1) phosphorylates BSU1 at serine 251. Mutation of serine 251 reduces BSU1's ability to mediate flagellin-induced MAP kinase activation and immunity, but not its abilities to suppress effector-triggered immunity and interact with GSK3, which is enhanced through the phosphorylation of BSU1 at serine 764 upon brassinosteroid signalling. These results demonstrate that BSU1 plays an essential role in immunity and transduces brassinosteroid-BRI1 and flagellin-FLS2 signals using different phosphorylation sites. Our study illustrates that phosphocoding in shared downstream components provides signalling specificities for diverse plant receptor kinases.

The Launch of the iCoDE Standard Project.

INTRODUCTION: The first meeting of the Integration of Continuous Glucose Monitor Data into the Electronic Health Record (iCoDE) project, organized by Diabetes Technology Society, took place virtually on January 27, 2022. METHODS: Clinicians, government officials, data aggregators, attorneys, and standards experts spoke in panels and breakout groups. Three themes were covered: 1) why digital health data integration into the electronic health record (EHR) is needed, 2) what integrated continuously monitored glucose data will look like, and 3) how this process can be achieved in a way that will satisfy clinicians, healthcare organizations, and regulatory experts. RESULTS: The meeting themes were addressed within eight sessions: 1) What Do Inpatient Clinicians Want to See With Integration of CGM Data into the EHR?, 2) What Do Outpatient Clinicians Want to See With Integration of CGM Data into the EHR?, 3) Why Are Data Standards and Guidances Useful?, 4) What Value Can Data Integration Services Add?, 5) What Are Examples of Successful Integration?, 6) Which Privacy, Security, and Regulatory Issues Must Be Addressed to Integrate CGM Data into the EHR?, 7) Breakout Group Discussions, and 8) Presentation of Breakout Group Ideas. CONCLUSIONS: Creation of data standards and workflow guidance are necessary components of the Integration of Continuous Glucose Monitor Data into the Electronic Health Record (iCoDE) standard project. This meeting, which launched iCoDE, will be followed by a set of working group meetings intended to create the needed standard.

Diabetes Technology Meeting 2021.

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.

Hospital Diabetes Meeting 2022.

The annual Virtual Hospital Diabetes Meeting was hosted by Diabetes Technology Society on April 1 and April 2, 2022. This meeting brought together experts in diabetes technology to discuss various new developments in the field of managing diabetes in hospitalized patients. Meeting topics included (1) digital health and the hospital, (2) blood glucose targets, (3) software for inpatient diabetes, (4) surgery, (5) transitions, (6) coronavirus disease and diabetes in the hospital, (7) drugs for diabetes, (8) continuous glucose monitoring, (9) quality improvement, (10) diabetes care and educatinon, and (11) uniting people, process, and technology to achieve optimal glycemic management. This meeting covered new technology that will enable better care of people with diabetes if they are hospitalized.

Continuous Ketone Monitoring Consensus Report 2021.

This article is the work product of the Continuous Ketone Monitoring Consensus Panel, which was organized by Diabetes Technology Society and met virtually on April 20, 2021. The panel consisted of 20 US-based experts in the use of diabetes technology, representing adult endocrinology, pediatric endocrinology, advanced practice nursing, diabetes care and education, clinical chemistry, and bioengineering. The panelists were from universities, hospitals, freestanding research institutes, government, and private practice. Panelists reviewed the medical literature pertaining to ten topics: (1) physiology of ketone production, (2) measurement of ketones, (3) performance of the first continuous ketone monitor (CKM) reported to be used in human trials, (4) demographics and epidemiology of diabetic ketoacidosis (DKA), (5) atypical hyperketonemia, (6) prevention of DKA, (7) non-DKA states of fasting ketonemia and ketonuria, (8) potential integration of CKMs with pumps and automated insulin delivery systems to prevent DKA, (9) clinical trials of CKMs, and (10) the future of CKMs. The panelists summarized the medical literature for each of the ten topics in this report. They also developed 30 conclusions (amounting to three conclusions for each topic) about CKMs and voted unanimously to adopt the 30 conclusions. This report is intended to support the development of safe and effective continuous ketone monitoring and to apply this technology in ways that will benefit people with diabetes.