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Background During the summer of 2019/2020, Australia experienced a catastrophic wildfire season that affected nearly 80% of Australians either directly or indirectly. The impacts of climate crisis on perinatal health have only recently begun to receive attention. The objective of this study was to understand experiences of perinatal women during the bushfire and smoke events of 2019–2020 regarding health, health care, and public health messaging. Methods Semistructured interviews were conducted by phone or web conferencing platforms with 43 participants living in the south-east of Australia who were either pregnant or who had recently had a baby during the 2019/2020 fires. Results The health impacts on participants of the fires, associated smoke, and evacuations for some, were both physical and psychological. Many participants sought information regarding how to protect their own health and that of their unborn/recently born children, but reported this difficult to find. Conclusions Pregnant women and new mothers exposed to bushfire events are a risk group for adverse physical and psychological outcomes. At the time of the 2019/2020 Australian bushfires, exposed women could not easily access evidence-based information to mitigate this risk. Family practitioners are well placed to provide pregnant women and new mothers with this sought-after information, but they need to be prepared well in advance of future similar events.

Background An important strategy to understand young people’s needs regarding technologies for type 1 diabetes mellitus (T1DM) management is to examine their day-to-day experiences with these technologies. Objective This study aimed to examine young people’s and their caregivers’ experiences with diabetes technologies in an exploratory way and relate the findings to the existing technology acceptance and technology design theories. On the basis of this procedure, we aimed to develop device characteristics that meet young people’s needs. Methods Overall, 16 in-person and web-based face-to-face interviews were conducted with 7 female and 9 male young people with T1DM (aged between 12 and 17 years) and their parents between December 2019 and July 2020. The participants were recruited through a pediatric diabetes clinic based at Canberra Hospital. Data-driven thematic analysis was performed before theory-driven analysis to incorporate empirical data results into the unified theory of acceptance and use of technology (UTAUT) and value-sensitive design (VSD). We used the COREQ (Consolidated Criteria for Reporting Qualitative Research) checklist for reporting our research procedure and findings. In this paper, we summarize the key device characteristics that meet young people’s needs. Results Summarized interview themes from the data-driven analysis included aspects of self-management, device use, technological characteristics, and feelings associated with device types. In the subsequent theory-driven analysis, the interview themes aligned with all UTAUT and VSD factors except for one (privacy). Privacy concerns or related aspects were not reported throughout the interviews, and none of the participants made any mention of data privacy. Discussions around ideal device characteristics focused on reliability, flexibility, and automated closed loop systems that enable young people with T1DM to lead an independent life and alleviate parental anxiety. However, in line with a previous systematic review by Brew-Sam et al, the analysis showed that reality deviated from these expectations, with inaccuracy problems reported in continuous glucose monitoring devices and technical failures occurring in both continuous glucose monitoring devices and insulin pumps. Conclusions Our research highlights the benefits of the transdisciplinary use of exploratory and theory-informed methods for designing improved technologies. Technologies for diabetes self-management require continual advancement to meet the needs and expectations of young people with T1DM and their caregivers. The UTAUT and VSD approaches were found useful as a combined foundation for structuring the findings of our study.

Background There is a lack of evidence for pre-eclampsia prophylaxis with aspirin in women with pre-existing diabetes mellitus (DM). Aims To examine the evidence for aspirin in pre-eclampsia prophylaxis in women with pre-existing DM. Material and methods An electronic search using Ovid MEDLINE, Embase, CinicalTrials.gov and the Cochrane CENTRAL register of controlled trials through to February 2021 was performed. Reference lists of identified studies, previous review articles, clinical practice guidelines and government reports were manually searched. Randomised controlled trials (RCTs) of aspirin vs placebo for pre-eclampsia prophylaxis were included. Articles were manually reviewed to determine if cohorts included women with DM. The systematic review was performed following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement. Data from included trials were extracted independently by two authors who also independently assessed risk of bias as per the Cochrane Handbook criteria version 5.1.0. Data were analysed using Rev-Man 5.4. Results Forty RCTs were identified, of which 11 included a confirmed subset of women with DM; however, data were insufficient for meta-analysis. Meta-analysis of 930 women with DM, from individual patient data included in a systematic review and unpublished data from one of the 11 RCTs, showed a non-significant difference in the outcome of pre-eclampsia in participants treated with aspirin compared to placebo (odds ratio 0.58; 95% CI 0.20-1.71; P = 0.33). Conclusions Pre-eclampsia risk reduction with aspirin prophylaxis in women with pre-existing DM may be similar to women without pre-existing DM. However, randomised data within this meta-analysis were insufficient, warranting the need for further studies within this high-risk group of women.

Objective: To gain an understanding of how women with gestational diabetes perceive their illness, and whether depressive/anxiety symptoms and/or psychological distress influence these illness perceptions. Method: A cross-sectional study was conducted with 159 pregnant women aged 18–44 attending gestational diabetes clinics. Participants completed a questionnaire, which included the Edinburgh Depression Scale (EDS), Kessler 10-item Psychological Distress Scale (K-10), Brief Illness Perception Questionnaire (BIPQ), and psychiatric/general health items. Multiple regression was used to explore the relationship between EDS (total and anxiety subscale) scores and BIPQ scores, as well as between K-10 (total and anxiety subscale) scores and BIPQ scores. Results: Regression analysis revealed a positive association between EDS total/anxiety subscale scores and BIPQ total score, as well as between K-10 total/anxiety subscale scores and BIPQ total score, controlling for potentially confounding variables. There was a strong positive correlation between EDS total score and K-10 total score. The most frequently expressed concern about GDM was an adverse effect on their baby’s health. A poor diet was the most frequently reported perceived ‘cause’ of GDM. Conclusion: Greater severity of depressive and anxiety symptoms, and psychological distress, is associated with more negative illness perceptions of GDM in pregnant women.

OBJECTIVE Preanalytical processing of blood samples can affect plasma glucose measurement because ongoing glycolysis by cells prior to centrifugation can lower its concentration. In June 2017, ACT Pathology changed the processing of oral glucose tolerance test (OGTT) blood samples for pregnant women from a delayed to an early centrifugation protocol. The effect of this change on the rate of gestational diabetes mellitus (GDM) diagnosis was determined. RESEARCH DESIGN AND METHODS All pregnant women in the Australian Capital Territory (ACT) are recommended for GDM testing with a 75-g OGTT using the World Health Organization diagnostic criteria. From January 2015 to May 2017, OGTT samples were collected into sodium fluoride (NaF) tubes and kept at room temperature until completion of the test (delayed centrifugation). From June 2017 to October 2018, OGTT samples in NaF tubes were centrifuged within 10 min (early centrifugation). RESULTS A total of 7,509 women were tested with the delayed centrifugation protocol and 4,808 with the early centrifugation protocol. The mean glucose concentrations for the fasting, 1-h, and 2-h OGTT samples were, respectively, 0.24 mmol/L (5.4%), 0.34 mmol/L (4.9%), and 0.16 mmol/L (2.3%) higher using the early centrifugation protocol (P < 0.0001 for all), increasing the GDM diagnosis rate from 11.6% (n = 869/7,509) to 20.6% (n = 1,007/4,887). CONCLUSIONS The findings of this study highlight the critical importance of the preanalytical processing protocol of OGTT blood samples used for diagnosing GDM. Delay in centrifuging of blood collected into NaF tubes will result in substantially lower rates of diagnosis than if blood is centrifuged early.

Background Gestational diabetes (GDM) is one of the commonest pregnancy complications and is placing an increasing burden on diabetes and obstetric resources. Aims To describe different antenatal models of care that have developed to address the increasing proportion of pregnancies complicated by GDM. Materials and methods Narrative review with thematic analysis from 15 volunteer antenatal diabetes in pregnancy services from Australia and New Zealand identified through a national diabetes organisation. Main outcomes were approaches to patient education, medical nutrition therapy (MNT), ongoing management and escalation of therapy for women with GDM. Results All clinics provided at least one group education and one MNT session within 1-2 weeks of GDM diagnosis. Women from culturally and linguistically diverse communities usually required 1:1 education. Ongoing management of women with GDM was through either all women being seen in the GDM clinic, a step-up approach (ongoing management by the primary antenatal team with diabetes team referral if self-blood glucose monitoring (SBGM) or insulin therapy dosage criteria are reached) or step-down approach (ongoing management by the diabetes team with step-down to the primary antenatal team if SBGM criteria are reached). Telehealth was used to reduce the burden of clinic attendance, particularly in rural areas. Conclusions Increasing numbers, earlier diagnoses, the need to provide care to women in rural, remote areas, and cultural/language differences, have generated a range of different antenatal models of care, allowed better workload accommodation and probably reduced costs. Randomised controlled trials of different models of care, with associated health economic analyses, are urgently needed.

Objective This study aims to explore whether the single-item Self-Rated Mental Health Question (SRMHQ) may be an indicator of the need for further mental health assessment and investigation in women with gestational diabetes mellitus (GDM). Method Women with GDM ( n = 159) were recruited from outpatient clinics in the Australian Capital Territory prior to a GDM information session (mean gestational age = 26, SD = 4.5). Participants were aged 20–45 (mean = 33, SD = 4.2) and completed a single-item Self-Rated Health Question (SRHQ), single-item Self-Rated Mental Health Question (SRMHQ), Kessler 10-item Psychological Distress Scale (K-10), and Edinburgh Depression Scale (EDS), as well as demographic, psychiatric, and general health items. Multiple regression was used to explore whether there was an association between SRMHQ responses and K-10 or EDS total scores. Results Regression analysis revealed that the SRMHQ was a statistically significant predictor of K-10 and EDS total scores, while controlling for key potential confounders. When mental health was rated as “poor” compared to “excellent,” this was associated with an additional 12 and 9 points on K-10 and EDS total scores, respectively. Conclusion The SRMHQ may have a role as an indicator of the need for further mental health assessment and investigation in women with gestational diabetes mellitus.

Diabetes can be diagnosed by either Fasting Plasma Glucose or Hemoglobin A1c. The aim of our study was to explore the differences between the two criteria through the development of a machine learning based diabetes diagnostic algorithm and analysing the predictive contribution of each input biomarker. Our study concludes that fasting insulin is predictive of diabetes defined by FPG, but not by HbA1c. Besides, 28 other fasting blood biomarkers were not significant predictors of diabetes.

Background Portable breath ketone sensors may help people with Type 1 Diabetes Mellitus (T1DM) avoid episodes of diabetic ketoacidosis; however, the design features preferred by users have not been studied. We aimed to elucidate breath sensor design preferences of young people with T1DM (age 12 to 16) and their parents to inform the development of a breath ketone sensor prototype that would best suit their diabetes management needs. Research designs and methods To elicit foundational experiences from which design preference ideas could be generated, two commercially available breath ketone sensors, designed for ketogenic diet monitoring, were explored over one week by ten young people with T1DM. Participants interacted with the breath ketone sensing devices, and undertook blood ketone testing, at least twice daily for five days to simulate use within a real life and ambulatory care setting. Semi-structured interviews were conducted post-testing with the ten young participants and their caregivers (n = 10) to elicit preferences related to breath sensor design and use, and to inform the co-design of a breath ketone sensor prototype for use in T1DM self-management. We triangulated our data collection with key informant interviews with two diabetes educators working in pediatric care about their perspectives related to young people using breath ketone sensors. Results Participants acknowledged the non-invasiveness of breath sensors as compared to blood testing. Affordability, reliability and accuracy were identified as prerequisites for breath ketone sensors used for diabetes management. Design features valued by young people included portability, ease of use, sustainability, readability and suitability for use in public. The time required to use breath sensors was similar to that for blood testing. The requirement to maintain a 10-second breath exhalation posed a challenge for users. Diabetes educators highlighted the ease of use of breath devices especially for young people who tended to under-test using blood ketone strips. Conclusions Breath ketone sensors for diabetes management have potential that may facilitate ketone testing in young people. Our study affirms features for young people that drive usability of breath sensors among this population, and provides a model of user preference assessment.

(unstructured)An important strategy to understand young people’s needs regarding technologies for Type 1 Diabetes Mellitus (T1DM) management is to examine their day-to-day experiences with these technologies. This study aimed to describe T1DM youth and their caregivers’ experiences and preferences regarding insulin pumps, sensor technologies, and related communication technologies based on a hybrid theoretical foundation, as well as to describe derived ideal device characteristics. Sixteen face-to-face interviews were conducted with young people and their parents. Data analysis included data-driven thematic analysis followed by theory-driven analysis (Unified Theory of Acceptance and Use of Technology; value sensitive design). Initial themes derived from the interviews included aspects of self-management, device use, technological characteristics, and feelings associated with device types. Interview findings were congruent with factors from the two theories. Discussions around ideal devices focused on reliability, flexibility, and automated closed loop systems that enabled an independent life for young people and alleviated parental anxiety. Reality deviated from expectations, with inaccuracy problems and technical failures reported. Technologies for diabetes self-management require continual advancement to meet the needs of young people with T1DM and their caregivers. Understanding experiences and challenges with devices enabled us to identify theory-supported device characteristics useful for the designing of improved technologies.Extended abstract (structured)BackgroundAn important strategy to understand young people’s needs and preferences regarding technologies for Type 1 Diabetes Mellitus (T1DM) management is to examine their day-to-day experiences with these technologies.ObjectiveThis study aimed to describe T1DM youth and their caregivers’ experiences and preferences regarding insulin pumps, sensor technologies, and related communication technologies based on a hybrid theoretical foundation, as well as to describe derived ideal device characteristics.Materials and MethodsSixteen face-to-face interviews were conducted with young people with T1DM and their parents about their diabetes technology use. A combination of data-driven thematic analysis in a first stage, and theory-driven analysis in a second stage was used to incorporate in-depth study analysis and existing theoretical literature. Relevant literature included technology adoption (Unified Theory of Acceptance and Use of Technology/UTAUT) and value sensitive design (VSD) models. Based on this approach ideal device characteristics for young people with T1DM were summarized.ResultsInitial themes derived from the interviews included aspects of diabetes self-management, device use, and specific device-related technological characteristics and feelings associated with the specific device types (continuous glucose monitoring, insulin pump, flash glucose monitoring). The interview data delivered information congruent with all UTAUT and VSD factors except for one (privacy). Discussions around ideal diabetes devices focused on reliability, flexibility, and automated closed loop systems that enabled an independent and normal life for adolescents, and alleviated parental anxiety. However, in line with the previous systematic review, the interview analysis showed that reality deviated from these expectations, with inaccuracy problems reported for continuous glucose monitoring devices, and technical failures occurring in both continuous glucose monitoring devices and insulin pumps.ConclusionsUTAUT and VSD approaches were found useful as a combined foundation for structuring our study findings. Technologies for diabetes self-management require continual advancement to meet the needs and expectations of young people with T1DM and their caregivers. Understanding their experiences, as well as challenges with the devices, enabled us to identify theory-supported ideal device characteristics that can be useful in the designing and developing of improved technologies.

Objective To explore the experiences of young people with type 1 diabetes mellitus (T1DM) and their parents in accessing integrated family-centred care in the Australian Capital Territory during the COVID-19 pandemic. Methods and analysis This is a pragmatic, qualitative descriptive study for which we conducted semistructured interviews with 11 young people with T1DM aged 12–16 years and 10 of their parents who attended an outpatient diabetes service in Canberra, Australia. Thematic analysis was conducted in accordance with the methods outlined by Braun and Clarke. Results Three themes were identified: feeling vulnerable, new ways of accessing care and trust in the interdisciplinary diabetes healthcare team. Participants believed having T1DM made them more vulnerable to poor outcomes if they contracted COVID-19, resulting in avoidance of face-to-face care. Telephone consultations offered a convenient and contact-free way to undertake 3-monthly reviews. The greatest difference between telephone and face-to-face consultations was not having access to the whole interdisciplinary diabetes support team at one appointment, physical examination and haemoglobin A1c testing during telehealth consultations. Participants trusted that clinicians would arrange face-to-face meetings if required. Some felt a video option might be better than telephone, reflecting in part the need for more training in communication skills for remote consultations. Conclusion Young people with T1DM and their parents require collaborative care and contact with multiple healthcare professionals to facilitate self-management and glycaemic control. While telephone consultations offered convenient, safe, contact-free access to healthcare professionals during the COVID-19 pandemic, the added value of video consultations and facilitating access to the whole interdisciplinary diabetes support team need to be considered in future clinical implementation of telehealth.

Background. Portable breath ketone sensors may help people with Type 1 Diabetes Mellitus (T1DM) avoid episodes of diabetic ketoacidosis; however the design features preferred by users have not been studied. We aimed to elucidate breath analysis and design preferences associated with commercial breath ketone devices among young people with T1DM aged 12-16 years and their parents in order to inform the development of a breath ketone sensor prototype for diabetes management. Research Designs and Methods. Two commercially available breath ketone sensors, designed for ketogenic diet monitoring, were explored over one week by ten young people with T1DM to get an insight into breath measurements. Participants interacted with the devices at least twice daily for five days, taking breath ketone, blood ketone and blood glucose measurements. Semi-structured interviews were conducted post-testing with the young participants and their caregivers to elicit preferences related to breath analysis and to inform the co-design of a diabetes breath ketone sensor prototype. To validate the results from a professional healthcare perspective, we interviewed two diabetes educators working in pediatric care about their perspective of young people using breath ketone sensors. Results. Participants acknowledged the non-invasiveness of breath sensors as compared to blood testing. Affordability, reliability and accuracy were identified as prerequisites for breath ketone sensors used for diabetes management. Design features valued by young people included portability, ease of use, sustainability, readability and suitability for use in public. The time required to use breath sensors was similar to that for blood testing. The requirement to maintain a 10-second breath exhalation posed a challenge for users. Diabetes educators highlighted the ease of use of breath devices especially for young people with insufficient blood ketone testing. Conclusions. Breath ketone sensors for diabetes management bear potential to facilitate ketone testing in young people. Our study affirms features for young people that drive usability of breath sensors among this population, and provides a model of user preference assessment.

BackgroundMaintenance of a normal fetal nutrient supply requires major adaptations in maternal metabolic physiology, including of the islet beta-cell. The role of lipid signaling processes in the mechanisms of islet beta-cell adaptation to pregnancy has been minimally investigated.ObjectiveTo determine the effects of pregnancy on islet fatty acid (FA) metabolic partitioning and FA augmentation of glucose-stimulated insulin secretion (GSIS).MethodsAge matched virgin, early pregnant (gestational day-11, G11) and late pregnant (G19) Sprague-Dawley rats were studied. Fasted and fed state biochemistry, oral glucose tolerance tests (OGTT), and fasted and post-OGTT liver glycogen, were determined to assess in vivo metabolic characteristics. In isolated islets, FA (BSA-bound palmitate 0.25 mmol/l) augmentation of GSIS, FA partitioning into esterification and oxidation processes using metabolic tracer techniques, lipolysis by glycerol release, triacylglycerols (TG) content, and the expression of key beta-cell genes were determined.ResultsPlasma glucose in pregnancy was lower, including during the OGTT (glucose area under the curve 0-120 min (AUC0-120); 655±24 versus 849±13 mmol.l-1.min; G19 vs virgin; P0-120; 97±7 versus 83±7 ng.ml-1.min; G19 vs virgin; not significant). Liver glycogen was depleted in fasted G19 rats with full recovery after oral glucose. Serum TG increased during pregnancy (4.4±0.4, 6.7±0.5; 17.1±1.5 mmol/l; virgin, G11, G19, PPPpargc1a, a key regulator of mitochondrial metabolism, was reduced by 51% in G11 and 64% in G19 pregnant rat islets compared to virgin rat islets (PConclusionA lowered set-point for islet and hepatic glucose homeostasis in the pregnant rat has been confirmed. Islet adaptation to pregnancy includes increased FA esterification, reduced FA oxidation, and enhanced FA augmentation of glucose-stimulated insulin secretion.

High protein feeding has been shown to accelerate the development of type 1 diabetes in female non-obese diabetic (NOD) mice. Here, we investigated whether reducing systemic amino acid availability via knockout of the Slc6a19 gene encoding the system B(0) neutral amino acid transporter AT1 would reduce the incidence or delay the onset of type 1 diabetes in female NOD mice. Slc6a19 gene deficient NOD mice were generated using the CRISPR-Cas9 system which resulted in marked aminoaciduria. The incidence of diabetes by week 30 was 59.5% (22/37) and 69.0% (20/29) in NOD.Slc6a19+/+ and NOD.Slc6a19−/− mice, respectively (hazard ratio 0.77, 95% confidence interval 0.41–1.42, Mantel-Cox log rank test: p = 0.37). The median survival time without diabetes was 28 and 25 weeks for NOD.Slc6a19+/+ and NOD.Slc6a19−/− mice, respectively (ratio 1.1, 95% confidence interval 0.6–2.0). Histological analysis did not show differences in islet number or the degree of insulitis between wild type and Slc6a19 deficient NOD mice. We conclude that Slc6a19 deficiency does not prevent or delay the development of type 1 diabetes in female NOD mice.

Aims/hypothesis Pancreatic beta cell dedifferentiation, transdifferentiation into other islet cells and apoptosis have been implicated in beta cell failure in type 2 diabetes, although the mechanisms are poorly defined. The endoplasmic reticulum stress response factor X-box binding protein 1 (XBP1) is a major regulator of the unfolded protein response. XBP1 expression is reduced in islets of people with type 2 diabetes, but its role in adult differentiated beta cells is unclear. Here, we assessed the effects of Xbp1 deletion in adult beta cells and tested whether XBP1-mediated unfolded protein response makes a necessary contribution to beta cell compensation in insulin resistance states. Methods Mice with inducible beta cell-specific Xbp1 deletion were studied under normal (chow diet) or metabolic stress (high-fat diet or obesity) conditions. Glucose tolerance, insulin secretion, islet gene expression, alpha cell mass, beta cell mass and apoptosis were assessed. Lineage tracing was used to determine beta cell fate. Results Deletion of Xbp1 in adult mouse beta cells led to beta cell dedifferentiation, beta-to-alpha cell transdifferentiation and increased alpha cell mass. Cell lineage-specific analyses revealed that Xbp1 deletion deactivated beta cell identity genes (insulin, Pdx1, Nkx6.1, Beta2, Foxo1) and derepressed beta cell dedifferentiation (Aldh1a3) and alpha cell (glucagon, Arx, Irx2) genes. Xbp1 deletion in beta cells of obese ob/ob or high-fat diet-fed mice triggered diabetes and worsened glucose intolerance by disrupting insulin secretory capacity. Furthermore, Xbp1 deletion increased beta cell apoptosis under metabolic stress conditions by attenuating the antioxidant response. Conclusions/interpretation These findings indicate that XBP1 maintains beta cell identity, represses beta-to-alpha cell transdifferentiation and is required for beta cell compensation and prevention of diabetes in insulin resistance states. Graphical abstract

IntroductionThe terms ‘precision medicine’ and ‘personalised medicine’ have become key terms in health-related research and in science-related public communication. However, the application of these two concepts and their interpretation in various disciplines are heterogeneous, which also affects research translation and public awareness. This leads to confusion regarding the use and distinction of the two concepts. Our aim is to provide a snapshot of the current understanding of these concepts.Methods and analysisOur study will use Rodgers’ evolutionary concept analysis to systematically examine the current understanding of the concepts ‘precision medicine’ and ‘personalised medicine’ in clinical medicine, biomedicine (incorporating genomics and bioinformatics), health services research, physics, chemistry, engineering, machine learning and artificial intelligence, and to identify their respective attributes (clusters of characteristics) and surrogate and related terms. A systematic search of the literature will be conducted for 2016–2022 using databases relevant to each of these disciplines: ACM Digital Library, CINAHL, Cochrane Library, F1000Research, IEEE Xplore, PubMed/Medline, Science Direct, Scopus and Web of Science. These are among the most representative databases for the included disciplines. We will examine similarities and differences in definitions of ‘precision medicine’ and ‘personalised medicine’ in the respective disciplines and across (sub)disciplines, including attributes of each term. This will enable us to determine how these two concepts are distinguished.Ethics and disseminationFollowing ethical and research standards, we will comprehensively report the methodology for a systematic analysis following Rodgers’ concept analysis method. Our systematic concept analysis will contribute to the clarification of the two concepts and distinction in their application in given settings and circumstances. Such a broad concept analysis will contribute to non-systematic syntheses of the concepts, or occasional systematic reviews on one of the concepts that have been published in specific disciplines, in order to facilitate interdisciplinary communication, translational medical research and implementation science.

People with type 1 diabetes mellitus (T1DM) must continuously monitor their blood glucose levels and regulate them by insulin dosing to stay in a safe range. A reliable glucose prediction technique could pre-alert the risk of abnormal glycaemia in the near future. In this paper, we apply an attention-based deep network for glucose prediction, which models both the temporal dependencies and the physiological relations among glucose and glucose-related life events, including insulin and carbohydrate intake. We also propose to make use of the knowledge learned from non-target subjects with the same disease to improve the personalised prediction by applying parameters transfer. Our approach was evaluated on the standard benchmark OhioT1DM dataset, where the experiments achieved average root mean square errors over the 12 subjects of 17.82 mg/dL for 30 minutes and 28.54 mg/dL for 60 minutes. Additionally, our ablation experiments indicated that the use of transfer learning constantly improved the prediction. On this basis, we conclude that our approach achieves state-of-the-art performance with statistical significance, and data from other people with T1DM could help on improving personalised predictions. We release our codes at https://github.com/r-cui/GluPred under the MIT license.

Background Monitoring glucose and other parameters in persons with type 1 diabetes (T1D) can enhance acute glycemic management and the diagnosis of long-term complications of the disease. For most persons living with T1D, the determination of insulin delivery is based on a single measured parameter—glucose. To date, wearable sensors exist that enable the seamless, noninvasive, and low-cost monitoring of multiple physiological parameters. Objective The objective of this literature survey is to explore whether some of the physiological parameters that can be monitored with noninvasive, wearable sensors may be used to enhance T1D management. Methods A list of physiological parameters, which can be monitored by using wearable sensors available in 2020, was compiled by a thorough review of the devices available in the market. A literature survey was performed using search terms related to T1D combined with the identified physiological parameters. The selected publications were restricted to human studies, which had at least their abstracts available. The PubMed and Scopus databases were interrogated. In total, 77 articles were retained and analyzed based on the following two axes: the reported relations between these parameters and T1D, which were found by comparing persons with T1D and healthy control participants, and the potential areas for T1D enhancement via the further analysis of the found relationships in studies working within T1D cohorts. Results On the basis of our search methodology, 626 articles were returned, and after applying our exclusion criteria, 77 (12.3%) articles were retained. Physiological parameters with potential for monitoring by using noninvasive wearable devices in persons with T1D included those related to cardiac autonomic function, cardiorespiratory control balance and fitness, sudomotor function, and skin temperature. Cardiac autonomic function measures, particularly the indices of heart rate and heart rate variability, have been shown to be valuable in diagnosing and monitoring cardiac autonomic neuropathy and, potentially, predicting and detecting hypoglycemia. All identified physiological parameters were shown to be associated with some aspects of diabetes complications, such as retinopathy, neuropathy, and nephropathy, as well as macrovascular disease, with capacity for early risk prediction. However, although they can be monitored by available wearable sensors, most studies have yet to adopt them, as opposed to using more conventional devices. Conclusions Wearable sensors have the potential to augment T1D sensing with additional, informative biomarkers, which can be monitored noninvasively, seamlessly, and continuously. However, significant challenges associated with measurement accuracy, removal of noise and motion artifacts, and smart decision-making exist. Consequently, research should focus on harvesting the information hidden in the complex data generated by wearable sensors and on developing models and smart decision strategies to optimize the incorporation of these novel inputs into T1D interventions.

BACKGROUND Type 1 diabetes (T1D) is a chronic autoimmune disease in which a deficiency in insulin production impairs the glucose homeostasis of the body. Continuous subcutaneous infusion of insulin is a commonly used treatment method. Artificial pancreas systems (APS) use continuous glucose level monitoring and continuous subcutaneous infusion of insulin in a closed-loop mode incorporating a controller (or control algorithm). However, the operation of APS is challenging because of complexities arising during meals, exercise, stress, sleep, illnesses, glucose sensing and insulin action delays, and the cognitive burden. To overcome these challenges, options to augment APS through integration of additional inputs, creating multi-input APS (MAPS), are being investigated. OBJECTIVE The aim of this survey is to identify and analyze input data, control architectures, and validation methods of MAPS to better understand the complexities and current state of such systems. This is expected to be valuable in developing improved systems to enhance the quality of life of people with T1D. METHODS A literature survey was conducted using the Scopus, PubMed, and IEEE Xplore databases for the period January 1, 2005, to February 10, 2020. On the basis of the search criteria, 1092 articles were initially shortlisted, of which 11 (1.01%) were selected for an in-depth narrative analysis. In addition, 6 clinical studies associated with the selected studies were also analyzed. RESULTS Signals such as heart rate, accelerometer readings, energy expenditure, and galvanic skin response captured by wearable devices were the most frequently used additional inputs. The use of invasive (blood or other body fluid analytes) inputs such as lactate and adrenaline were also simulated. These inputs were incorporated to switch the mode of the controller through activity detection, directly incorporated for decision-making and for the development of intermediate modules for the controller. The validation of the MAPS was carried out through the use of simulators based on different physiological models and clinical trials. CONCLUSIONS The integration of additional physiological signals with continuous glucose level monitoring has the potential to optimize glucose control in people with T1D through addressing the identified limitations of APS. Most of the identified additional inputs are related to wearable devices. The rapid growth in wearable technologies can be seen as a key motivator regarding MAPS. However, it is important to further evaluate the practical complexities and psychosocial aspects associated with such systems in real life.

Background In the last decade, diabetes management has begun to transition to technology-based care, with young people being the focus of many technological advances. Yet, detailed insights into the experiences of young people and their caregivers of using technology to manage type 1 diabetes mellitus are lacking. Objective The objective of our study was to describe the breadth of experiences and perspectives on diabetes technology use among children and adolescents with type 1 diabetes mellitus and their caregivers. Methods This systematic literature review used integrated thematic analysis to guide a narrative synthesis of the included studies. We analyzed the perspectives and experiences of young people with type 1 diabetes mellitus and their caregivers reported in qualitative studies, quantitative descriptive studies, and studies with a mixed methods design. Results Seventeen articles met the inclusion criteria, and they included studies on insulin pump, glucose sensors, and remote monitoring systems. The following eight themes were derived from the analysis: (1) expectations of the technology prior to use, (2) perceived impact on sleep and overnight experiences, (3) experiences with alarms, (4) impact on independence and relationships, (5) perceived usage impact on blood glucose control, (6) device design and features, (7) financial cost, and (8) user satisfaction. While many advantages of using diabetes technology were reported, several challenges for its use were also reported, such as cost, the size and visibility of devices, and the intrusiveness of alarms, which drew attention to the fact that the user had type 1 diabetes mellitus. Continued use of diabetes technology was underpinned by its benefits outweighing its challenges, especially among younger people. Conclusions Diabetes technologies have improved the quality of life of many young people with type 1 diabetes mellitus and their caregivers. Future design needs to consider the impact of these technologies on relationships between young people and their caregivers, and the impact of device features and characteristics such as size, ease of use, and cost.

BACKGROUND In the last decade, diabetes management has begun to transition to technology-based care, with young people being the focus of many technological advances. Yet, detailed insights into the experiences of young people and their caregivers of using technology to manage type 1 diabetes mellitus are lacking. OBJECTIVE The objective of our study was to describe the breadth of experiences and perspectives on diabetes technology use among children and adolescents with type 1 diabetes mellitus and their caregivers. METHODS This systematic literature review used integrated thematic analysis to guide a narrative synthesis of the included studies. We analyzed the perspectives and experiences of young people with type 1 diabetes mellitus and their caregivers reported in qualitative studies, quantitative descriptive studies, and studies with a mixed methods design. RESULTS Seventeen articles met the inclusion criteria, and they included studies on insulin pump, glucose sensors, and remote monitoring systems. The following eight themes were derived from the analysis: (1) expectations of the technology prior to use, (2) perceived impact on sleep and overnight experiences, (3) experiences with alarms, (4) impact on independence and relationships, (5) perceived usage impact on blood glucose control, (6) device design and features, (7) financial cost, and (8) user satisfaction. While many advantages of using diabetes technology were reported, several challenges for its use were also reported, such as cost, the size and visibility of devices, and the intrusiveness of alarms, which drew attention to the fact that the user had type 1 diabetes mellitus. Continued use of diabetes technology was underpinned by its benefits outweighing its challenges, especially among younger people. CONCLUSIONS Diabetes technologies have improved the quality of life of many young people with type 1 diabetes mellitus and their caregivers. Future design needs to consider the impact of these technologies on relationships between young people and their caregivers, and the impact of device features and characteristics such as size, ease of use, and cost.

The prevalence of obesity and obesity-related metabolic comorbidities are rapidly increasing worldwide, placing a huge economic burden on health systems. Excessive nutrient supply combined with reduced physical exercise results in positive energy balance that promotes adipose tissue expansion. However, the metabolic response and pattern of fat accumulation is variable, depending on the individual’s genetic and acquired susceptibility factors. Some develop metabolically healthy obesity (MHO) and are resistant to obesity-associated metabolic diseases for some time, whereas others readily develop metabolically unhealthy obesity (MUO). An unhealthy response to excess fat accumulation could be due to susceptibility intrinsic factors (e.g., increased likelihood of dedifferentiation and/or inflammation), or by pathogenic drivers extrinsic to the adipose tissue (e.g., hyperinsulinemia), or a combination of both. This review outlines the major transcriptional factors and genes associated with adipogenesis and regulation of adipose tissue homeostasis and describes which of these are disrupted in MUO compared to MHO individuals. It also examines the potential role of pathogenic insulin hypersecretion as an extrinsic factor capable of driving the changes in adipose tissue which cause transition from MHO to MUO. On this basis, therapeutic approaches currently available and emerging to prevent and reverse the transition from MHO to MUO transition are reviewed.

Background Type 1 diabetes (T1D) is a chronic autoimmune disease in which a deficiency in insulin production impairs the glucose homeostasis of the body. Continuous subcutaneous infusion of insulin is a commonly used treatment method. Artificial pancreas systems (APS) use continuous glucose level monitoring and continuous subcutaneous infusion of insulin in a closed-loop mode incorporating a controller (or control algorithm). However, the operation of APS is challenging because of complexities arising during meals, exercise, stress, sleep, illnesses, glucose sensing and insulin action delays, and the cognitive burden. To overcome these challenges, options to augment APS through integration of additional inputs, creating multi-input APS (MAPS), are being investigated. Objective The aim of this survey is to identify and analyze input data, control architectures, and validation methods of MAPS to better understand the complexities and current state of such systems. This is expected to be valuable in developing improved systems to enhance the quality of life of people with T1D. Methods A literature survey was conducted using the Scopus, PubMed, and IEEE Xplore databases for the period January 1, 2005, to February 10, 2020. On the basis of the search criteria, 1092 articles were initially shortlisted, of which 11 (1.01%) were selected for an in-depth narrative analysis. In addition, 6 clinical studies associated with the selected studies were also analyzed. Results Signals such as heart rate, accelerometer readings, energy expenditure, and galvanic skin response captured by wearable devices were the most frequently used additional inputs. The use of invasive (blood or other body fluid analytes) inputs such as lactate and adrenaline were also simulated. These inputs were incorporated to switch the mode of the controller through activity detection, directly incorporated for decision-making and for the development of intermediate modules for the controller. The validation of the MAPS was carried out through the use of simulators based on different physiological models and clinical trials. Conclusions The integration of additional physiological signals with continuous glucose level monitoring has the potential to optimize glucose control in people with T1D through addressing the identified limitations of APS. Most of the identified additional inputs are related to wearable devices. The rapid growth in wearable technologies can be seen as a key motivator regarding MAPS. However, it is important to further evaluate the practical complexities and psychosocial aspects associated with such systems in real life.

Overweight and obesity are major contributors to the total global burden of chronic diseases due to the consequences of their associated comorbid conditions which can affect all systems of the body. These comorbidities are often considered to be consequence of the excess weight with unidirectional causality; however, causality is almost certainly multidirectional with roles for both physical and psychological factors. In this chapter, an overview of overweight- and obesity-related medical illnesses, categorised according to the body systems affected, is provided. Some focus is directed towards the role of the metabolic syndrome in these illnesses. The importance of causality of comorbid conditions at early, middle and late stages of disease is emphasised, as interventions targeting causalities at each of these times are likely to have the greatest impact on lessening the burden of overweight and obesity on affected individuals.

Purpose To compare per-region macular sensitivity and delay from objective perimetry with Matrix perimetry and retinal thickness in mild diabetic macular edema (DMO). Methods Thirty-three patients with type 2 diabetes (T2D) aged 59.2 ± 10.5 years participated in a longitudinal study. Macular thickness, sensitivities and delays from the objectiveFIELD Analyzer (OFA), and Matrix perimeter sensitivities were mapped onto a common spatial layout to compute per-region correlations between structure/function measures. A generalized linear mixed-effects logistic regression model determined which variables contributed to clinical diagnosis of DMO. Results For OFA, the mean sensitivity differences compared with normal in patients with T2D were negative and the mean delay differences positive, indicating lowered sensitivities and prolonged delays, both increasing with diabetes duration. Shorter diabetes duration could produce either localized peripheral hypersensitivities or shorter delays. Functional change could occur when retinal thickness was stable. Peripheral macular thickness correlated with central and peripheral OFA sensitivity and delay, all P < 0.0012 in DMO and a median of P = 0.001 without DMO; this was not true for Matrix sensitivities. The logistic model determined that peripheral thickness, OFA sensitivity (P = 0.043), and time in the study (P = 0.001) contribute independently to the odds of DMO versus no DMO. Conclusions Mean sensitivities decreased and mean delays increased with duration of diabetes. Peripheral macular thickness correlated significantly with central and peripheral macular OFA sensitivity and delay. Peripheral macular thickness and functional measures may provide sensitive prognostic data. Translational Relevance Functional loss can precede structural change in DMO, so including such functional assessment for deciding on treatment may be beneficial.

Metabolic deceleration in pancreatic β-cells is associated with inhibition of glucose-induced insulin secretion (GIIS), but only in the presence of intermediate/submaximal glucose concentrations. Here, we used acute metformin treatment as a tool to induce metabolic deceleration in INS1 (832/13) β-cells, with the goal of identifying key pathways and metabolites involved in GIIS. Metabolites and pathways previously implicated as signals for GIIS were measured in the cells at 2–25 mm glucose, with or without 5 mm metformin. We defined three criteria to identify candidate signals: 1) glucose-responsiveness, 2) sensitivity to metformin-induced inhibition of the glucose effect at intermediate glucose concentrations, and 3) alleviation of metformin inhibition by elevated glucose concentrations. Despite the lack of recovery from metformin-induced impairment of mitochondrial energy metabolism (glucose oxidation, O2 consumption, and ATP production), insulin secretion was almost completely restored at elevated glucose concentrations. Meeting the criteria for candidates involved in promoting GIIS were the following metabolic indicators and metabolites: cytosolic NAD+/NADH ratio (inferred from the dihydroxyacetone phosphate:glycerol-3-phosphate ratio), mitochondrial membrane potential, ADP, Ca2+, 1-monoacylglycerol, diacylglycerol, malonyl-CoA, and HMG-CoA. On the contrary, most of the purine and nicotinamide nucleotides, acetoacetyl-CoA, H2O2, reduced glutathione, and 2-monoacylglycerol were not glucose-responsive. Overall these results underscore the significance of mitochondrial energy metabolism-independent signals in GIIS regulation; in particular, the candidate lipid signaling molecules 1-monoacylglycerol, diacylglycerol, and malonyl-CoA; the predominance of KATP/Ca2+ signaling control by low ADP·Mg2+ rather than by high ATP levels; and a role for a more oxidized state (NAD+/NADH) in the cytosol during GIIS that favors high glycolysis rates.

Overweight/obesity, sleep disturbance, night eating, and a sedentary lifestyle are common co-occurring problems. There is a tendency for them to co-occur together more often than they occur alone. In some cases, there is clarity as to the time course and evolution of the phenomena. However, specific mechanism(s) that are proposed to explain a single co-occurrence cannot fully explain the more generalized tendency to develop concurrent symptoms and/or disorders after developing one of the phenomena. Nor is there a clinical theory with any utility in explaining the development of co-occurring symptoms, disorders and behaviour and the mechanism(s) by which they occur. Thus, we propose a specific mechanism—dysregulation of core body temperature (CBT) that interferes with sleep onset—to explain the development of the concurrences. A detailed review of the literature related to CBT and the phenomena that can alter CBT or are altered by CBT is provided. Overweight/obesity, sleep disturbance and certain behaviour (e.g. late-night eating, sedentarism) were linked to elevated CBT, especially an elevated nocturnal CBT. A number of existing therapies including drugs (e.g. antidepressants), behavioural therapies (e.g. sleep restriction therapy) and bright light therapy can also reduce CBT. An elevation in nocturnal CBT that interferes with sleep onset can parsimoniously explain the development and perpetuation of common co-occurring symptoms, disorders and behaviour including overweight/obesity, sleep disturbance, late-night eating, and sedentarism. Nonetheless, a significant correlation between CBT and the above symptoms, disorders and behaviour does not necessarily imply causation. Thus, statistical and methodological issues of relevance to this enquiry are discussed including the likely presence of autocorrelation. Level V, narrative review.

BACKGROUND: Canagliflozin is a sodium–glucose cotransporter 2 inhibitor that reduces glycemia as well as blood pressure, body weight, and albuminuria in people with diabetes. We report the effects of treatment with canagliflozin on cardiovascular, renal, and safety outcomes. METHODS: The CANVAS Program integrated data from two trials involving a total of 10,142 participants with type 2 diabetes and high cardiovascular risk. Participants in each trial were randomly assigned to receive canagliflozin or placebo and were followed for a mean of 188.2 weeks. The primary outcome was a composite of death from cardiovascular causes, nonfatal myocardial infarction, or nonfatal stroke. RESULTS: The mean age of the participants was 63.3 years, 35.8% were women, the mean duration of diabetes was 13.5 years, and 65.6% had a history of cardiovascular disease. The rate of the primary outcome was lower with canagliflozin than with placebo (occurring in 26.9 vs. 31.5 participants per 1000 patient-years; hazard ratio, 0.86; 95% confidence interval [CI], 0.75 to 0.97; P

While few dispute the existence of the metabolic syndrome as a clustering of factors indicative of poor metabolic health, its utility above that of its individual components in the clinical care of individual patients is questioned. This is likely a consequence of the failure of clinicians and scientists to agree on a unifying mechanism to explain the metabolic syndrome. Insulin resistance has most commonly been proposed for this role and is generally considered to be a root causative factor for not only metabolic syndrome but also for its associated conditions of non-alcoholic fatty liver disease (NAFLD), polycystic ovary syndrome (PCOS), obesity-related type 2 diabetes (T2D) and atherosclerotic cardiovascular disease (ASCVD). An alternative view, for which evidence is mounting, is that hyper-responsiveness of islet β-cells to a hostile environment, such as westernised lifestyle, is primary and that the resulting hyperinsulinaemia drives the other components of the metabolic syndrome. Importantly, within this new conceptual framework, insulin resistance, while always a biomarker and state of poor metabolic health, is not considered to be harmful, but a protective adaptive response of critical tissues including the myocardium against insulin-induced metabolic stress. This major shift in how metabolic syndrome can be considered puts insulin hypersecretion into position as the unifying mechanism. If shown to be correct, this new conceptual framework has major implications for the future prevention and management of the metabolic syndrome, including its associated conditions of NAFLD, PCOS, obesity-related T2D and ASCVD.

Background: To test the feasibility of benchmarking the care of women with pregnancies complicated by hyperglycaemia. Methods: A retrospective audit of volunteer diabetes services in Australia and New Zealand involving singleton pregnancies resulting in live births between 2014 and 2020. Ranges are shown and compared across services. Results: The audit included 10,144 pregnancies (gestational diabetes mellitus (GDM) = 8696, type 1 diabetes (T1D) = 435, type 2 diabetes (T2D) = 1013) from 11 diabetes services. Among women with GDM, diet alone was used in 39.4% (ranging among centres from 28.8–57.3%), metformin alone in 18.8% (0.4–43.7%), and metformin and insulin in 10.1% (1.5–23.4%), when compared between sites, all p &lt, 0.001. Birth was by elective caesarean in 12.1% (3.6–23.7%) or emergency caesarean in 9.5% (3.5–21.2%) (all p &lt, 0.001). Preterm births (&lt, 37 weeks) ranged from 3.7% to 9.4% (p &lt, 0.05), large for gestational age 10.3–26.7% (p &lt, 0.001), admission to special care nursery 16.7–25.0% (p &lt, 0.001), and neonatal hypoglycaemia (&lt, 2.6 mmol/L) 6.0–27.0% (p &lt, 0.001). Many women with T1D and T2D had limited pregnancy planning including first trimester hyperglycaemia (HbA1c &gt, 6.5% (48 mmol/mol)), 78.4% and 54.6%, respectively (p &lt, 0.001). Conclusion: Management of maternal hyperglycaemia and pregnancy outcomes varied significantly. The maintenance and extension of this benchmarking service provides opportunities to identify policy and clinical approaches to improve pregnancy outcomes among women with hyperglycaemia in pregnancy.