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Hybrid closed-loop (HCL) systems remain underexplored within aviation, and as atmospheric pressure changes can independently affect insulin pumps and continuous glucose monitoring readings, this preliminary study assessed the feasibility of HCL safety evaluation, in both fasting and post-prandial states, by using hypobaric chamber to simulate flights. Participants with type 1 diabetes and on HCL were studied: Medtronic Guardian 4-Medtronic 780G-SmartGuard ( n = 4), Dexcom G6-Omnipod DASH-Android APS ( n = 1), and Dexcom G6-Ypsomed Pump-CamAPS ( n = 1). Flight cabin pressures of 550 mmHg and 750 mmHg were simulated in a hypobaric chamber. Seven-hundred-50 glucose measurements were taken, with glucose levels demonstrating a stable decline to 4 mmol/L during fasting. To maintain a tight fasting and post-prandial glucose range across the different pressure settings, the HCL administered insulin as expected. While not demonstrating any apparent issues, repeating flight simulation protocol with other systems, examining longer flights, and undertaking larger, powered randomised controlled trials can confirm their safety in aviation.

Aims/hypothesis: The aim of this work was to examine the impact of hypoglycaemia on daily functioning among adults with type 1 diabetes or insulin-treated type 2 diabetes, using the novel Hypo-METRICS app., Methods: For 70 consecutive days, 594 adults (type 1 diabetes, n=274; type 2 diabetes, n=320) completed brief morning and evening Hypo-METRICS 'check-ins' about their experienced hypoglycaemia and daily functioning. Participants wore a blinded glucose sensor (i.e. data unavailable to the participants) for the study duration. Days and nights with or without person-reported hypoglycaemia (PRH) and/or sensor-detected hypoglycaemia (SDH) were compared using multilevel regression models., Results: Participants submitted a mean ± SD of 86.3±12.5% morning and 90.8±10.7% evening check-ins. For both types of diabetes, SDH alone had no significant associations with the changes in daily functioning scores. However, daytime and night-time PRH (with or without SDH) were significantly associated with worsening of energy levels, mood, cognitive functioning, negative affect and fear of hypoglycaemia later that day or while asleep. In addition, night-time PRH (with or without SDH) was significantly associated with worsening of sleep quality (type 1 and type 2 diabetes) and memory (type 2 diabetes). Further, daytime PRH (with or without SDH), was associated with worsening of fear of hyperglycaemia while asleep (type 1 diabetes), memory (type 1 and type 2 diabetes) and social functioning (type 2 diabetes)., Conclusions/interpretation: This prospective, real-world study reveals impact on several domains of daily functioning following PRH but not following SDH alone. These data suggest that the observed negative impact is mainly driven by subjective awareness of hypoglycaemia (i.e. PRH), through either symptoms or sensor alerts/readings and/or the need to take action to prevent or treat episodes., (© 2024. The Author(s).)

Introduction: This study examined associations between hypoglycemia awareness status and hypoglycemia symptoms reported in real-time using the novel Hypoglycaemia-MEasurement, ThResholds and ImpaCtS (Hypo-METRICS) smartphone application (app) among adults with insulin-treated type 1 (T1D) or type 2 diabetes (T2D). Methods: Adults who experienced at least one hypoglycemic episode in the previous 3 months were recruited to the Hypo-METRICS study. They prospectively reported hypoglycemia episodes using the app for 10 weeks. Any of eight hypoglycemia symptoms were considered present if intensity was rated between "A little bit" to "Very much" and absent if rated "Not at all." Associations between hypoglycemia awareness (as defined by Gold score) and hypoglycemia symptoms were modeled using mixed-effects binary logistic regression, adjusting for glucose monitoring method and diabetes duration. Results: Of 531 participants (48% T1D, 52% T2D), 45% were women, 91% white, and 59% used Flash or continuous glucose monitoring. Impaired awareness of hypoglycemia (IAH) was associated with lower odds of reporting autonomic symptoms than normal awareness of hypoglycemia (NAH) (T1D odds ratio [OR] 0.43 [95% confidence interval {CI} 0.25-0.73], P  = 0.002); T2D OR 0.51 [95% CI 0.26-0.99], P  = 0.048), with no differences in neuroglycopenic symptoms. In T1D, relative to NAH, IAH was associated with higher odds of reporting autonomic symptoms at a glucose concentration <54 than >70 mg/dL (OR 2.18 [95% CI 1.21-3.94], P  = 0.010). Conclusion: The Hypo-METRICS app is sensitive to differences in hypoglycemia symptoms according to hypoglycemia awareness in both diabetes types. Given its high ecological validity and low recall bias, the app may be a useful tool in research and clinical settings. The clinical trial registration number is NCT04304963.

Objective: The aim of this analysis was to assess glycemic control before and during the coronavirus disease (COVID-19) pandemic., Methods: Data from 64 (main analysis) and 80 (sensitivity analysis) people with type 1 diabetes (T1D) using intermittently scanned continuous glucose monitoring (isCGM) were investigated retrospectively. The baseline characteristics were collected from electronic medical records. The data were examined over three periods of three months each: from 16th of March 2019 until 16th of June 2019 (pre-pandemic), from 1st of December 2019 until 29th of February 2020 (pre-lockdown) and from 16th of March 2020 until 16th of June 2020 (lockdown 2020), representing the very beginning of the COVID-19 pandemic and the first Austrian-wide lockdown., Results: For the main analysis, 64 individuals with T1D (22 female, 42 male), who had a mean glycated hemoglobin (HbA1c) of 58.5 mmol/mol (51.0 to 69.3 mmol/mol) and a mean diabetes duration 13.5 years (5.5 to 22.0 years) were included in the analysis. The time in range (TIR [70-180mg/dL] ) was the highest percentage of measures within all three studied phases, but the lockdown 2020 phase delivered the best data in all these cases. Concerning the time below range (TBR [<70mg/dL] ) and the time above range (TAR [>180mg/dL] ), the lockdown 2020 phase also had the best values. Regarding the sensitivity analysis, 80 individuals with T1D (26 female, 54 male), who had a mean HbA1c of 57.5 mmol/mol (51.0 to 69.3 mmol/mol) and a mean diabetes duration of 12.5 years (5.5 to 20.7 years), were included. The TIR [70-180mg/dL] was also the highest percentage of measures within all three studied phases, with the lockdown 2020 phase also delivering the best data in all these cases. The TBR [<70mg/dL] and the TAR [>180mg/dL] underscored the data in the main analysis., Conclusion: Superior glycemic control, based on all parameters analyzed, was achieved during the first Austrian-wide lockdown compared to prior periods, which might be a result of reduced daily exertion or more time spent focusing on glycemic management.

Introduction: Nocturnal hypoglycemia is generally calculated between 00:00 and 06:00. However, those hours may not accurately reflect sleeping patterns and it is unknown whether this leads to bias. We therefore compared hypoglycemia rates while asleep with those of clock-based nocturnal hypoglycemia in adults with type 1 diabetes (T1D) or insulin-treated type 2 diabetes (T2D). Methods: Participants from the Hypo-METRICS study wore a blinded continuous glucose monitor and a Fitbit Charge 4 activity monitor for 10 weeks. They recorded details of episodes of hypoglycemia using a smartphone app. Sensor-detected hypoglycemia (SDH) and person-reported hypoglycemia (PRH) were categorized as nocturnal (00:00-06:00 h) versus diurnal and while asleep versus awake defined by Fitbit sleeping intervals. Paired-sample Wilcoxon tests were used to examine the differences in hypoglycemia rates. Results: A total of 574 participants [47% T1D, 45% women, 89% white, median (interquartile range) age 56 (45-66) years, and hemoglobin A1c 7.3% (6.8-8.0)] were included. Median sleep duration was 6.1 h (5.2-6.8), bedtime and waking time ∼23:30 and 07:30, respectively. There were higher median weekly rates of SDH and PRH while asleep than clock-based nocturnal SDH and PRH among people with T1D, especially for SDH <70 mg/dL (1.7 vs. 1.4, P  < 0.001). Higher weekly rates of SDH while asleep than nocturnal SDH were found among people with T2D, especially for SDH <70 mg/dL (0.8 vs. 0.7, P  < 0.001). Conclusion: Using 00:00 to 06:00 as a proxy for sleeping hours may underestimate hypoglycemia while asleep. Future hypoglycemia research should consider the use of sleep trackers to record sleep and reflect hypoglycemia while asleep more accurately. The trial registration number is NCT04304963.

Introduction: The aim of this study was to determine the acceptability and psychometric properties of the Hypo-METRICS (Hypoglycemia MEasurement, ThResholds and ImpaCtS) application (app): a novel tool designed to assess the direct impact of symptomatic and asymptomatic hypoglycemia on daily functioning in people with insulin-treated diabetes., Materials and Methods: 100 adults with type 1 diabetes mellitus (T1DM, n = 64) or insulin-treated type 2 diabetes mellitus (T2DM, n = 36) completed three daily 'check-ins' (morning, afternoon and evening) via the Hypo-METRICs app across 10 weeks, to respond to 29 unique questions about their subjective daily functioning. Questions addressed sleep quality, energy level, mood, affect, cognitive functioning, fear of hypoglycemia and hyperglycemia, social functioning, and work/productivity. Completion rates, structural validity, internal consistency, and test-retest reliability were explored. App responses were correlated with validated person-reported outcome measures to investigate convergent (rs>±0.3) and divergent (rs<±0.3) validity., Results: Participants' mean±SD age was 54±16 years, diabetes duration was 23±13 years, and most recent HbA1c was 56.6±9.8 mmol/mol. Participants submitted mean±SD 191±16 out of 210 possible 'check-ins' (91%). Structural validity was confirmed with multi-level confirmatory factor analysis showing good model fit on the adjusted model (Comparative Fit Index >0.95, Root-Mean-Square Error of Approximation <0.06, Standardized Root-Mean-square Residual<0.08). Scales had satisfactory internal consistency (all ω≥0.5), and high test-retest reliability (rs≥0.7). Convergent and divergent validity were demonstrated for most scales., Conclusion: High completion rates and satisfactory psychometric properties demonstrated that the Hypo-METRICS app is acceptable to adults with T1DM and T2DM, and a reliable and valid tool to explore the daily impact of hypoglycemia., Competing Interests: US works for Novo Nordisk A/S (the work for this manuscript was undertaken prior to this employment). UPB has served on advisory boards and received lecture fees from for Novo Nordisk and Sanofi. BDG has received research support from Novo Nordisk. SAA has served on advisory boards for Novo Nordisk and Medtronic and have spoken at educational events sponsored by Novo Nordisk and Sanofi. JKM is a member on the advisory board of Abbott Diabetes Care, Boehringer Ingelheim, Becton-Dickinson, Eli Lilly, Medtronic, Novo Nordisk A/S, Prediktor A/S, Roche Diabetes Care, Sanofi-Aventis and received speaker honoraria from Abbott Diabetes Care, AstraZeneca, Becton-Dickinson, Dexcom, Eli Lilly, MSD, Novo Nordisk A/S, Roche Diabetes Care, Sanofi, and Servier. JKM is a shareholder of decide Clinical Software GmbH. FP has received unrestricted funding for research from Novo Nordisk, Eli Lilly and Sanofi. PC has received personal fees from Abbott, Insulet, Medtronic, Novo Nordisk, Eli Lilly, Sanofi and Dexcom. This does not alter our adherence to PLOS ONE policies on sharing data and materials. The data underlying the results presented in the study are available from the Hypo-RESOLVE data repository for researchers who meet the criteria for access. Please contact Hypo-RESOLVE (chair of the publication committee Professor Stephanie Amiel or principal investigator Professor Pratik Choudhary) for further details: https://hypo-resolve.eu/contact, (Copyright: © 2023 Søholm et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Aim: To evaluate the efficacy and safety of basal-bolus insulin therapy in managing glycaemia during fasting periods in hospitalized patients with type 2 diabetes., Materials and Methods: We performed a post hoc analysis of two prospective, uncontrolled interventional trials that applied electronic decision support system-guided basal-bolus (meal-related and correction) insulin therapy. We searched for fasting periods (invasive or diagnostic procedures, medical condition) during inpatient stays. In a mixed model analysis, patients' glucose levels and insulin doses on days with regular food intake were compared with days with fasting periods., Results: Out of 249 patients, 115 patients (33.9% female, age 68.3 ± 10.3 years, diabetes duration 15.1 ± 10.9 years, body mass index 30.1 ± 5.4 kg/m 2 , HbA1c 69 ± 20 mmol/mol) had 194 days with fasting periods. Mean daily blood glucose (BG) was lower (modelled difference [ModDiff]: -0.5 ± 0.2 mmol/L, P = .006), and the proportion of glucose values within the target range (3.9-10.0 mmol/L) increased on days with fasting periods compared with days with regular food intake (ModDiff: +0.06 ± 0.02, P = .005). Glycaemic control on fasting days was driven by a reduction in daily bolus insulin doses (ModDiff: -11.0 ± 0.9 IU, P < .001), while basal insulin was similar (ModDiff: -1.1 ± 0.6 IU, P = .082) compared with non-fasting days. Regarding hypoglycaemic events (BG < 3.9 mmol/L), there was no difference between fasting and non-fasting days (χ 2 0.9% vs. 1.7%, P = .174)., Conclusions: When using well-titrated basal-bolus insulin therapy in hospitalized patients with type 2 diabetes, the basal insulin dose does not require adjustment during fasting periods to achieve safe glycaemic control, provided meal-related bolus insulin is omitted and correction bolus insulin is tailored to glucose levels., (© 2021 John Wiley & Sons Ltd.)

Continuous and flash glucose monitoring (GM) systems have been established in diabetes care. We compared the sensor performance of 3 commercially available GM systems. A total of 12 patients with type 1 diabetes were included in a single-centre, open-label study in which the sensor performance of the Abbott FreeStyle libre (Abbott), Dexcom G4 Platinum (Dexcom) and Medtronic MiniMed 640G (Medtronic) systems over 12 hours was compared during mimicked real-life conditions (meals, exercise, hypo- and hyperglycaemia). Sensor performance was determined by fulfilment of ISO 15197:2013 criteria, calculating mean absolute relative difference (MARD), and was also illustrated using Parkes error grid and Bland-Altman plots. Sensor performance during changes in metabolic variables (lactate, betahydroxybutyrate, glucagon, non-esterified-fatty-acids) was determined by Spearman's rank correlation coefficient testing. The systems fulfilled ISO 15197:2013 criteria by 73.2% (Abbott), 56.1% (Dexcom) and 52.0% (Medtronic). The MARDs ± standard deviation in the entire glycaemic range were 13.2% ± 10.9% (Abbott), 16.8% ± 12.3% (Dexcom) and 21.4% ± 17.6% (Medtronic), respectively. All sensors performed less accurately during hypoglycaemia and best during hyperglycaemia. We did not observe an influence of metabolic variables on sensor performance., (© 2017 John Wiley & Sons Ltd.)

Odor information is processed in spherical structures called glomeruli, which in all animals with differentiated olfactory systems are sites of densely spaced synaptic contacts between olfactory sensory axons and target central nervous system (CNS) neurons. Glomerulus development in the antennal (olfactory) lobe of the moth brain, which is initiated by the arrival of antennal receptor axons, requires interaction among three elements: glial cells, receptor axons, and their targets, the antennal-lobe neurons. Receptor axons form an array of protoglomeruli that become surrounded by glia and serve as a template for mature glomeruli. Previous experiments showed that when the number of glial cells is sharply reduced during development either by irradiation or by an anti-mitotic agent, receptor axons form protoglomeruli, but in the mature lobes, glomeruli are absent and central neurons lack the characteristic glomerular tufting of their arbors. The current investigation was conducted to determine which cellular events in the process of glomerulus formation are disrupted by severe reduction in glial-cell number. The branching patterns of receptor axons and antennal-lobe neurons were examined in animals that had been irradiated to produce glia-deficient antennal lobes at stages during which glomeruli normally would develop. We found that the receptor axons did form protoglomeruli, but that the protoglomeruli quickly disintegrated in glia-deficient antennal lobes; the receptor axons branched diffusely, except where several neighboring glia survived irradiation and together formed a wall of processes that appeared to block the passage of neuronal processes. Multi-glomerular antennal-lobe neurons never developed tufted arbors even at early stages. These results suggest that maintenance of protoglomeruli depends on the border of glia that forms around each protoglomerulus and that the subsequent tufting of antennal-lobe neurons depends on maintenance of the protoglomerular template during the period of dendritic growth.