Towards the standardisation of adult person-reported outcome domains in diabetes research: A Consensus Statement development panel.

Diabetes is unique among chronic diseases because clinical outcomes are intimately tied to how the person living with diabetes reacts to and implements treatment recommendations. It is further characterised by widespread social stigma, judgement and paternalism. This physical, social and psychological burden collectively influences self-management behaviours. It is widely recognised that the individual's perspective about the impact of trying to manage the disease and the burden that self-management confers must be addressed to achieve optimal health outcomes. Standardised, rigorous assessment of mental and behavioural health status, in interaction with physical health outcomes is crucial to aid understanding of person-reported outcomes (PROs). Whilst tempting to conceptualise PROs as an issue of perceived quality of life (QoL), in fact health-related QoL is multi-dimensional and covers indicators of physical or functional health status, psychological and social well-being. This complexity is illuminated by the large number of person reported outcome measures (PROMs) that have been developed across multiple psychosocial domains. Often measures are used inappropriately or because they have been used in the scientific literature rather than based on methodological or outcome assessment rigour. Given the broad nature of psychosocial functioning/mental health, it is important to broadly define PROs that are evaluated in the context of therapeutic interventions, real-life and observational studies. This report summarises the central themes and lessons derived in the assessment and use of PROMs amongst adults with diabetes. Effective assessment of PROMs routinely in clinical research is crucial to understanding the true impact of any intervention. Selecting appropriate measures, relevant to the specific factors of PROs important in the research study will provide valuable data alongside physical health data.

Associations of clinical, psychological, and sociodemographic characteristics and ecological momentary assessment completion in the 10-week Hypo-METRICS study: Hypoglycaemia MEasurements ThResholds and ImpaCtS.

INTRODUCTION: Reporting of hypoglycaemia and its impact in clinical studies is often retrospective and subject to recall bias. We developed the Hypo-METRICS app to measure the daily physical, psychological, and social impact of hypoglycaemia in adults with type 1 and insulin-treated type 2 diabetes in real-time using ecological momentary assessment (EMA). To help assess its utility, we aimed to determine Hypo-METRICS app completion rates and factors associated with completion. METHODS: Adults with diabetes recruited into the Hypo-METRICS study were given validated patient-reported outcome measures (PROMs) at baseline. Over 10 weeks, they wore a blinded continuous glucose monitor (CGM), and were asked to complete three daily EMAs about hypoglycaemia and aspects of daily functioning, and two weekly sleep and productivity PROMs on the bespoke Hypo-METRICS app. We conducted linear regression to determine factors associated with app engagement, assessed by EMA and PROM completion rates and CGM metrics. RESULTS: In 602 participants (55% men; 54% type 2 diabetes; median(IQR) age 56 (45-66) years; diabetes duration 19 (11-27) years; HbA1c 57 (51-65) mmol/mol), median(IQR) overall app completion rate was 91 (84-96)%, ranging from 90 (81-96)%, 89 (80-94)% and 94(87-97)% for morning, afternoon and evening check-ins, respectively. Older age, routine CGM use, greater time below 3.0 mmol/L, and active sensor time were positively associated with app completion. DISCUSSION: High app completion across all app domains and participant characteristics indicates the Hypo-METRICS app is an acceptable research tool for collecting detailed data on hypoglycaemia frequency and impact in real-time.

Association Between Treatment Adherence and Continuous Glucose Monitoring Outcomes in People With Diabetes Using Smart Insulin Pens in a Real-World Setting.

OBJECTIVE: To evaluate the association of insulin injection adherence, smart insulin pen engagement, and glycemic control using real-world data from 16 countries from adults self-administering basal insulin degludec and bolus insulin with a smart insulin pen (NovoPen 6 or NovoPen Echo Plus) alongside continuous glucose monitoring (CGM). RESEARCH DESIGN AND METHODS: Data were aggregated over 14-day periods. Treatment adherence was defined according to the number of missed basal and missed bolus insulin doses and smart pen engagement according to the number of days with data uploads. RESULTS: Data from 3,945 adults, including 25,157 14-day periods with ≥70% CGM coverage, were analyzed. On average, 0.2 basal and 6.0 bolus insulin doses were missed over 14 days. The estimated probability of missing at least one basal insulin dose over a 14-day period was 17.6% (95% CI 16.5, 18.7). Missing one basal or bolus insulin dose per 14 days was associated with a significant decrease in percentage of time with glucose levels in range (TIR) (3.9-10.0 mmol/L), of -2.8% (95% CI -3.7, -1.8) and -1.7% (-1.8, -1.6), respectively; therefore, missing two basal or four bolus doses would decrease TIR by >5%. Smart pen engagement was associated positively with glycemic outcomes. CONCLUSIONS: This combined analysis of real-world smart pen and CGM data showed that missing two basal or four bolus insulin doses over a 14-day period would be associated with a clinically relevant decrease in TIR. Smart insulin pens provide valuable insights into treatment injection behaviors.

A Three-Arm Randomized Controlled Study Comparing Patient-Reported Outcomes in People With Type 1 Diabetes Using Continuous Subcutaneous Insulin Infusion or Multiple Daily Injections.

BACKGROUND: The aim of this study was to compare patient-reported outcomes (PROs) in people with type 1 diabetes using either continuous subcutaneous insulin infusion (CSII) with two different insulin patch pumps or multiple daily injections (MDIs). MATERIALS AND METHODS: In this randomized three-arm study, people with type 1 diabetes on MDI therapy were included and used either MDI, the Accu-Chek Solo micropump system (Solo) or Omnipod for 26 weeks. From weeks 26 to 39, all participants used CSII with Solo. Patient-reported outcomes were assessed using the diabetes technology questionnaire (DTQ); in addition, HbA1c values were measured. RESULTS: Overall, 181 participants were randomized (61 MDI arm, 62 Solo arm, 58 Omnipod arm) and 142 completed the study. After 26 weeks in the study, the DTQ "change" score in the Solo group (105.9 [100.6-111.2]; baseline-adjusted mean [95% confidence interval]) was significantly higher than in the MDI group (94.8 [89.6-100.0]) (P = .001). The comparison between the Solo group (105.1 [99.1-111.1]) and the Omnipod group (108.7 [103.1-114.4]) showed no significant differences (P = .382). HbA1c increased by 0.2% ± 0.7% in the MDI group and decreased in both pump groups (Solo group -0.2% ± 0.8% and Omnipod group -0.1% ± 0.8%). Differences in HbA1c between the Solo group and the MDI group were significant (P = .009), but not between the Solo group and the Omnipod group (P = .896). CONCLUSIONS: This study showed that switching from MDI to CSII improves both psychosocial well-being and physiological outcomes. Furthermore, there were no substantial differences between the established and the recently released patch pump. Trial registration at www.clinicaltrials.gov is NCT03478969.

Associations Between Hypoglycemia Awareness Status and Symptoms of Hypoglycemia Among Adults with Type 1 or Insulin-Treated Type 2 Diabetes Using the Hypo-METRICS Smartphone Application.

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.

Retrospective Comparison of Commercially Available Automated Insulin Delivery With Open-Source Automated Insulin Delivery Systems in Type 1 Diabetes.

BACKGROUND: Automated insulin delivery (AID) systems have shown to improve glycemic control in a range of populations and settings. At the start of this study, only one commercial AID system had entered the Austrian market (MiniMed 670G, Medtronic). However, there is an ever-growing community of people living with type 1 diabetes (PWT1D) using open-source (OS) AID systems. MATERIALS AND METHODS: A total of 144 PWT1D who used either the MiniMed 670G (670G) or OS-AID systems routinely for a period of at least three to a maximum of six months, between February 18, 2020 and January 15, 2023, were retrospectively analyzed (116 670G aged from 2.6 to 71.8 years and 28 OS-AID aged from 3.4 to 53.5 years). The goal is to evaluate and compare the quality of glycemic control of commercially available AID and OS-AID systems and to present all data by an in-depth descriptive analysis of the population. No statistical tests were performed. RESULTS: The PWT1D using OS-AID systems spent more time in range (TIR)70-180 mg/dL (81.7% vs 73.9%), less time above range (TAR)181-250 mg/dL (11.1% vs 19.6%), less TAR>250 mg/dL (2.5% vs 4.3%), and more time below range (TBR)54-69 mg/dL (2.2% vs 1.7%) than PWT1D using the 670G system. The TBR<54 mg/dL was comparable in both groups (0.3% vs 0.4%). In the OS-AID group, median glucose level and glycated hemoglobin (HbA1c) were lower than in the 670G system group (130 vs 150 mg/dL; 6.2% vs 7.0%). CONCLUSION: In conclusion, both groups were able to achieve satisfactory glycemic outcomes independent of age, gender, and diabetes duration. However, the PWT1D using OS-AID systems attained an even better glycemic control with no clinical safety concerns.

Risks in the analogue and digitally-supported medication process and potential solutions to increase patient safety in the hospital: A mixed methods study.

BACKGROUND: In hospital medication errors are common. Our aim was to investigate risks of the analogue and digitally-supported medication process and any potential solutions. METHODS: A mixed methods study including a structured literature search and online questionnaires based on the Delphi method was conducted. First, all risks were structured into main and sub-risks and second, risks were grouped into risk clusters. Third, healthcare experts assessed risk clusters regarding their likelihood of occurrence their possible impact on patient safety. Experts were also asked to estimate the potential for digital solutions and solutions that strengthen the competence of healthcare professionals. RESULTS: Overall, 160 main risks and 542 sub-risks were identified. Main risks were grouped into 43 risk clusters. 33 healthcare experts (56% female, 50% with >20 years professional-experience) ranked the likelihood of occurrence and the impact on patient safety in the top 15 risk clusters regarding the process steps: admission (n = 4), prescribing (n = 3), verifying (n = 1), preparing/dispensing (n = 3), administering (n = 1), discharge (n = 1), healthcare professional competence (n = 1), and patient adherence (n = 1). 28 healthcare experts (64% female, 43% with >20 years professional-experience) mostly suggested awareness building and training, strengthened networking, and involvement of pharmacists at point-of-care as likely solutions to strengthen healthcare professional competence. For digital solutions they primarily suggested a digital medication list, digital warning systems, barcode-technology, and digital support in integrated care. CONCLUSIONS: The medication process holds a multitude of potential risks, in both the analogue and the digital medication process. Different solutions to strengthen healthcare professional competence and in the area of digitalization were identified that could help increase patient safety and minimize possible errors.

Postprandial Glucose Excursions with Ultra-Rapid Insulin Analogs in Hybrid Closed-Loop Therapy for Adults with Type 1 Diabetes.

Objective: To evaluate postprandial glucose control when applying (1) faster-acting insulin aspart (Fiasp) compared to insulin aspart and (2) ultra-rapid insulin lispro (Lyumjev) compared to insulin lispro using the CamAPS FX hybrid closed-loop algorithm. Research Design and Methods: We undertook a secondary analysis of postprandial glucose excursions from two double-blind, randomized, crossover hybrid closed-loop studies contrasting Fiasp to standard insulin aspart, and Lyumjev to standard insulin lispro. Endpoints included incremental area under curve (iAUC)-2h, iAUC-4h, 4 h postprandial time in target range, time above range, and time below range. It was approved by independent research ethics committees. Results: Two trials with 8 weeks of data from 51 adults with type 1 diabetes were analyzed and 7137 eligible meals were included. During Lyumjev compared with insulin lispro, iAUC-2h and iAUC-4h were significantly decreased following breakfast (mean difference 92 mmol/L per 2 h (95% confidence interval [CI]: 56 to 127); P < 0.001 and 151 mmol/L per 4 h (95% CI: 74 to 229); P < 0.001, respectively) and the evening meal (P < 0.001 and P = 0.011, respectively). Mean time in target range (3.9-10.0 mmol/L) for 4 h postprandially significantly increased during Lyumjev with a mean difference of 6.7 percentage points (95% CI: 3.3 to 10) and 5.7 percentage points (95% CI: 1.4 to 9.9) for breakfast and evening meal, respectively. In contrast, there were no significant differences in iAUC-2h, iAUC-4h, and the other measures of postprandial glucose control between insulin aspart and Fiasp during breakfast, lunch, and evening meal (P > 0.05). Conclusion: The use of Lyumjev with CamAPS FX closed-loop system improved postprandial glucose excursions compared with insulin lispro, while the use of Fiasp did not provide any advantage compared with insulin aspart. Clinical Trial Registration numbers: NCT04055480, NCT05257460.

A Comparison of the Rates of Clock-Based Nocturnal Hypoglycemia and Hypoglycemia While Asleep Among People Living with Diabetes: Findings from the Hypo-METRICS Study.

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.

Comparator Data Characteristics and Testing Procedures for the Clinical Performance Evaluation of Continuous Glucose Monitoring Systems.

Comparing the performance of different continuous glucose monitoring (CGM) systems is challenging due to the lack of comprehensive guidelines for clinical study design. In particular, the absence of concise requirements for the distribution of comparator (reference) blood glucose (BG) concentrations and their rate of change (RoC) that are used to evaluate CGM performance, impairs comparability. For this article, several experts in the field of CGM performance testing have collaborated to propose characteristics of the distribution of comparator measurements that should be collected during CGM performance testing. Specifically, it is proposed that at least 7.5% of comparator BG concentrations are <70 mg/dL (3.9 mmol/L) and >300 mg/dL (16.7 mmol/L), respectively, and that at least 7.5% of BG-RoC combinations indicate fast BG changes with impending hypo- or hyperglycemia, respectively. These proposed characteristics of the comparator data can facilitate the harmonization of testing conditions across different studies and CGM systems and ensure that the most relevant scenarios representing real-life situations are established during performance testing. In addition, a study protocol and testing procedure for the manipulation of glucose levels are suggested that enable the collection of comparator data with these characteristics. This work is an important step toward establishing a future standard for the performance evaluation of CGM systems.

Relationship Between Lipohypertrophy, Glycemic Control, and Insulin Dosing: A Systematic Meta-Analysis.

Background: Lipohypertrophy is a common complication in patients with diabetes receiving insulin therapy. There is a lack of consensus regarding how much lipohypertrophy affects diabetes management. Our study aimed to assess the potential correlation between lipohypertrophy and glycemic control, as well as insulin dosing in patients with diabetes. Methods: We performed a systematic review followed by a meta-analysis to collect data about glycemic control and insulin dosing in diabetic patients with and without lipohypertrophy. To identify relevant studies published in English, we searched medical databases (MEDLINE/PubMed, Embase, and CENTRAL) from 1990 to January 20, 2023. An additional hand-search of references was performed to retrieve publications not indexed in medical databases. Results of meta-analyses were presented either as prevalence odds ratios (pORs) or mean differences (MDs) with 95% confidence intervals (95% CIs). This study was registered on PROSPERO (CRD42023393103). Results: Of the 5540 records and 240 full-text articles screened, 37 studies fulfilled the prespecified inclusion criteria. Performed meta-analyses showed that patients with lipohypertrophy compared with those without lipohypertrophy were more likely to experience unexplained hypoglycemia (pOR [95% CI] = 6.98 [3.30-14.77]), overall hypoglycemia (pOR [95% CI] = 6.65 [1.37-32.36]), and glycemic variability (pOR [95% CI] = 5.24 [2.68-10.23]). Patients with lipohypertrophy also had higher HbA1c (MD [95% CI] = 0.55 [0.23-0.87] %), and increased daily insulin consumption (MD [95% CI] = 7.68 IU [5.31-10.06]). Conclusions: These results suggest that overall glycemic control is worse in patients with lipohypertrophy than in those without this condition.

A narrative commentary about interoperability in medical devices and data used in diabetes therapy from an academic EU/UK/US perspective.

People living with diabetes have many medical devices available to assist with disease management. A critical aspect that must be considered is how systems for continuous glucose monitoring and insulin pumps communicate with each other and how the data generated by these devices can be downloaded, integrated, presented and used. Not only is interoperability associated with practical challenges, but also devices must adhere to all aspects of regulatory and legal frameworks. Key issues around interoperability in terms of data ownership, privacy and the limitations of interoperability include where the responsibility/liability for device and data interoperability lies and the need for standard data-sharing protocols to allow the seamless integration of data from different sources. There is a need for standardised protocols for the open and transparent handling of data and secure integration of data into electronic health records. Here, we discuss the current status of interoperability in medical devices and data used in diabetes therapy, as well as regulatory and legal issues surrounding both device and data interoperability, focusing on Europe (including the UK) and the USA. We also discuss a potential future landscape in which a clear and transparent framework for interoperability and data handling also fulfils the needs of people living with diabetes and healthcare professionals.

Combining Glucose Monitoring and Insulin Infusion in an Integrated Device: A Narrative Review of Challenges and Proposed Solutions.

The introduction of automated insulin delivery (AID) systems has enabled increasing numbers of individuals with type 1 diabetes (T1D) to improve their glycemic control largely. However, use of AID systems is limited due to their complexity and costs associated. The user must wear both a continuously monitoring glucose system and an insulin infusion pump. The glucose sensor and the insulin catheter must be inserted at two different body sites using different insertion devices. In addition, the user must pair and manage the different systems. These communicate with the AID software implemented on the pump or on a third device such as a dedicated display device or smart phone application. These components might be developed and commercialized by different manufacturers, which in turn can cause difficulties for patients seeking technical support. A possible solution to these challenges would be to integrate the glucose sensor and insulin catheter into a single device. This would allow the glucose sensor and insulin catheter to be inserted simultaneously, eliminating the need for pairing, and simplifying system management. In recent years, different technologies have been developed and evaluated in clinical investigations that combine the glucose sensor and the insulin catheter in one platform. The consistent finding of all these studies is that integration has no adverse effect on insulin infusion and glucose measurements provided that certain conditions are met. In this review, we discuss the perceived challenges of such an approach and discuss possible solutions that have been proposed.

Assessing the Content Validity, Acceptability, and Feasibility of the Hypo-METRICS App: Survey and Interview Study.

BACKGROUND: The Hypoglycaemia - MEasurement, ThResholds and ImpaCtS (Hypo-METRICS) smartphone app was developed to investigate the impact of hypoglycemia on daily functioning in adults with type 1 diabetes mellitus or insulin-treated type 2 diabetes mellitus. The app uses ecological momentary assessments, thereby minimizing recall bias and maximizing ecological validity. It was used in the Hypo-METRICS study, a European multicenter observational study wherein participants wore a blinded continuous glucose monitoring device and completed the app assessments 3 times daily for 70 days. OBJECTIVE: The 3 aims of the study were to explore the content validity of the app, the acceptability and feasibility of using the app for the duration of the Hypo-METRICS study, and suggestions for future versions of the app. METHODS: Participants who had completed the 70-day Hypo-METRICS study in the United Kingdom were invited to participate in a brief web-based survey and an interview (approximately 1h) to explore their experiences with the app during the Hypo-METRICS study. Thematic analysis of the qualitative data was conducted using both deductive and inductive methods. RESULTS: A total of 18 adults with diabetes (type 1 diabetes: n=10, 56%; 5/10, 50% female; mean age 47, SD 16 years; type 2 diabetes: n=8, 44%; 2/8, 25% female; mean age 61, SD 9 years) filled out the survey and were interviewed. In exploring content validity, participants overall described the Hypo-METRICS app as relevant, understandable, and comprehensive. In total, 3 themes were derived: hypoglycemia symptoms and experiences are idiosyncratic; it was easy to select ratings on the app, but day-to-day changes were perceived as minimal; and instructions could be improved. Participants offered suggestions for changes or additional questions and functions that could increase engagement and improve content (such as providing more examples with the questions). In exploring acceptability and feasibility, 5 themes were derived: helping science and people with diabetes; easy to fit in, but more flexibility wanted; hypoglycemia delaying responses and increasing completion time; design, functionality, and customizability of the app; and limited change in awareness of symptoms and impact. Participants described using the app as a positive experience overall and as having a possible, although limited, intervention effect in terms of both hypoglycemia awareness and personal impact. CONCLUSIONS: The Hypo-METRICS app shows promise as a new research tool to assess the impact of hypoglycemia on an individual's daily functioning. Despite suggested improvements, participants' responses indicated that the app has satisfactory content validity, overall fits in with everyday life, and is suitable for a 10-week research study. Although developed for research purposes, real-time assessments may have clinical value for monitoring and reviewing hypoglycemia symptom awareness and personal impact.

Reply to Freckmann et al. Comment on "Hochfellner et al. Accuracy Assessment of the GlucoMen® Day CGM System in Individuals with Type 1 Diabetes: A Pilot Study. Biosensors 2022, 12, 106".

We thank Dr. Freckmann et al. [...].

Continuous Glucose Monitoring by Insulin-Treated Pilots Flying Commercial Aircraft Within the ARA.MED.330 Diabetes Protocol: A Preliminary Feasibility Study.

Background and Aims: A preliminary study compared the use of continuous glucose monitoring (CGM) with the use of self-monitored blood glucose (SMBG) by aircraft pilots with insulin-treated diabetes in the United Kingdom, Ireland, and Austria, certified to fly commercial aircraft within the European Aviation Safety Agency ARA.MED.330 protocol. Methods: SMBG and simultaneous interstitial glucose measurements using CGM (Dexcom G6®) were recorded during pre- and in-flight periods. Results: Eight male pilots (seven with type 1 diabetes and one with type 3c diabetes), median age of 48.5 years and median diabetes duration of 11.5 years, participated. The correlation coefficient (R) between 874 contemporaneously recorded SMBG and CGM values was 0.843, P < 0.001. The mean glucose concentration was 8.78 mmol/L (standard deviation [SD] 0.67) using SMBG compared with 8.71 mmol/L (SD 0.85) recorded using CGM. The mean absolute relative difference was 9.39% (SD 3.12). Conclusions: CGM using Dexcom G6 systems is a credible alternative to SMBG for monitoring glucose levels when insulin-treated pilots fly commercial aircraft. The study was registered with Clinical Trials.gov NCT04395378.

Time Spent in Hypoglycemia According to Age and Time of Day: Observations During Closed-Loop Insulin Delivery.

Objective: We aimed to assess whether percentage of time spent in hypoglycemia during closed-loop insulin delivery differs by age group and time of day. Methods: We retrospectively analyzed data from hybrid closed-loop studies involving young children (2-7 years), children and adolescents (8-18 years), adults (19-59 years), and older adults (≥60 years) with type 1 diabetes. Main outcome was time spent in hypoglycemia <3.9 mmol/L (<70 mg/dL). Eight weeks of data for 88 participants were analyzed. Results: Median time spent in hypoglycemia over the 24-h period was highest in children and adolescents (4.4% [interquartile range 2.4-5.0]) and very young children (4.0% [3.4-5.2]), followed by adults (2.7% [1.7-4.0]), and older adults (1.8% [1.2-2.2]); P < 0.001 for difference between age groups. Time spent in hypoglycemia during nighttime (midnight-05:59) was lower than during daytime (06:00-23:59) across all age groups. Conclusion: Time in hypoglycemia was highest in the pediatric age group during closed-loop insulin delivery. Hypoglycemia burden was lowest overnight across all age groups.

Perioperative Insulin Regimens in Patients With Insulin-Treated Type 2 Diabetes Mellitus Hospitalized for a Short Time for Minor Eye Surgery.

BACKGROUND: Elective surgery in patients with insulin-treated type 2 diabetes mellitus (T2D) and the admission period in the hospital, comprise a distinctive and challenging situation for physicians, nurses, as well as for the patients themselves. There is a lack of widely accepted evidence-based and standardized approach of care in regard to perioperative management of patients with insulin-treated T2D. METHODS: The main purpose of this proof-of-concept study was to investigate whether a standardized insulin and meal regimen on the day of surgery leads to a better management of diabetes in terms of blood glucose (BG) levels. Two different insulin and meal regimens-group A with half of insulin dose given with a standardized postoperative meal and group B with a custom preoperative breakfast and full insulin dose-were compared with Group C with routine care (no meal and no insulin injection on the day of surgery). Each group consisted of 12 to 15 patients. BG measurements were performed pre- and immediately postoperatively, before meals and at bedtime. RESULTS: Both standardized and well-defined insulin and meal regimens resulted in better average BG levels in the perioperative period, especially in the morning after the surgery. CONCLUSIONS: In this study, we observed that a standardized perioperative insulin regimen efficiently lowered postoperative BG levels. Providing a custom breakfast and a full insulin dose resulted in lower postoperative BG levels. These approaches were not associated with an increase in hypoglycemic events. Physicians and nursing staff gave positive feedback to the structured and well-defined approaches.

[Antihyperglycemic treatment guidelines for diabetes mellitus type 2 (Update 2023)]. / Antihyperglykämische Therapie bei Diabetes mellitus Typ 2 (Update 2023).

Hyperglycemia significantly contributes to complications in patients with diabetes mellitus. While lifestyle interventions remain cornerstones of disease prevention and treatment, most patients with type 2 diabetes will eventually require pharmacotherapy for glycemic control. The definition of individual targets regarding optimal therapeutic efficacy and safety as well as cardiovascular effects is of great importance. In this guideline we present the most current evidence-based best clinical practice data for healthcare professionals.