Using Artificial Intelligence to Improve the Accuracy of a Wrist-Worn, Noninvasive Glucose Monitor: A Pilot Study

BACKGROUND

Self-monitoring of glucose is important to the successful management of diabetes; however, existing monitoring methods require a degree of invasive measurement which can be unpleasant for users. This study investigates the accuracy of a noninvasive glucose monitoring system that analyses spectral variations in microwave signals.

METHODS

An open-label, pilot design study was conducted with four cohorts (N = 5/cohort). In each session, a dial-resonating sensor (DRS) attached to the wrist automatically collected data every 60 seconds, with a novel artificial intelligence (AI) model converting signal resonance output to a glucose prediction. Plasma glucose was measured in venous blood samples every 5 minutes for Cohorts 1 to 3 and every 10 minutes for Cohort 4. Accuracy was evaluated by calculating the mean absolute relative difference (MARD) between the DRS and plasma glucose values.

RESULTS

Accurate plasma glucose predictions were obtained across all four cohorts using a random sampling procedure applied to the full four-cohort data set, with an average MARD of 10.3%. A statistical analysis demonstrates the quality of these predictions, with a surveillance error grid (SEG) plot indicating no data pairs falling into the high-risk zones.

CONCLUSIONS

These findings show that MARD values approaching accuracies comparable to current commercial alternatives can be obtained from a multiparticipant pilot study with the application of AI. Microwave biosensors and AI models show promise for improving the accuracy and convenience of glucose monitoring systems for people with diabetes.

Tailored Meal-Type Food Provision for Diabetes Patients Can Improve Routine Blood Glucose Management in Patients with Type 2 Diabetes: A Crossover Study

This study aimed to determine whether patients with type 2 diabetes can benefit from a meal plan designed based on diabetes management guidelines to improve blood glucose levels. Participants were divided into intervention and control groups. The intervention group consumed a diabetic diet for 2 weeks, while the control group consumed their normal diet. After 2 weeks, the groups switched their dietary regimens. The participants' demographic and clinical characteristics were evaluated, including factors such as blood pressure, blood lipid levels, weight and waist circumference, blood glucose levels (self-monitored and continuously monitored), nutritional status, and blood-based markers of nutrient intake. The dietary intervention group improved waist circumference, body fat percentage, low-density lipoprotein cholesterol, triglyceride levels, and glucose. The energy composition ratio of carbohydrates and proteins changed favorably, and sugar intake decreased. In addition, the proportion of continuous glucose monitoring readings within the range of 180-250 mg/dL was relatively lower in the intervention group than that of the control group. Meals designed based on diabetes management guidelines can improve clinical factors, including stable blood glucose levels in daily life, significantly decrease the carbohydrate energy ratio, and increase the protein energy ratio. This study can help determine the role of dietary interventions in diabetes management and outcomes.

A low-glucose eating pattern is associated with improvements in glycemic variability among women at risk for postmenopausal breast cancer: an exploratory analysis

Background

High glycemic variability (GV) is a biomarker of cancer risk, even in the absence of diabetes. The emerging concept of chrononutrition suggests that modifying meal timing can favorably impact metabolic risk factors linked to diet-related chronic disease, including breast cancer. Here, we examined the potential of eating when glucose levels are near personalized fasting thresholds (low-glucose eating, LGE), a novel form of timed-eating, to reduce GV in women without diabetes, who are at risk for postmenopausal breast cancer.

Methods

In this exploratory analysis of our 16-week weight loss randomized controlled trial, we included 17 non-Hispanic, white, postmenopausal women (average age = 60.7 ± 5.8 years, BMI = 34.5 ± 6.1 kg/m2, HbA1c = 5.7 ± 0.3%). Participants were those who, as part of the parent study, provided 3-7 days of blinded, continuous glucose monitoring data and image-assisted, timestamped food records at weeks 0 and 16. Pearson's correlation and multivariate regression were used to assess associations between LGE and GV, controlling for concurrent weight changes.

Results

Increases in LGE were associated with multiple unfavorable measures of GV including reductions in CGM glucose mean, CONGA, LI, J-Index, HBGI, ADDR, and time spent in a severe GV pattern (r = -0.81 to -0.49; ps < 0.044) and with increases in favorable measures of GV including M-value and LBGI (r = 0.59, 0.62; ps < 0.013). These associations remained significant after adjusting for weight changes.

Conclusion

Low-glucose eating is associated with improvements in glycemic variability, independent of concurrent weight reductions, suggesting it may be beneficial for GV-related disease prevention. Further research in a larger, more diverse sample with poor metabolic health is warranted.Clinical trial registration: ClinicalTrials.gov, NCT03546972.

Error traps in the perioperative management of children with type 1 diabetes

Patients with type 1 diabetes mellitus (T1D) require insulin administration at all times to maintain euglycemia and metabolic stability. Insulin administration in the perioperative period is complicated by fasting requirements and perioperative stressors that can change the patient's insulin needs. In addition, many anesthesia providers are not familiar with insulin dosing strategies and technology, such as insulin pumps and continuous glucose monitors (CGMs), that are commonly used by patients with T1D. Errors in perioperative insulin administration can lead to hypoglycemia, hyperglycemia, and diabetic ketoacidosis. This article reviews common errors of associated with the perioperative management of patients with T1D, including failure to assess and coordinate patient care preoperatively; failure to understand diabetes management and technology; failure to monitor blood glucose and recognize dysglycemia; and failure to appropriately administer basal insulin.

Correlation between time on target and glycated hemoglobin in people with diabetes mellitus: systematic review

to analyze the correlation between time on target and glycated hemoglobin in people living with diabetes mellitus and carrying out continuous blood glucose monitoring or self-monitoring of capillary blood glucose.

systematic review of etiology and risk based on JBI guidelines and reported according to Preferred Reporting Items for Systematic Reviews and Meta- Analyses, covering six databases and grey literature. The sample included 16 studies and methodological quality was assessed using JBI tools. Protocol registered in the Open Science Framework, available at https://doi.org/10.17605/OSF.IO/NKMZB.

time on target (70-180 mg/dl) showed a negative correlation with glycated hemoglobin, while time above target (>180 mg/dl) showed a positive correlation. Correlation coefficients ranged between -0.310 and -0.869 for time on target, and between 0.66 and 0.934 for time above target. A study was carried out on a population that performed self-monitoring.

there is a statistically significant correlation between time on target and time above target with glycated hemoglobin. The higher the proportion in the adequate glycemic range, the closer to or less than 7% the glycated hemoglobin will be. More studies are needed to evaluate this metric with data from self-monitoring of blood glucose.

Knowledge, Attitude and Practice of Patients with Gestational Diabetes Mellitus Regarding Gestational Diabetes Mellitus: A Cross-Sectional Study

Introduction

Self-monitoring of blood glucose levels and changes in diet and lifestyle play important roles in the management of gestational diabetes mellitus (GDM).

Methods

This cross-sectional study enrolled patients with GDM at Hangzhou Women's Hospital, China, between September 1, 2022, and October 26, 2022. A questionnaire was designed that included the following dimensions: demographic/clinical information, knowledge, attitude and practice. Correlations between knowledge, attitude and practice scores were evaluated using Spearman correlation analysis. Factors associated with practice score ≥14/16 were identified using multivariate logistic regression.

Results

The analysis included 499 women with GDM and a mean age of 31.22±3.89 years. The average knowledge, attitude and practice score were 11.55±3.04, 34.23±4.06 and 10.7±2.87 points, respectively. Knowledge score was positively correlated with attitude score (r=0.318, P<0.001) and practice score (r=0.351, P<0.001); attitude and practice scores were also positively correlated (r=0.209, P<0.001). Multivariate analysis identified higher knowledge score (odds ratio [OR], 1.138; 95% confidence interval [95% CI], 1.042-1.244; P=0.004) and higher attitude score (OR, 1.137; 95% CI, 1.060-1.219; P<0.001) as independently associated with good practice (ie, practice score ≥14 points).

Conclusion

The results provide important insights into the knowledge, attitudes and practices of women with GDM in China regarding GDM and its management. These findings may facilitate the development and implementation of education and training programs to improve the self-management of GDM by women in China.

Exploring the Impact of Dawn Phenomenon on Glucose-Guided Eating Thresholds in Individuals With Type 2 Diabetes Using Continuous Glucose Monitoring: Observational Study

BACKGROUND

Glucose-guided eating (GGE) improves metabolic markers of chronic disease risk, including insulin resistance, in adults without diabetes. GGE is a timed eating paradigm that relies on experiencing feelings of hunger and having a preprandial glucose level below a personalized threshold computed from 2 consecutive morning fasting glucose levels. The dawn phenomenon (DP), which results in elevated morning preprandial glucose levels, could cause typically derived GGE thresholds to be unacceptable or ineffective among people with type 2 diabetes (T2DM).

OBJECTIVE

The aim of this study is to quantify the incidence and day-to-day variability in the magnitude of DP and examine its effect on morning preprandial glucose levels as a preliminary test of the feasibility of GGE in adults with T2DM.

METHODS

Study participants wore a single-blinded Dexcom G6 Pro continuous glucose monitoring (CGM) system for up to 10 days. First and last eating times and any overnight eating were reported using daily surveys over the study duration. DP was expressed as a dichotomous variable at the day level (DP day vs non-DP day) and as a continuous variable reflecting the percent of days DP was experienced on a valid day. A valid day was defined as having no reported overnight eating (between midnight and 6 AM). ∂ Glucose was computed as the difference in nocturnal glucose nadir (between midnight and 6 AM) to morning preprandial glucose levels. ∂ Glucose ≥20 mg/dL constituted a DP day. Using multilevel modeling, we examined the between- and within-person effects of DP on morning preprandial glucose and the effect of evening eating times on DP.

RESULTS

In total, 21 adults (59% female; 13/21, 62%) with non-insulin-treated T2DM wore a CGM for an average of 10.5 (SD 1.1) days. Twenty out of 21 participants (95%) experienced DP for at least 1 day, with an average of 51% of days (SD 27.2; range 0%-100%). The mean ∂ glucose was 23.7 (SD 13.2) mg/dL. People who experience DP more frequently had a morning preprandial glucose level that was 54.1 (95% CI 17.0-83.9; P<.001) mg/dL higher than those who experienced DP less frequently. For within-person effect, morning preprandial glucose levels were 12.1 (95% CI 6.3-17.8; P=.008) mg/dL higher on a DP day than on a non-DP day. The association between ∂ glucose and preprandial glucose levels was 0.50 (95% CI 0.37-0.60; P<.001). There was no effect of the last eating time on DP.

CONCLUSIONS

DP was experienced by most study participants regardless of last eating times. The magnitude of the within-person effect of DP on morning preprandial glucose levels was meaningful in the context of GGE. Alternative approaches for determining acceptable and effective GGE thresholds for people with T2DM should be explored and evaluated.

Implementation of flash glucose monitoring in four pediatric diabetes clinics: controlled before and after study to produce real-world evidence of patient benefit

AIMS

To assess the real-world evidence for flash glucose monitoring (Abbott FreeStyle Libre) for children with type 1 diabetes in terms of glucose control, secondary healthcare resources and costs.

RESEARCH DESIGN AND METHODS

We conducted a controlled before and after study (approximately 12 months before and after) using routinely collected health record data on children who start using flash monitors and a control population of children with self-monitoring of blood glucose (SMBG). Our population-based sample of eligible individuals using flash monitoring (n=114) and controls (n=80) aged between 4 and 18 years was drawn from four paediatric diabetes clinics (secondary care) in the South West England. Outcome measures included: glycated hemoglobin (HbA1c), frequency of BG tests; frequency of sensor scans; time in recommended glucose range; short-term complications (hypoglycemia, diabetic ketoacidosis and related illness resulting in investigation) and secondary care costs.

RESULTS

After adjustment for age, time since diagnosis, deprivation and the test modality (point of care or laboratory), the mean HbA1c reading for controls was 61.2 (mmol/mol) for the period before and 63.9 after. For individuals using flash monitoring, the adjusted mean HbA1c reading was 64.6 for the period before implementation and 63.8 after. Rates of short-term complications were low across all groups in the study. Whereas the 'after' flash monitoring group had substantially higher incremental costs (+£703 vs the flash monitoring 'before' comparison and +£841 vs contemporaneous SMBG controls), these cost differences were driven by primary care prescribing (sensor costs).

CONCLUSIONS

There was some indication that flash monitoring might help young people improve the control of their diabetes but for our sample, the difference between finger-prick testing and flash monitoring was not clinically significant (HbA1c improvement <5 mmol/mol). Given the pace of technological change within diabetes, research efforts should now facilitate the real-time analysis of long-term routine data on flash and continuous glucose monitors.

Patient and nursing experience of flash glucose monitoring following kidney transplantation

Flash glucose monitoring (FGM) is increasingly used for blood glucose assessment due to ease of use and is now subsidized in Australia for blood glucose measurement for patients with Type 1 Diabetes Mellitus. Dysglycaemia is common following kidney transplantation and is associated with worse outcomes and there are data to support the use of FGM post-transplant to better detect and manage changes in blood glucose levels. There is, however, no data on patient or staff perceptions of FGM, or resource implications in this setting. We prospectively evaluated patients and nursing staff experiences of FGM compared to traditional capillary glucose measurement in the immediate post-transplant setting, along with resource utilization, cost of testing, staff time taken to test and accuracy. Twenty-one kidney transplant recipients had a FGM sensor applied in the post-operative period and results compared to capillary blood glucose monitoring (CBGM) measured at least four times a day. Six-hundred-fifty-six glucose measurements were obtained, median per patient of 30 readings (IQR 10). Pearson's correlation between FGM and CBGM readings is 0.95 (p < .001). FGM readings were lower than CBGM by an average of 1.2 mmol/L (SD 0.7). Using a 5-point preference questionnaire (with ratings varying from strongly disagree-strongly agree), both patients and nurses were highly satisfied with the usability and convenience of FGM, with all preferring FGM over CBGM. Average time to perform FGM was 3.6 s versus 64 s for CBGM. In average, cost of FGM was $58 less than traditional testing per patient. FGM is an accurate, convenient and cost-effective tool that may support optimal management of glycaemic control in the post-transplant period.

Noninvasive Continuous Glucose Monitoring With a Novel Wearable Dial Resonating Sensor: A Clinical Proof-of-Concept Study

BACKGROUND

A noninvasive, wearable continuous glucose monitor would be a major advancement in diabetes therapy. This trial investigated a novel noninvasive glucose monitor which analyzes spectral variations in radio frequency/microwave signals reflected from the wrist.

METHODS

A single-arm, open-label, experimental study compared glucose values from a prototype investigational device with laboratory glucose measurements from venous blood samples (Super GL Glucose Analyzer, Dr. Müller Gerätebau GmbH) at varying levels of glycemia. The study included 29 male participants with type 1 diabetes (age range = 19-56 years). The study comprised three stages with the following aims: (1) demonstrate initial proof-of-principle, (2) test an improved device design, and (3) test performance on two consecutive days without device recalibration. The co-primary endpoints in all trial stages were median and mean absolute relative difference (ARD) calculated across all data points.

RESULTS

In stage 1, the median and mean ARDs were 30% and 46%, respectively. Stage 2 produced marked performance improvements with a median and mean ARD of 22% and 28%, respectively. Stage 3 showed that, without recalibration, the device performed as well as the initial prototype (stage 1) with a median and mean ARD of 35% and 44%, respectively.

CONCLUSION

This proof-of-concept study shows that a novel noninvasive continuous glucose monitor was capable of detecting glucose levels. Furthermore, the ARD results are comparable to first models of commercially available minimally invasive products without the need to insert a needle. The prototype has been further developed and is being tested in subsequent studies.

TRIAL REGISTRATION NUMBER

NCT05023798.

Assessing non-adjunctive CGM safety at home and in new markets (ANSHIN)

INTRODUCTION

Continuous glucose monitoring (CGM) can guide treatment for people with type 1 (T1D) and type 2 diabetes (T2D). The ANSHIN study assessed the impact of non-adjunctive CGM use in adults with diabetes using intensive insulin therapy (IIT).

MATERIALS AND METHODS

This single-arm, prospective, interventional study enrolled adults with T1D or T2D who had not used CGM in the prior 6 months. Participants wore blinded CGMs (Dexcom G6) during a 20-day run-in phase, with treatment based on fingerstick glucose values, followed by a 16-week intervention phase and then a randomized 12-week extension phase with treatment based on CGM values. The primary outcome was change in HbA1c. Secondary outcomes were CGM metrics. Safety endpoints were the number of severe hypoglycaemic (SH) and diabetic ketoacidosis (DKA) events.

RESULTS

Of the 77 adults enrolled, 63 completed the study. Those enrolled had mean (SD) baseline HbA1c of 9.8% (1.9%), 36% had T1D, and 44% were ≥65 years old. Mean HbA1c decreased by 1.3, 1.0 and 1.0 percentage points for participants with T1D, T2D or age ≥65, respectively (p < .001 for each). CGM-based metrics including time in range also improved significantly. SH events decreased from the run-in period (67.3 per 100 person-years) to the intervention period (17.0 per 100 person-years). Three DKA events unrelated to CGM use occurred during the total intervention period.

CONCLUSIONS

Non-adjunctive use of the Dexcom G6 CGM system improved glycaemic control and was safe for adults using IIT.

Diabetes Device Downloading: Benefits and Barriers Among Youth With Type 1 Diabetes

BACKGROUND

The majority of youth with type 1 diabetes (T1D) fail to meet glycemic targets despite increasing continuous glucose monitoring (CGM) use. We therefore aimed to determine the proportion of caregivers who review recent glycemic trends ("retrospective review") and make ensuant insulin adjustments based on this data ("retroactive insulin adjustments"). We additionally considered that fear of hypoglycemia and frequency of severe hypoglycemia would be associated with performing retrospective review.

METHODS

We conducted a cross-sectional survey of caregivers of youth with T1D, collecting demographics, diabetes technology usage, patterns of glucose data review/insulin dose self-adjustment, and Hypoglycemia Fear Survey (HFS).

RESULTS

Nineteen percent of eligible caregivers (191/1003) responded. Performing retrospective review was associated with younger child age (12.2 versus 15.4, P = .0001) and CGM use (92% versus 73%, P = .004), but was not associated with a significant improvement in child's HbA1c (7.89 versus 8.04, P = .65). Retrospective reviewers had significantly higher HFS-behavior scores (31.9 versus 27.7, P = .0002), which remained significantly higher when adjusted for child's age and CGM use (P = .005). Linear regression identified a significant negative association between HbA1c (%) and number of retroactive insulin adjustments (0.24 percent lower mean HbA1c per additional adjustment made, P = .02).

CONCLUSIONS

Retrospective glucose data review is associated with improved HbA1c when coupled with data-driven retroactive insulin adjustments. Barriers to data downloading existed even in this cohort of predominantly CGM-using T1D families.

Management of Individuals With Diabetes at High Risk for Hypoglycemia: An Endocrine Society Clinical Practice Guideline

CONTEXT

Hypoglycemia in people with diabetes is common, especially in those taking medications such as insulin and sulfonylureas (SU) that place them at higher risk. Hypoglycemia is associated with distress in those with diabetes and their families, medication nonadherence, and disruption of life and work, and it leads to costly emergency department visits and hospitalizations, morbidity, and mortality.

OBJECTIVE

To review and update the diabetes-specific parts of the 2009 Evaluation and Management of Adult Hypoglycemic Disorders: Endocrine Society Clinical Practice Guideline and to address developing issues surrounding hypoglycemia in both adults and children living with diabetes. The overriding objectives are to reduce and prevent hypoglycemia.

METHODS

A multidisciplinary panel of clinician experts, together with a patient representative, and methodologists with expertise in evidence synthesis and guideline development, identified and prioritized 10 clinical questions related to hypoglycemia in people living with diabetes. Systematic reviews were conducted to address all the questions. The Grading of Recommendations Assessment, Development and Evaluation (GRADE) methodology was used to assess the certainty of evidence and make recommendations.

RESULTS

The panel agreed on 10 questions specific to hypoglycemia risk and prevention in people with diabetes for which 10 recommendations were made. The guideline includes conditional recommendations for use of real-time continuous glucose monitoring (CGM) and algorithm-driven insulin pumps in people with type 1 diabetes (T1D), use of CGM for outpatients with type 2 diabetes at high risk for hypoglycemia, use of long-acting and rapid-acting insulin analogs, and initiation of and continuation of CGM for select inpatient populations at high risk for hypoglycemia. Strong recommendations were made for structured diabetes education programs for those at high risk for hypoglycemia, use of glucagon preparations that do not require reconstitution vs those that do for managing severe outpatient hypoglycemia for adults and children, use of real-time CGM for individuals with T1D receiving multiple daily injections, and the use of inpatient glycemic management programs leveraging electronic health record data to reduce the risk of hypoglycemia.

CONCLUSION

The recommendations are based on the consideration of critical outcomes as well as implementation factors such as feasibility and values and preferences of people with diabetes. These recommendations can be used to inform clinical practice and health care system improvement for this important complication for people living with diabetes.

Diabetes patient preferences for glucose-monitoring technologies: results from a discrete choice experiment in Poland and the Netherlands

INTRODUCTION

New glucose-monitoring technologies have different cost-benefit profiles compared with traditional finger-prick tests, resulting in a preference-sensitive situation for patients. This study aimed to assess the relative value adults with diabetes assign to device attributes in two countries.

RESEARCH DESIGN AND METHODS

Adults with type 1 or 2 diabetes from the Netherlands (n=226) and Poland (n=261) completed an online discrete choice experiment. Respondents choose between hypothetical glucose monitors described using seven attributes: precision, effort to check, number of finger pricks required, risk of skin irritation, information provided, alarm function and out-of-pocket costs. Panel mixed logit models were used to determine attribute relative importance and to calculate expected uptake rates and willingness to pay (WTP).

RESULTS

The most important attribute for both countries was monthly out-of-pocket costs. Polish respondents were more likely than Dutch respondents to choose a glucose-monitoring device over a standard finger prick and had higher WTP for a device. Dutch respondents had higher WTP for device improvements in an effort to check and reduce the number of finger pricks a device requires.

CONCLUSION

Costs are the primary concern of patients in both countries when choosing a glucose monitor and would likely hamper real-world uptake. The costs-benefit profiles of such devices should be critically reviewed.

Flash glucose monitoring system in special situations

The management of diabetes mellitus (DM) requires maintaining glycemic control, and patients must keep their blood glucose levels close to the normal range to reduce the risk of microvascular complications and cardiovascular events. While glycated hemoglobin (A1C) is currently the primary measure for glucose management and a key marker for long-term complications, it does not provide information on acute glycemic excursions and overall glycemic variability. These limitations may even be higher in some special situations, thereby compromising A1C accuracy, especially when wider glycemic variability is expected and/or when the glycemic goal is more stringent. To attain adequate glycemic control, continuous glucose monitoring (CGM) is more useful than self-monitoring of blood glucose (SMBG), as it is more convenient and provides a greater amount of data. Flash Glucose Monitoring (isCGM /FGM) is a widely accepted option of CGM for measuring interstitial glucose levels in individuals with DM. However, its application under special conditions, such as pregnancy, patients on hemodialysis, patients with cirrhosis, during hospitalization in the intensive care unit and during physical exercise has not yet been fully validated. This review addresses some of these specific situations in which hypoglycemia should be avoided, or in pregnancy, where strict glycemic control is essential, and the application of isCGM/FGM could alleviate the shortcomings associated with poor glucose control or high glycemic variability, thereby contributing to high-quality care.

A pragmatic low carbohydrate diet intervention changes neither carbohydrate consumption nor glycemia in adolescents and young adults with type 1 diabetes in a randomized trial

OBJECTIVE

Despite enthusiasm for low carbohydrate diets (LCDs) among patients with type 1 diabetes (T1DM), no prospective study has investigated outcomes in adolescent T1DM. We aimed to quantify a pragmatic LCD intervention's impact on glycemia, lipidemia, and quality of life (QOL) in adolescents with T1DM.

RESEARCH DESIGN AND METHODS

At an academic center, we randomized 39 patients with T1DM aged 13-21 years to one of three 12-week interventions: an LCD, an isocaloric standard carbohydrate diet (SCD), or general diabetes education without a prescriptive diet. Glycemic outcomes included glycosylated hemoglobin (HbA1c) and continuous glucose monitoring.

RESULTS

There were no significant differences in glycemic, lipidemic, or QOL parameters between groups at any timepoint. Median HbA1c was similar at baseline between groups and did not change appreciably (7.9%-8.4% in LCDs, 7.9%-7.9% in SCDs, and 8.2%-7.8% in controls). Change in carbohydrate consumption was minimal with only one participant reaching target carbohydrate intake.

CONCLUSIONS

This pragmatic LCD intervention did not alter carbohydrate consumption or glycemia. Although this study was unable to evaluate a highly controlled LCD, it indicates that adolescents are unlikely to implement an educational LCD intervention in routine clinic settings. Thus, this approach is unlikely to effectively mitigate hyperglycemia in adolescents.

Effect of Digital-Tool-Supported Basal Insulin Titration Algorithm in Reaching Glycemic Control in Patients with Type 2 Diabetes in Mexico

BACKGROUND

My Dose Coach (MDC) is a mobile application combined with a web portal that can suggest optimized basal insulin (BI) injection doses using Self-Measured Plasma Glucose (SMPG) and hypoglycemia data. This study aimed to evaluate its efficacy on patients reaching SMPG and Fasting blood glucose (FBG) target range 90-130 mg/dl (5-7.2 mmol/L) goals without severe hypoglycemic episodes. We also addressed the mean reduction in glycated hemoglobin (A1C), FBG, and SMPG and the improvement in the WHO's Five Well Being Index (WBI).

METHODS

This prospective pilot study involved the use of MDC in outpatients with type 2 diabetes (T2DM) from a Hospital in Northern Mexico. Patients on treatment with any BI were included in the study. The follow-up was of 16 weeks. Student t-tests or McNemar test were used for effect comparisons.

RESULTS

We included 158 patients (46.8% women), mean (SD) age 51 (10.3) years. We achieved SMPG target range in 58.9% [mean (95CI) reduction of 30.9 mg/dl (22.5-37.7; P < .001)] of the patients [66(28) days], with no severe hypoglycemia events. FBG goal was reached in 55.7% [mean (95CI) reduction of 63.4 mg/dl (49.6-77.2; P < .001)]. The mean (95CI) reduction of A1C was 1.78% (1.47-2, P < .01) with the last observation carried forward. There was a mean (95CI) increase of 2.23 (-3, -1.4, P < .01) points in WBI scale.

CONCLUSIONS

MDC successfully helped to achieve FBG and SMPG goals, reduced A1C, and increased WBI with no severe hypoglycemia events.

The Association of Personality Traits and Parameters of Glycemic Regulation in Type 1 Diabetes Mellitus Patients Using isCGM

This study aimed to examine the impact of personality on glycemic regulation in adult patients with type 1 diabetes mellitus (T1DM). The study group consisted of subjects with T1DM, who were ≥ 18 years of age. The study was conducted in two phases: At baseline, subjects completed the Croatian version of the International Personality Item Pool scale (IPIP50s) and a questionnaire designed to gather socioeconomic data, duration of diabetes, presence of chronic complications, presence of cardiovascular risk factors, frequency, and type of pre-existing hypoglycemic episodes per week. Blood and urine samples were collected and body mass index (BMI) was calculated. Each participant was provided with the intermittently scanned glucose monitoring system (isCGM) Freestyle Libre. During the second visit (3 months from the start of the trial), glycemic parameters were collected from the reports generated from the Freestyle Libre system. Estimated glycated hemoglobin (HbA1c) values were significantly lower after three months compared to baseline HbA1c (Wilcoxon test, p < 0.001). An inverse correlation between the number of daily scans and degree of extraversion among subjects was observed, e.g., higher degrees of extraversion resulted in lower numbers of daily scans, while lower degrees of extraversion, i.e., introvertedness, resulted in higher numbers of daily scans (Rho = −0.238 p = 0.009). There was a positive correlation between emotional stability and time spent in hypoglycemia (Rho = 0.214; p = 0.02). In addition, a shorter duration of diabetes was associated with higher percentages of TIR and vice versa (p = 0.02). Investigating personality traits can be a useful tool for identifying patients predisposed to hypoglycemia and lower scanning frequency. Patients with a longer history of T1DM require closer follow-up and should be re-educated when necessary.

Application of the FreeStyle®Libre Glucose Monitoring System in type 1 diabetes mellitus patients aged 1-4 years

BACKGROUND

To investigate the analytical accuracy, safety performance, and user satisfaction (guardians of study participants) of the FreeStyle®Libre Glucose Monitoring System in the treatment of type 1 diabetes mellitus (T1DM), in children aged <4 years.

METHODS

Sixteen hospitalized children with new onset T1DM, aged 4 months to 4 years, were enrolled in this study. Patients wore the sensor for 14 days; sensor scans were performed immediately and at 5, 10, and 15 min after capillary blood glucose (BG) measurements to evaluate the effectiveness of the device and the lag effect.

RESULTS

The consensus error grid showed that 96.40% of values fell within zone A (no clinical impact) and 3.60% within zone B (little/no clinical impact). Overall, the mean absolute relative difference (MARD) was 9.34%, and was higher in the capillary BG <4.0 mmol/L group (15.18%) than in the 4-10 mmol/L (9.63%) and >10 mmol/L (7.17%) groups. The MARD increased gradually with scanning time extension, indicating a short lag effect. Regression analysis showed that a higher BG level was associated with a greater difference in FreeStyle®Libre System measurements.

CONCLUSIONS

The use of the FreeStyle®Libre System in children aged 1-4 years is accurate and safe, and may be accurate down to 4 months, independent of patient characteristics.

Diabetes: the role of continuous glucose monitoring

Diabetes mellitus is a chronic condition affecting 1 out of every 11 people worldwide. Monitoring of blood glucose allows for therapeutic lifestyle and pharmacotherapy changes to reduce the occurrence of hyperglycaemia and hypoglycaemia. Advancements in technology over the past two decades have increased patient and clinician access to glucose data and trends with continuous glucose monitoring (CGM) systems. This narrative review seeks to investigate the efficacy and safety of CGM for the management of diabetes. In type 1 diabetes (T1DM) and type 2 diabetes, efficacy studies of real-time CGM (rtCGM) or intermittently scanned CGM (isCGM) have shown a decrease in HbA1C (0.3–0.6%) over traditional self-monitoring blood glucose. Percent time in the target glucose range also improved (6.8–17.6%). Rates of hypoglycaemia, including severe hypoglycaemia, decreased in studies of rtCGM and isCGM with most available data in T1DM. In pregnant women with T1DM, rtCGM has shown modest improvements in HbA1C and time in target glucose range and decreased risk of neonatal complications. Multiple studies have shown that the use of rtCGM or isCGM increased diabetes treatment satisfaction amongst patients. Head-to-head studies of rtCGM and isCGM are limited but one study indicates that a CGM system with alarms may be preferred in T1DM to reduce the risk of hypoglycaemia. Selection of a CGM device should depend on patient-specific factors and insurance coverage. The results of one study show that the benefits of CGM device use were not sustained after discontinuing use. Increasing widespread and long-term access to CGM devices is necessary to improve the management of diabetes amongst the greater population.

Insight into hypoglycemia frequency in congenital hyperinsulinism: evaluation of a large UK CGM dataset

INTRODUCTION

Hypoglycemia is often recurrent and severe in patients with congenital hyperinsulinism (CHI). However, there is little information regarding frequency or patterns of episodes to inform clinical management and future trial design.

RESEARCH DESIGN AND METHODS

We aimed to describe frequency and patterns of hypoglycemia by varying thresholds through a large continuous glucose monitoring (CGM) dataset. Through the UK CHI centers of excellence, data were analyzed from patients with CHI over a 5-year period. Hypoglycemia thresholds of 3.0 (H3.0), 3.5 (H3.5) and 3.9 (H3.9) mmol/L were used to test threshold change on hypoglycemia frequencies.

RESULTS

From 63 patients, 3.4 million data points, representing 32 years of monitoring, were analyzed. By UK consensus threshold H3.5, patients experienced a mean 1.3 hypoglycemic episodes per day. Per cent time hypoglycemic increased from 1.2% to 3.3% to 6.9% when threshold changed from H3.0 to H3.5 and H3.9. Merged data showed periodicity of hypoglycemia risk in 24-hour periods in all patients.

CONCLUSIONS

We have evaluated a large dataset to provide a comprehensive picture of the frequency and patterns of hypoglycemia for patients with CHI in the UK. These data establish a baseline risk of hypoglycemia by CGM and provide a framework for clinical management and clinical trial design.

Selection of Noninvasive Features in Wrist-Based Wearable Sensors to Predict Blood Glucose Concentrations Using Machine Learning Algorithms

Glucose monitoring technologies allow users to monitor glycemic fluctuations (e.g., blood glucose levels). This is particularly important for individuals who have diabetes mellitus (DM). Traditional self-monitoring blood glucose (SMBG) devices require the user to prick their finger and extract a blood drop to measure the blood glucose based on chemical reactions with the blood. Unlike traditional glucometer devices, noninvasive continuous glucose monitoring (NICGM) devices aim to solve these issues by consistently monitoring users' blood glucose levels (BGLs) without invasively acquiring a sample. In this work, we investigated the feasibility of a novel approach to NICGM using multiple off-the-shelf wearable sensors and learning-based models (i.e., machine learning) to predict blood glucose. Two datasets were used for this study: (1) the OhioT1DM dataset, provided by the Ohio University; and (2) the UofM dataset, created by our research team. The UofM dataset consists of fourteen features provided by six sensors for studying possible relationships between glucose and noninvasive biometric measurements. Both datasets are passed through a machine learning (ML) pipeline that tests linear and nonlinear models to predict BGLs from the set of noninvasive features. The results of this pilot study show that the combination of fourteen noninvasive biometric measurements with ML algorithms could lead to accurate BGL predictions within the clinical range; however, a larger dataset is required to make conclusions about the feasibility of this approach.

Improved glucometrics in people with type 1 diabetes 1 year into the COVID-19 pandemic

INTRODUCTION

Various studies have shown a number of glycemic parameters to improve over several weeks in people with type 1 diabetes during the first surge of the COVID-19 pandemic. Whether and to what extent such improvement is sustained during following COVID-19 surges remains unknown. Therefore, the aim of this study was to investigate glycemic parameters during the first year of the COVID-19 pandemic in people with type 1 diabetes and to determine factors associated with glycemic improvement.

RESEARCH DESIGN AND METHODS

This was an observational cohort study in people with type 1 diabetes, aged ≥16 years. We compared glycated hemoglobin (HbA_1c) and flash glucose monitoring (FGM) downloads between the prelockdown period and approximately 1 year thereafter. Using logistic regression analysis, we assessed associations between an HbA_1c reduction of at least 0.5% (~5.5 mmol/mol) with baseline clinical characteristics and self-reported changes in psychological well-being and lifestyle behavior related to COVID-19.

RESULTS

A total of 437 participants were included. As compared with prepandemic data, 1 year after the start of the COVID-19 pandemic and associated lockdowns, HbA_1c had decreased from 7.9%±1.1% (63±12 mmol/mol) to 7.5%±1.0% (59±11 mmol/mol) (p<0.001), whereas time in range increased from 55.8%±16.7% to 58.6%±16.7% (p=0.004) and time below (<3.9 mmol/L) and above (>13.9 mmol/L) range and glucose variability all decreased (all p<0.05). FGM use, higher HbA_1c at baseline and current smoking were independently associated with an HbA_1c decrease of at least 0.5%, whereas self-reported changes in psychological well-being and lifestyle behavior related to the first surge of the COVID-19 pandemic and associated lockdowns were not.

CONCLUSIONS

The COVID-19 pandemic and related lockdown measures were associated with improvement in glucometrics, including HbA_1c and FGM data, in individuals with type 1 diabetes, particularly in FGM users, those with higher HbA_1c at baseline or current smokers.

FreeStyle Libre Flash Glucose Monitoring system for people with type 1 diabetes in the UK: a budget impact analysis

INTRODUCTION

This study aims to estimate the budget impact of increased uptake of the FreeStyle Libre Flash Glucose Monitoring system in people with type 1 diabetes mellitus (T1DM) in the UK.

RESEARCH DESIGN AND METHODS

A budget impact model was developed, applying real-world data collected in the Association of British Clinical Diabetologists (ABCD) FreeStyle Libre Nationwide Audit. Costs of diabetes glucose monitoring in a T1DM population (n=1790) using self-monitoring of blood glucose (SMBG) or the FreeStyle Libre system were compared with a scenario with increased use of the FreeStyle Libre system.

RESULTS

The ABCD audit demonstrates FreeStyle Libre system use reduces diabetes-related resource utilization. The cost analysis found that higher acquisition costs are offset by healthcare costs avoided (difference £168 per patient per year (PPPY)). Total costs were £1116 PPPY with FreeStyle Libre system compared with £948 PPPY with SMBG. In an average-sized UK local health economy, increasing FreeStyle Libre system uptake from 30% to 50% increased costs by 3.4% (£1 787 345-£1 847 618) and when increased to 70% increased by a further 3.3%.

CONCLUSION

Increased uptake of the FreeStyle Libre system in the T1DM population marginally increases the cost to UK health economies and offers many system benefits.

FGM-based remote intervention for adults with type 1 diabetes: The FRIEND randomized clinical trial

BACKGROUND

The use of flash glucose monitoring (FGM) in conjunction with proper education has been reported to improve glycemic control in people with diabetes on insulin therapy. However, there are still few randomized controlled trials on the educational effect, and an ideal educational model has not been established. This study aimed to estimate the efficacy of remote intervention for glycemic control in adults with type 1 diabetes using FGM.

METHODS

In this single-center, randomized controlled trial, we enrolled adults with type 1 diabetes (HbA1c ≥7.0%). The participants were randomly assigned (1:1) to either FGM use with remote intervention (intervention group) or FGM use only (control group). Changes in glycemic outcomes such as HbA1c levels and continuous glucose monitoring metrics were evaluated at 12 weeks.

RESULTS

Among 36 randomized participants (mean age, 44.3 years; mean baseline HbA1c, 8.9%), 34 completed the study. The remote intervention did not significantly reduce HbA1c levels. FGM use significantly improved HbA1c levels by -1.4% and -0.8% in both groups with and without remote intervention, respectively (P=0.003 and P=0.004, respectively). However, the intervention group showed significant increases in time with glucose in the range of 70-180 mg/dL (TIR; from 49.8% to 60.9%, P=0.001) and significant decreases in time with hyperglycemia (P=0.002) and mean glucose (P=0.017), but the control group did not. Moreover, the TIR (P=0.019), time with hyperglycemia >250 mg/dL (P=0.019), and coefficient of variation (P=0.018) were significantly improved in the intervention group compared to the control group. In particular, the CGM metrics improved gradually as the remote intervention was repeated. Furthermore, the intervention group reported higher treatment satisfaction (P=0.016).

CONCLUSIONS

Ongoing, personalized education during FGM use may lead to amelioration of glycemic control in adults with type 1 diabetes, even remotely.

CLINICAL TRIAL REGISTRATION

https://clinicaltrials.gov/ct2/show/NCT04936633, identifier NCT04936633.

Eliciting Requirements for a Diabetes Self-Management Application for Underserved Populations: A Multi-Stakeholder Analysis

Medically underserved communities have limited access to effective disease management resources in the U.S. Mobile health applications (mHealth apps) offer patients a cost-effective way to monitor and self-manage their condition and to communicate with providers; however, current diabetes self-management apps have rarely included end-users from underserved communities in the design process. This research documents key stakeholder-driven design requirements for a diabetes self-management app for medically underserved patients. Semi-structured survey interviews were carried out on 97 patients with diabetes and 11 healthcare providers from medically underserved counties in South Texas, to elicit perspectives and preferences regarding a diabetes self-management app, and their beliefs regarding such an app's usage and utility. Patients emphasized the need for accessible educational content and for quick access to guidance on regulating blood sugar, diet, and exercise and physical activity using multimedia rather than textual forms. Healthcare providers indicated that glucose monitoring, educational content, and the graphical visualization of diabetes data were among the top-rated app features. These findings suggest that specific design requirements for the underserved can improve the adoption, usability, and sustainability of such interventions. Designers should consider health literacy and numeracy, linguistic barriers, data visualization, data entry complexity, and information exchange capabilities.

Parental monitoring for type 1 diabetes in genetically at-risk young children: The TEDDY study

OBJECTIVE

We examined parental diabetes monitoring behaviors in a cohort of children at increased genetic risk for type 1 diabetes. We hypothesized that being informed of a positive islet autoantibody (IA) would increase monitoring behaviors.

RESEARCH DESIGN AND METHODS

The Environmental Determinants of Diabetes in the Young (TEDDY) study follows 8676 children with high-risk human leucocyte antigen-DQ genotypes from birth to age 15, including general population (GP) children and those with a first-degree relative (FDR) with diabetes. Data on parental monitoring behaviors were solicited yearly. Serum samples were tested for IA and parents were informed of child results. We examined parental monitoring behaviors during the first 7 years of TEDDY.

RESULTS

In IA- children, the most common monitoring behavior was participating in TEDDY study tasks; up to 49.8% and 44.2% of mothers and fathers, respectively, reported this. Among FDRs, 7%-10% reported watching for diabetes symptoms and 7%-9% reported monitoring the child's glucose, for mothers and fathers, respectively. After IA+ notification, all monitoring behaviors significantly increased in GP parents; only glucose monitoring increased in FDR parents and these behaviors continued for up to 4 years. FDR status, accurate diabetes risk perception, and anxiety were associated with glucose monitoring in IA+ and IA- cohorts.

CONCLUSIONS

Many parents view TEDDY participation as a way to monitor for type 1 diabetes, a benefit of enrollment in a longitudinal study with no prevention offered. IA+ notification increases short- and long-term monitoring behaviors. For IA- and IA+ children, FDR parents engage in glucose monitoring, even when not instructed to do so.

Safety and feasibility of a factory-calibrated continuous glucose monitoring system in term and near-term infants at risk of hypoglycemia

Objective

Hypoglycemia increases the risk of adverse neurological outcomes in neonates. Adequate glucose monitoring requires repetitive and painful blood sampling. We aimed to evaluate the feasibility and accuracy of a continuous glucose monitoring system (CGMS) using factory-calibrated sensors to improve glucose monitoring and decrease the frequency of blood samples in neonates.

Material and Methods

A methodological study was conducted to investigate a correlation of CGMS values with blood glucose measurements.

Results

Factory-calibrated CGMS sensors were placed on 21 infants at risk of hypoglycemia after delivery. CGMS values were compared with blood glucose concentrations. Thirty-seven pairs of CGMS and blood glucose values were obtained. There was a good correlation between CGMS and blood glucose values (R=0.67, p<0.01) with a mean difference (2 standard deviations) of 9.78 (-24.68 to 44.25) mg/dL. The mean differences at <3 hours and ≥3 hours after sensor placement were 17.35 (-4.54 to 39.21) mg/dL and 0.88 (-37.62 to 39.38) mg/dL, respectively. CGMS values were significantly higher than blood glucose concentration at <3 hours after sensor placement (p<0.01), whereas no significant differences in glucose values were observed between the CGMS and blood glucose values at ≥3 hours after sensor placement (p=0.852).

Conclusion

The factory-calibrated CGMS was a safe and feasible modality for glucose monitoring. However, it has a tendency to overestimate the blood glucose concentrations. Therefore, this system should be used cautiously for neonates at risk of hypoglycemia, especially within 3 hours after sensor placement.

Glycemic outcomes related to depression in adults with type 1 diabetes

Glycemic outcomes of adults with type 1 diabetes may be affected by depression. Our aim was to compare outcomes of "depressed" (Patient Health Questionnaire-9 ⩾ 10, N = 83) to "not-depressed" matched control (Patient Health Questionnaire-2 < 3, N = 166) adults with type 1 diabetes with objective measures. The depressed group had poorer blood glucose control and, for those with glucose meter downloads, fewer glucose tests/day. The groups did not differ on glucose variability or episodes of hypoglycemia. Depression in adults with type 1 diabetes is associated with poorer glycemic control and less blood glucose monitoring. Future research should examine whether treatment of depression results in better self-care and glycemic outcomes.

Continuous glucose monitoring: A review of the evidence in type 1 and 2 diabetes mellitus

CONTEXT AND AIM

Continuous glucose monitoring (CGM) is becoming widely accepted as an adjunct to diabetes management. Compared to standard care, CGM can provide detailed information about glycaemic variability in an internationally standardised ambulatory glucose profile, enabling more informed user and clinician decision making. We aimed to review the evidence, user experience and cost-effectiveness of CGM.

METHODS

A literature search was conducted by combining subject headings 'CGM' and 'flash glucose monitoring', with key words 'type 1 diabetes' and 'type 2 diabetes', limited to '1999 to current'. Further evidence was obtained from relevant references of retrieved articles.

RESULTS

There is a strong evidence for CGM use in people with type 1 diabetes, with benefits of reduced glycated haemoglobin and hypoglycaemia, and increased time in range. While the evidence for CGM use in type 2 diabetes is less robust, similar benefits have been demonstrated. CGM can improve diabetes-related satisfaction in people with diabetes (PWD) and parents of children with diabetes, as well as the clinician experience. However, CGM does have limitations including cost, accuracy and perceived inconvenience. Cost-effectiveness analyses have indicated that CGM is a cost-effective adjunct to type 1 diabetes management that is associated with reduced diabetes-related complications and hospitalisation.

CONCLUSIONS

Continuous glucose monitoring is revolutionising diabetes management. It is a cost-effective adjunct to diabetes management that has the potential to improve glycaemic outcomes and quality of life in PWD, especially type 1 diabetes.

Adoption of Digital Health Technologies in the Practice of Behavioral Health: Qualitative Case Study of Glucose Monitoring Technology

Background

Evaluation of patients with serious mental illness (SMI) relies largely on patient or caregiver self-reported symptoms. New digital technologies are being developed to better quantify the longitudinal symptomology of patients with SMI and facilitate disease management. However, as these new technologies become more widely available, psychiatrists may be uncertain about how to integrate them into daily practice. To better understand how digital tools might be integrated into the treatment of patients with SMI, this study examines a case study of a successful technology adoption by physicians: endocrinologists’ adoption of digital glucometers.

Objective

This study aims to understand the key facilitators of and barriers to clinician and patient adoption of digital glucose monitoring technologies to identify lessons that may be applicable across other chronic diseases, including SMIs.

Methods

We conducted focus groups with practicing endocrinologists from 2 large metropolitan areas using a semistructured discussion guide designed to elicit perspectives of and experiences with technology adoption. The thematic analysis identified barriers to and facilitators of integrating digital glucometers into clinical practice. Participants also provided recommendations for integrating digital health technologies into clinical practice more broadly.

Results

A total of 10 endocrinologists were enrolled: 60% (6/10) male; a mean of 18.4 years in practice (SD 5.6); and 80% (8/10) working in a group practice setting. Participants stated that digital glucometers represented a significant change in the treatment paradigm for diabetes care and facilitated more effective care delivery and patient engagement. Barriers to the adoption of digital glucometers included lack of coverage, provider reimbursement, and data management support, as well as patient heterogeneity. Participant recommendations to increase the use of digital health technologies included expanding reimbursement for clinician time, streamlining data management processes, and customizing the technologies to patient needs.

Conclusions

Digital glucose monitoring technologies have facilitated more effective, individualized care delivery and have improved patient engagement and health outcomes. However, key challenges faced by the endocrinologists included lack of reimbursement for clinician time and nonstandardized data management across devices. Key recommendations that may be relevant for other diseases include improved data analytics to quickly and accurately synthesize data for patient care management, streamlined software, and standardized metrics.

Variability in preventive care practices among US adults with diabetes mellitus

INTRODUCTION

Patients with diabetes are advised to follow standard medical care including daily blood glucose and foot checks, eye examinations with pupil dilation, and cholesterol checks to prevent diabetes-related complications. It is unclear how these practices currently vary across different US population subgroups. The objective of this study was to assess variation in overall and individual diabetes care practices and identify specific factors associated with differences in these practices in a representative sample of US diabetic adults.

RESEARCH DESIGN AND METHODS

Cross-sectional data were from the 2017 Behavioral Risk Factor Surveillance System. Survey logistic regression was used to account for the complex sampling design.

RESULTS

Among 30 780 eligible participants, 8957 (equivalent to 28% of the target population) followed all four diabetes care practices. Insulin-dependent participants had higher adjusted odds (adjusted OR=2.95; 95% CI 2.62 to 3.31) of following all four diabetic care practices compared with those who did not. Cost-related variables (having healthcare coverage and/or a personal doctor) were positively associated with diabetes care practices, with the strongest association observed for adherence to more costly practices (annual eye examination and cholesterol check) versus less costly ones (daily blood glucose check, daily foot check).

CONCLUSIONS

Our findings suggest the need for diabetes care practice-specific and population subgroup-specific public health interventions to encourage early adherence to diabetic care practices and reduce complications.

Continuous Glucose Monitoring With Low-Carbohydrate Diet Coaching in Adults With Prediabetes: Mixed Methods Pilot Study

BACKGROUND

Type 2 diabetes mellitus (T2DM) is preventable; however, few patients with prediabetes participate in prevention programs. The use of user-friendly continuous glucose monitors (CGMs) with low-carbohydrate diet coaching is a novel strategy to prevent T2DM.

OBJECTIVE

This study aims to determine the patient satisfaction and feasibility of an intervention combining CGM use and low-carbohydrate diet coaching in patients with prediabetes to drive dietary behavior change.

METHODS

We conducted a mixed methods, single-arm pilot and feasibility study at a suburban family medicine clinic. A total of 15 adults with prediabetes with hemoglobin A_1c (HbA_1c) levels between 5.7% and 6.4% and a BMI >30 kg/m² were recruited to participate. The intervention and assessments took place during 3 in-person study visits and 2 qualitative phone interviews (3 weeks and 6 months after the intervention). During visit 1, participants were asked to wear a CGM and complete a food intake and craving log for 10 days. During visit 2, the food intake and craving log along with the CGM results of the participants were reviewed and the participants received low-carbohydrate diet coaching, including learning about carbohydrates and personalized feedback. A second CGM sensor, with the ability to scan and record glucose trends, was placed, and the participants logged their food intake and cravings as they attempted to reduce their total carbohydrate intake (<100 g/day). During visit 3, the participants reviewed their CGM and log data. The primary outcome was satisfaction with the use of CGM and low-carbohydrate diet. The secondary outcomes included feasibility, weight, and HbA_1c change, and percentage of time spent in hyperglycemia. Changes in attitudes and risk perception of developing diabetes were also assessed.

RESULTS

The overall satisfaction rate of our intervention was 93%. The intervention induced a weight reduction of 1.4 lb (P=.02) and a reduction of HbA_1c levels by 0.71% (P<.001) since enrollment. Although not significantly, the percentage of time above glucose goal and average daily glucose levels decreased slightly during the study period. Qualitative interview themes indicated no major barriers to CGM use; the acceptance of a low-carbohydrate diet; and that CGMs helped to visualize the impact of carbohydrates on the body, driving dietary changes.

CONCLUSIONS

The use of CGMs and low-carbohydrate diet coaching to drive dietary changes in patients with prediabetes is feasible and acceptable to patients. This novel method merits further exploration, as the preliminary data indicate that combining CGM use with low-carbohydrate diet coaching drives dietary changes, which may ultimately prevent T2DM.

Differences in glucose level between right arm and left arm using continuous glucose monitors

Background

Continuous glucose monitoring (CGM) measures interstitial glucose levels through a sensor with a thin filament inserted under the skin. It is customary for patients to rotate sensor application sites between arms to minimize skin irritation. However, there is limited data regarding the degree of inter-arm differences with CGM technology.

Methods

Self-proclaimed right-handed (n = 5) and left-handed (n = 5) participants, regardless of concurrent comorbidities, were enrolled for CGM. Participants wore a FreeStyle Libre Pro sensor on each arm for a maximum of 14 days. Muscle mass and body fat analysis was conducted using a multi-frequency segmental body composition analyzer. Glucose levels from both arms were time-matched with the first 12 hours eliminated from analysis. Mean glucose and time in target range were compared between readings from the right and left arm.

Results

A total of 9830 paired glucose levels were included for analysis. In all participants (n = 10), mean glucose on the right arm was 89.1 mg/dL (SD, 19.9) and 85.3 mg/dL (SD, 19.3) on the left arm (P < 0.001). Glucose was out of target range (70-180 mg/dL) for 12.7% of the time in the right arm compared to 18.5% in the left arm (P < 0.001).

Conclusions

In a group of 10 nondiabetic and diabetic adults, there was a statistically significant difference in CGM readings between the right and left arms. Time in target range may differ based on arm selection when using a CGM. Arm dominance did not explain the inter-arm glucose level discordance.

The efficacy and safety of insulin pump therapy with predictive low glucose suspend feature in decreasing hypoglycemia in children with type 1 diabetes mellitus: A systematic review and meta-analysis

BACKGROUND

Automated insulin delivery with predictive low glucose suspend (PLGS) feature has the potential to reduce risk of hypoglycemia in patients with type 1 diabetes mellitus (T1DM). We aim to systematically synthesize the evidence on the efficacy and safety of PLGS in children and adolescents with T1DM.

METHODS

We performed a systematic search through Ovid/MEDLINE, Ovid/Embase, and other search engines. We included randomized controlled trials (RCTs) evaluating the effect of sensor augmented pump (SAP) with PLGS feature compared to SAP or insulin pump therapy without SAP in decreasing hypoglycemia in children and adolescents aged 2 to 18 years with T1DM, with at least 2 weeks of follow-up. Two reviewers independently selected studies, extracted data, and evaluated the risk of bias (ROB).

RESULTS

Five RCTs with total sample size of 493 children aged 6 to 18 years met the inclusion criteria. The overall ROB of included studies was low. There is high quality evidence that PLGS is superior to SAP in decreasing time spent in hypoglycemia (sensor glucose [SG] <3.9 mmol/L [<70 mg/dL]/24 h) and nocturnal hypoglycemia (SG <3.9 mmol [<70 mg/dL]/L/night) with an absolute mean difference of 17.4 min/d (95% CI: -19.2, -15.5) and 26.3 min/night (95% CI: -35.5, -16.7), respectively, without increasing percentage of time spent in hyperglycemia or episodes of diabetic ketoacidosis (DKA). There was insufficient evidence for the impact of PLGS on health related quality of life (HRQL).

CONCLUSIONS

PLGS is superior to SAP in decreasing daytime and nocturnal hypoglycemia without increasing the risk of DKA or hyperglycemia. Future studies should address the impact of PLGS on children younger than 6-years-old and HRQL.

Modern diabetes devices in the school setting: Perspectives from school nurses

OBJECTIVE

To explore the experiences, practices, and attitudes of school nurses related to modern diabetes devices (insulin pumps, continuous glucose monitors, and hybrid-closed loop systems).

RESEARCH DESIGN AND METHODS

Semistructured interviews were conducted with 40 public school nurses caring for children in elementary and middle schools. Developed with stakeholder input, the interview questions explored experiences working with devices and communicating with the health care system. Deidentified transcripts were analyzed through an iterative process of coding to identify major themes.

RESULTS

School nurses reported a range of educational backgrounds (58% undergraduate, 42% graduate), geographic settings (20% urban, 55% suburban, 25% rural), and years of experience (20% <5 years, 38%, 5-15 years, 42% >15 years). Four major themes emerged: (a) As devices become more common, school nurses must quickly develop new knowledge and skills yet have inconsistent training opportunities; (b) Enthusiasm for devices is tempered by concerns about implementation due to poor planning prior to the school year and potential disruptions by remote monitors; (c) Barriers exist to integrating devices into schools, including school/classroom policies, liability/privacy concerns, and variable staff engagement; and (d) Collaboration between school nurses and providers is limited; better communication may benefit children with diabetes.

CONCLUSIONS

Devices are increasingly used by school-aged children. School nurses appreciate device potential but share structural and individual-level challenges. Guiding policy is needed as the technology progressively becomes standard of care. Enhanced training and collaboration with diabetes providers may help to optimize school-based management for children in the modern era.

Efficacy and safety of flash glucose monitoring in patients with type 1 and type 2 diabetes: a systematic review and meta-analysis

INTRODUCTION

Flash glucose monitoring (FGM) is a factory-calibrated sensor-based technology for the measurement of interstitial glucose. We performed a systematic review and meta-analysis to assess its efficacy and safety in patients with type 1 and type 2 diabetes.

RESEARCH DESIGN AND METHODS

PubMed, CENTRAL, Scopus and Web of Science were searched in July 2019. Twelve studies with a follow-up longer than 8 weeks, evaluating 2173 patients on prandial insulin, multiple daily insulin injections or continuous subcutaneous insulin infusion were included. The following data were extracted: HbA1c, time in range, time above 180 mg/dL, time below 70 mg/dL, frequency of hypoglycemic events, number of self-monitoring of blood glucose (SMBG) measurements, total daily insulin dose, patient-reported outcomes, adverse events, and discontinuation rate. A comparison with SMBG was conducted.

RESULTS

FGM use was associated with a reduction in HbA1c (-0.26% (-3 mmol/mol); p=0.002) from baseline to the last available follow-up, which correlated with HbA1c levels at baseline (-0.4% (-4 mmol/mol) for each 1.0% (11 mmol/mol) of HbA1c above 7.2% (55 mmol/mol)). Also, a decrease in time below 70 mg/dL was found (-0.60 hours/day; p=0.04). Favorable findings in patient-reported outcomes and no device-related serious adverse events were reported. When compared with SMBG, FGM was characterized by no statistically different change in HbA1c (p=0.09), with lower number of SMBG measurements per day (-3.76 n/day; p<0.001) and risk of discontinuation (relative risk=0.42; p=0.001). A limited number of studies, with a heterogeneous design and usually with a short-term follow-up and without specific training, were found.

CONCLUSIONS

The present review provides evidence for the use of FGM as an effective strategy for the management of diabetes.

System accuracy evaluation of 18 CE-marked current-generation blood glucose monitoring systems based on EN ISO 15197:2015

OBJECTIVE

Accuracy of 18 current-generation blood glucose monitoring systems (BGMS) available in Europe was evaluated applying criteria adapted from EN ISO 15197:2015 with one reagent system lot. BGMS were selected based on market research data.

RESEARCH DESIGN AND METHODS

The BGMS ABRA, Accu-Chek Guide, AURUM, CareSens Dual, CERA-CHEK 1CODE, ContourNext One, eBsensor, FreeStyle Freedom Lite, GL50 evo, GlucoCheck GOLD, GlucoMen areo 2K, GluNEO, MyStar DoseCoach, OneTouch Verio Flex, Pic GlucoTest, Rightest GM700S, TRUEyou, and WaveSense JAZZ Wireless were tested using capillary blood from 100 different subjects and assessing the percentage of results within ±15 mg/dL (0.83 mmol/L) or 15% of comparison method results for BG concentrations below or above 100 mg/dL (5.55 mmol/L), respectively. In addition, the minimal deviation from comparison method results within which ≥95% of results of the respective BGMS were found was calculated.

RESULTS

In total, 14 BGMS had ≥95% of results within ±15 mg/dL (0.83 mmol/L) or ±15% and 3 BGMS had ≥95% of results within ±10 mg/dL (0.55 mmol/L) or ±10% of the results obtained with the comparison method. The smallest deviation from comparison method results within which ≥95% of results were found was ±7.7 mg/dL (0.43 mmol/L) or ±7.7%; the highest deviation was ±19.7 mg/dL (1.09 mmol/L) or ±19.7%.

CONCLUSIONS

This accuracy evaluation shows that not all CE-labeled BGMS fulfill accuracy requirements of ISO 15197 reliably and that there is considerable variation even among BGMS fulfilling these criteria. This safety-related information should be taken into account by patients and healthcare professionals when making therapy decisions.

TRIAL REGISTRATION NUMBER

NCT03737188.

Estimating plasma glucose with the FreeStyle Libre Pro continuous glucose monitor during oral glucose tolerance tests in youth without diabetes

Few studies have assessed the accuracy of the FreeStyle Libre Pro (FLP) continuous glucose monitor for estimating plasma glucose (PG) in non-diabetic children.

OBJECTIVE

Determine the accuracy of FLP compared to PG during OGTT in healthy children.

SUBJECTS

Children (7-11.99 years) with healthy weight and overweight/obesity (n = 33; 52% male).

METHODS

Participants wore the FLP before and during a 2-hour OGTT; PG was measured at 30 minutes intervals. Potential systematic- and magnitude-related biases for FLP vs PG were examined.

RESULTS

FLP 15-minute averages and PG were correlated at most timepoints during OGTT (r2 = 0.35-0.69, P's < .001 for time point 30-120 minutes) and for PG area under the curve (AUC) (r2 = 0.65, P < .0001). There were no systematic biases as assessed by Bland-Altman analyses for FLP AUC or for FLP at each OGTT timepoint. However, for fasting glucose, a significant magnitude bias was noted (r2 = 0.38, P < .001), such that lower PG was underestimated, and higher PG was overestimated by FLP readings; further, there was poor correlation between fasting PG and FLP (r2 = 0.06, P = .22). BMIz was also associated with FLP accuracy: FLP overestimated PG in children with low BMIz and underestimated PG in those with overweight/obesity for OGTT AUC and OGTT PG at baseline, 60, and 120 minutes (all P's ≤ .015). No adverse events occurred with FLP.

CONCLUSIONS

Among children without diabetes, the FLP was well tolerated and correlated with post-OGTT glucose, but had magnitude bias affecting fasting glucose and appeared to underestimate plasma glucose in those with overweight/obesity. These results suggest potential limitations for the utility of the FLP for research.

Pan-European Economic Analysis to Identify Cost Savings for the Health Care Systems as a Result of Integrating Glucose Monitoring Based Telemedical Approaches Into Diabetes Management

BACKGROUND

Self-monitoring of blood glucose supported by the diabetes-app OneTouch Reveal® has demonstrated to improve HbA1c. We aimed at analyzing costs savings related the integration of telemedical features into diabetes management.

METHODS

Data from a randomized controlled trial were used to assess the 10-year risk of patients for fatal myocardial infarction (MI). On the basis of this risk assessments-also related to a 5% or 10% reduction of hypoglycemic episodes-cost savings for the health care systems of five European countries-France, Germany, Italy, Spain, and the United Kingdom-were modeled.

RESULTS

HbA1c reduction of 0.92% in insulin-treated type 2 diabetes patients (T2DM) was associated with a 2.3% decreased 10-year risk for fatal MI. In combination with a 10% reduction of hypoglycemic events this risk reduction led to cost savings of €16.1 million (France), €57.8 million (Germany), €30.9 million (Italy), €23.8 million (Spain), and €5.8 million (UK), considering all insulin-treated T2DM patients in the respective countries.

CONCLUSION

Improving metabolic control and thus risk for comorbidities like MI by combining the glucose meter with CRI with telemedical features has the potential to reduce costs for European health care systems.

Sydney Diabetes centre's experience of the Australian Government's roll out of subsidised continuous glucose monitoring for children with type 1 diabetes mellitus

AIM

To determine patient/carer expectations of continuous glucose monitoring (CGM) and short-term satisfaction, to assess the efficacy of CGM in improving: fear of hypoglycaemia and glycaemic control (HbA_1c , ketosis, hypoglycaemia) and to determine time requirements of diabetes clinic staff in commencing and administering CGM.

METHODS

We assessed CGM-naïve patients starting on CGM at a Sydney Diabetes Centre following the introduction of a nationwide government subsidy for CGM. A standardised questionnaire was administered collecting demographic and glycaemic information in addition to Likert scale assessment of expectations and satisfaction. Clinic staff reported time dedicated to CGM education, commencement and follow-up.

RESULTS

A total of 55 patients or parents/carers completed baseline questionnaires, with 37 completing a 3-month follow-up questionnaire. There were high expectations of CGM prior to commencement and high satisfaction ratings on follow-up. CGM improved fear of hypoglycaemia, and total daily insulin dose increased after commencement of CGM. There was a trend towards lower HbA_1c that was not statistically significant and no statistically significant reduction in ketosis or hypoglycaemia. Comments were mostly positive, with some concern raised regarding technical issues and a lack of subsidy after 21 years of age. Staff time requirements were substantial, with an estimated average of 7.7 h per patient per year.

CONCLUSIONS

Patients and families have high expectations of CGM, and satisfaction levels are high in the short term. Total insulin delivery increased after CGM commencement. Time requirements by staff are substantial but are worthwhile if families' overall satisfaction levels are high.

An Evaluation of Digital Health Tools for Diabetes Self-Management in Hispanic Adults: Exploratory Study

Background

Although multiple self-monitoring technologies for type 2 diabetes mellitus (T2DM) show promise for improving T2DM self-care behaviors and clinical outcomes, they have been understudied in Hispanic adult populations who suffer disproportionately from T2DM.

Objective

The objective of this study was to evaluate the acceptability, feasibility, and potential integration of wearable sensors for diabetes self-monitoring among Hispanic adults with self-reported T2DM.

Methods

We conducted a pilot study of T2DM self-monitoring technologies among Hispanic adults with self-reported T2DM. Participants (n=21) received a real-time continuous glucose monitor (RT-CGM), a wrist-worn physical activity (PA) tracker, and a tablet-based digital food diary to self-monitor blood glucose, PA, and food intake, respectively, for 1 week. The RT-CGM captured viewable blood glucose concentration (mg/dL) and PA trackers collected accelerometer-based data, viewable on the device or an associated tablet app. After 1 week of use, we conducted a semistructured interview with each participant to understand experiences and thoughts on integration of the data from the devices into a technology-facilitated T2DM self-management intervention. We also conducted a brief written questionnaire to understand participants’ self-reported T2DM history and past experience using digital health tools for T2DM self-management. Feasibility was measured by device utilization and objective RT-CGM, PA tracker, and diet logging data. Acceptability and potential integration were evaluated through thematic analysis of verbatim interview transcripts.

Results

Participants (n=21, 76% female, 50.4 [SD 11] years) had a mean self-reported hemoglobin A_1c of 7.4 [SD 1.8] mg/dL and had been diagnosed with T2DM for 7.4 [SD 5.2] years (range: 1-16 years). Most (89%) were treated with oral medications, whereas the others self-managed through diet and exercise. Nearly all participants (n=20) used both the RT-CGM and PA tracker, and 52% (11/21) logged at least one meal, with 33% (7/21) logging meals for 4 or more days. Of the 8 possible days, PA data were recorded for 7.1 [SD 1.8] days (range: 2-8), and participants averaged 7822 [SD 3984] steps per day. Interview transcripts revealed that participants felt most positive about the RT-CGM as it unveiled previously unknown relationships between lifestyle and health and contributed to changes in T2DM-related thoughts and behaviors. Participants felt generally positive about incorporating the wearable sensors and mobile apps into a future intervention if support were provided by a health coach or health care provider, device training were provided, apps were tailored to their language and culture, and content were both actionable and delivered on a single platform.

Conclusions

Sensor-based tools for facilitating T2DM self-monitoring appear to be a feasible and acceptable technology among low-income Hispanic adults. We identified barriers to acceptability and highlighted preferences for wearable sensor integration in a community-based intervention. These findings have implications for the design of T2DM interventions targeting Hispanic adults.

Experiences of Adults With Type 1 Diabetes Using Glucose Sensor-Based Mobile Technology for Glycemic Variability: Qualitative Study

Background

Adults with type 1 diabetes (PWDs) face challenging self-management regimens including monitoring their glucose values multiple times a day to assist with achieving glycemic targets and reduce the risk of long-term diabetes complications. Recent advances in diabetes technology have reportedly improved glycemia, but little is known about how PWDs utilize mobile technology to make positive changes in their diabetes self-management.

Objective

The aim of this qualitative study was to explore PWDs’ experiences using Sugar Sleuth, a glucose sensor–based mobile app and Web-based reporting system, integrated with the FreeStyle Libre glucose monitor that provides feedback about glycemic variability.

Methods

We used a qualitative descriptive research design and conducted semistructured interviews with 10 PWDs (baseline mean glycated hemoglobin, HbA_1c) 8.0%, (SD 0.45); 6 males and 4 females, aged 52 years (SD 15), type 1 diabetes (T1D) duration 31 years (SD 13), 40% (4/10, insulin pump) following a 14-week intervention during which they received clinical support and used Sugar Sleuth to evaluate and understand their glucose data. Audio-recorded interviews were transcribed, coded, and analyzed using thematic analysis and NVivo 11 (QSR International Pty Ltd).

Results

A total of 4 main themes emerged from the data. Participants perceived Sugar Sleuth as an Empowering Tool that served to inform lifestyle choices and diabetes self-management tasks, promoted preemptive self-care actions, and improved discussions with clinicians. They also described Sugar Sleuth as providing a Source of Psychosocial Support and offering relief from worry, reducing glycemic uncertainty, and supporting positive feelings about everyday life with diabetes. Participants varied in their Approaches to Glycemic Data: 40% (4/10) described using Sugar Sleuth to review data, understand glycemic cause and effect, and plan for future self-care. On the contrary, 60% (6/10) were reluctant to review past data; they described receiving benefits from the immediate numbers and trend arrows, but the app still prompted them to enter in the suspected causes of glucose excursions within hours of their occurrence. Finally, only 2 participants voiced Concerns About Use of Sugar Sleuth; they perceived the app as sometimes too demanding of information or as not attuned to the socioeconomic backgrounds of PWDs from diverse populations.

Conclusions

Results suggest that Sugar Sleuth can be an effective educational tool to enhance both patient-clinician collaboration and diabetes self-management. Findings also highlight the importance of exploring psychosocial and socioeconomic factors that may advance the understanding of PWDs’ individual differences when using glycemic technology and may promote the development of customized mobile tools to improve diabetes self-management.

Experiences of Patients With a Diabetes Self-Care App Developed Based on the Information-Motivation-Behavioral Skills Model: Before-and-After Study

BACKGROUND

Mobile phones have been actively used in various ways for diabetes self-care. Mobile phone apps can manage lifestyle factors such as diet, exercise, and medication without time or place restrictions. A systematic review has found these apps to be effective in reducing blood glucose. However, the existing apps were developed and evaluated without a theoretical framework to explain the process of changes in diabetes self-care behaviors.

OBJECTIVE

This study aimed to evaluate the diabetes self-care app that we developed by measuring differences in diabetes self-care factors between before and after using the app with the Information-Motivation-Behavioral skills model of Diabetes Self-Care (IMB-DSC).

METHODS

We conducted a single-group pre- and postintervention study with a convenience sample of diabetes patients. A total of 38 adult patients with diabetes who had an Android smartphone were recruited. After conducting a preliminary survey of those who agreed to participate in the study, we provided them with a manual and a tutorial video about the diabetes self-care app. The app has functions for education, recommendations, writing a diary, recording, goal setting, sharing, communication, feedback, and interfacing with a glucometer, and it was applied for 4 weeks. We measured the general characteristics of participants, their history of diabetes self-care app usage, IMB-DSC factors, and blood glucose levels. The IMB-DSC factors of information, personal motivation, social motivation, behavioral skills, and behaviors were measured using an assessment tool consisting of 87 items extracted from the Diabetes Knowledge Test, third version of the Diabetes Attitude Scale, Diabetes Family Behavior Checklist, and Diabetes Self-Management Assessment Report Tool.

RESULTS

The mean age of the participants was 43.87 years. A total 30 participants out of 38 (79%) had type 2 diabetes and 8 participants (21%) had type 1 diabetes. The most frequently used app function was recording, which was used by 34 participants out of 38 (89%). Diabetes self-care behaviors (P=.02) and diabetes self-care social motivation (P=.05) differed significantly between pre- and postintervention, but there was no significant difference in diabetes self-care information (P=.85), diabetes self-care personal motivation (P=.57), or diabetes self-care behavioral skills (P=.89) between before and after using the diabetes self-care app.

CONCLUSIONS

Diabetes self-care social motivation was significantly improved with our diabetes self-care app by sharing experiences and sympathizing with other diabetes patients. Diabetes self-care behavior was also significantly improved with the diabetes self-care app by providing an interface with a glucometer that removes the effort of manual input. Diabetes self-care information, diabetes self-care personal motivation, and diabetes self-care behavioral skills were not significantly improved. However, they will be improved with additional offline interventions such as reflective listening and simulation.

Impact of Use Frequency of a Mobile Diabetes Management App on Blood Glucose Control: Evaluation Study

Background

Technology has long been used to carry out self-management as well as to improve adherence to treatment in people with diabetes. However, most technology-based apps do not meet the basic requirements for engaging patients.

Objective

This study aimed to evaluate the effect of use frequency of a diabetes management app on glycemic control.

Methods

Overall, 2 analyses were performed. The first consisted of an examination of the reduction of blood glucose (BG) mean, using a randomly selected group of 211 users of the SocialDiabetes app (SDA). BG levels at baseline, month 3, and month 6 were calculated using the intercept of a regression model based on data from months 1, 4, and 7, respectively. In the second analysis, the impact of low and high BG risk was examined. A total of 2692 users logging SDA ≥5 days/month for ≥6 months were analyzed. The highest quartile regarding low blood glucose index (LBGI) and high blood glucose index (HBGI) at baseline (t1) was selected (n=74 for group A; n=440 for group B). Changes in HBGI and LBGI at month 6 (t2) were analyzed.

Results

For analysis 1, baseline BG results for type 1 diabetes mellitus (T1DM) groups A and B were 213.61 (SD 31.57) mg/dL and 206.43 (SD 18.65) mg/dL, respectively, which decreased at month 6 to 175.15 (SD 37.88) mg/dL and 180.6 (SD 40.47) mg/dL, respectively. For type 2 diabetes mellitus (T2DM), baseline BG was 218.77 (SD 40.18) mg/dL and 232.55 (SD 46.78) mg/dL, respectively, which decreased at month 6 to 160.51 (SD 39.32) mg/dL and 173.14 (SD 52.81) mg/dL for groups A and B, respectively. This represents a reduction of estimated A_1c (eA_1c) of approximately 1.3% (P<.001) and 0.9% (P=.001) for T1DM groups A and B, respectively, and 2% (P<.001) for both A and B T2DM groups, respectively. For analysis 2, T1DM baseline LBGI values for groups A and B were 5.2 (SD 3.9) and 4.4 (SD 2.3), respectively, which decreased at t2 to 3.4 (SD 3.3) and 3.4 (SD 1.9), respectively; this was a reduction of 34.6% (P=.005) and 22.7% (P=.02), respectively. Baseline HBGI values for groups A and B were 12.6 (SD 4.3) and 10.6 (SD 4.03), respectively, which decreased at t2 to 9.0 (SD 6.5) and 8.6 (SD 4.7), respectively; this was a reduction of 30% (P=.001) and 22% (P=.003), respectively.

Conclusions

A significant reduction in BG was found in all groups, independent of the use frequency of the app. Better outcomes were found for T2DM patients. A significant reduction in LBGI and HBGI was found in all groups, regardless of the use frequency of the app. LBGI and HBGI indices of both groups tend to have similar values after 6 months of app use.

Mobile App for Improved Self-Management of Type 2 Diabetes: Multicenter Pragmatic Randomized Controlled Trial

Background

As the increasing prevalence of type 2 diabetes mellitus has put pressure on health systems to appropriately manage these patients, there have been a growing number of mobile apps designed to improve the self-management of diabetes. One such app, BlueStar, has been shown to significantly reduce hemoglobin A_1c (HbA_1c) levels in small studies and is the first app in the United States to receive Food and Drug Administration approval as a mobile prescription therapy. However, the impact of the app across real-world population among different clinical sites and health systems remains unclear.

Objective

The primary objective of this study was to conduct a pragmatic randomized controlled trial of the BlueStar mobile app to determine if app usage leads to improved HbA_1c levels among diverse participants in real-life clinical contexts. We hypothesized that this mobile app would improve self-management and HbA_1c levels compared with controls.

Methods

The study consisted of a multicenter pragmatic randomized controlled trial. Overall, 110 participants randomized to the immediate treatment group (ITG) received the intervention for 6 months, and 113 participants randomized to the wait-list control (WLC) group received usual care for the first 3 months and then received the intervention for 3 months. The primary outcome was glucose control measured by HbA_1c levels at 3 months. Secondary outcomes assessed intervention impact on patient self-management, experience of care, and self-reported health utilization using validated scales, including the Problem Areas in Diabetes, the Summary of Diabetes Self-Care Activities, and the EuroQol-5D. Intervention usage data were collected directly from the app.

Results

The results of an analysis of covariance controlling for baseline HbA_1c levels did not show evidence of intervention impact on HbA_1c levels at 3 months (mean difference [ITG−WLC] −0.42, 95% CI −1.05 to 0.21; P=.19). Similarly, there was no intervention effect on secondary outcomes measuring diabetes self-efficacy, quality of life, and health care utilization behaviors. An exploratory analysis of 57 ITG participants investigating the impact of app usage on HbA_1c levels showed that each additional day of app use corresponded with a 0.016-point decrease in participants’ 3-month HbA_1c levels (95% CI −0.03 to −0.003). App usage varied significantly by site, as participants from 1 site logged in to the app a median of 36 days over 14 weeks (interquartile range [IQR] 10.5-124); those at another site used the app significantly less (median 9; IQR 6-51).

Conclusions

The results showed no difference between intervention and control arms for the primary clinical outcome of glycemic control measured by HbA_1c levels. Although there was low usage of the app among participants, results indicate contextual factors, particularly site, had a significant impact on overall usage. Future research into the patient and site-specific factors that increase app utilization are needed.

Trial Registration

Clinicaltrials.gov NCT02813343; https://clinicaltrials.gov/ct2/show/NCT02813343 (Archived by WebCite at https://clinicaltrials.gov/ct2/show/NCT02813343)

Contribution of structured self-monitoring of blood glucose to self-efficacy in poorly controlled diabetes patients in China

AIM

To investigate the association between structured self-monitoring of blood glucose (SMBG) and diabetes self-efficacy in Chinese patients.

METHODS

This study was a single-centre, open-label, prospective, randomized controlled trial. A total of 250 type 1 and type 2 diabetes patients were recruited and randomly assigned to the structured SMBG group and the control group in a 1:1 ratio. The main outcome observed in this subgroup analysis was a change in the diabetes self-efficacy scale (DSES) scores. A multivariate generalized estimating equation was used to evaluate factors affecting the DSES scores.

RESULTS

We found that the DSES scores tended to decrease significantly with the follow-up time in the intervention group (Wald β = 7.882, P < .001; Wald β = 3.130, P = .003; Wald β = 7.879, P < .001). However, no significant differences in the DSES scores were detected in the control group. Glycaemic control improved in both the intervention and control groups at the third month (P < .05). In the intervention group, sustained improvement of the DSES scores maintained the improvement in glycaemic control through the sixth month. In the control group, glycaemic control tended to deteriorate in the sixth month without the support of an improved DSES scores (P = .056).

CONCLUSION

Structured SMBG could contribute to the effective and persistent improvement of diabetes self-efficacy. (ClinicalTrials.gov, NCT02225691).

Reduced insulin sensitivity is correlated with impaired sleep in adolescents with cystic fibrosis

BACKGROUND

Prevalence of cystic fibrosis-related diabetes (CFRD) rises sharply in adolescence/young-adulthood and is associated with increased morbidity/mortality. Sleep may be a modifiable risk factor for diabetes but its relationship with metabolic function has not been fully examined in youth with CF. The aim of the study was to examine the relationship between objectively measured sleep and glucose metabolism in youth with CF.

METHODS

Adolescents (43 with CF and 11 healthy controls) completed 1-week of concurrent home continuous glucose monitoring (CGM) and actigraphy. Fasting labs and an oral glucose tolerance test were obtained. T-tests and analysis of variance (ANOVA) were used to test differences between actigraphy outcomes in CF participants and controls. Spearman's rank correlation coefficients were used to test for correlations between actigraphy, CGM, and insulin sensitivity (IS) measures.

RESULTS

All participants averaged insufficient sleep (mean = 7.5 hours per night) compared to the 8 to 10 hours recommended for this age group. CF participants had poorer sleep by actigraphy measures than healthy controls. Higher minimum daytime glucoses on CGM correlated with shorter total sleep time (TST) and worse sleep efficiency (SE). Reduced IS in CF participants with dysglycemia was correlated with shorter TST, longer sleep latency, more wake after sleep onset, and poorer SE.

CONCLUSIONS

Poor sleep appears to correlate with higher blood glucose and lower IS in CF adolescents with dysglycemia. Further research is needed to better understand the mechanisms and directionality behind this relationship.