Self-Monitoring of Blood Glucose Requirements with the Use of Intermittently Scanned Continuous Glucose Monitoring

Current intermittently scanned continuous glucose monitoring (isCGM) devices do not allow calibration and require confirmatory self-monitored blood glucose (SMBG) under specific defined conditions. The overall time spent in an SMBG-indicated state while using isCGM has not been reported in the existing literature. We present the time spent in an SMBG-indicated state and the daily number of transitions to an SMBG-indicated state during isCGM use in a high-risk cohort of adults with type 1 diabetes. This is a post hoc analysis of participants randomized to isCGM as part of a clinical study. The percentage of values meeting one or more of the criteria for SMBG testing (hours per day) and the number of transitions to an SMBG-indicated state per day were calculated according to the manufacturer's label in the United Kingdom. Complete data sets for 20 participants on isCGM for 8 weeks were included in the analysis. Participants spent a mean (SD) of 5.61 (1.81) h/day in an SMBG-indicated state and there were 5.43 (1.42) transitions to an SMBG-indicated state per day while using isCGM. These findings have important implications for cost-effectiveness and for decision-making around insulin dose calculations and driving. Our findings emphasize the need for continued SMBG testing among people at high risk of hypoglycemia who use isCGM. Cost-effectiveness analyses for isCGM may require revision.

Differences for Percentage Times in Glycemic Range Between Continuous Glucose Monitoring and Capillary Blood Glucose Monitoring in Adults with Type 1 Diabetes: Analysis of the REPLACE-BG Dataset

Background: Self-monitored blood glucose (SMBG) and real-time continuous glucose monitoring (rtCGM) are used by people living with type 1 diabetes (T1D) to assess glucose and inform decision-making. Percentage time in range (%TIR) between 3.9 and 10 mmol/L has been associated with incident microvascular complications using historical SMBG data. However, the association between %TIR calculated from rtCGM data has not been identified. This study investigates whether %TIR values generated from rtCGM and SMBG data significantly differ from each other in adults with T1D. Materials and Methods: rtCGM and SMBG data from the REPLACE-BG study were obtained and analyzed. The dataset contained rtCGM (Dexcom G4 Platinum) and SMBG (Contour Next) values for 226 participants during a run-in phase lasting up to 10 weeks, followed by the 26-week trial. Percentages times in hypoglycemic, euglycemia and hyperglycemic ranges were generated from rtCGM and SMBG data using last observation carry forward method (zero-order hold) and linear interpolation (first-order hold). Results: Participants had a median (interquartile range [IQR]) age of 43.0 (31.0-55.0) years, and hemoglobin A1C of 53 (49-57) mmol/mol [7.0 (6.6-7.4)%]. The median (IQR) %TIR was significantly higher with rtCGM than with SMBG; 63.0 (55.9-71.0)% versus 54.6 (45.6-63.0)%, respectively, P < 0.001. Median %times in hypoglycemia and hyperglycemia were significantly different with SMBG than rtCGM (P < 0.001). SMBG-derived data using linear interpolation significantly differed from the carry forward method (P < 0.001 for all glycemic ranges). Differences reported were greater at night than during the day (P < 0.001 for all glycemic ranges). Conclusion: The %time in all glycemic ranges reported by SMBG and rtCGM differ significantly, suggesting relationships between times in ranges, and complication status may be different between monitoring modalities. In addition, varying methods of calculating %TIR from SMBG-derived data provide significantly differing results. %TIR targets may therefore vary by monitoring choice and methods of calculation and harmonization of TIR standards may be challenging.

Diabetes Healthcare Professionals Use Multiple Continuous Glucose Monitoring Data Indicators to Assess Glucose Management

BACKGROUND

Continuous glucose monitoring (CGM) offers multiple data features that can be leveraged to assess glucose management. However, how diabetes healthcare professionals (HCPs) actually assess CGM data and the extent to which they agree in assessing glycemic management are not well understood.

METHODS

We asked HCPs to assess ten de-identified CGM datasets (each spanning seven days) and rank order each day by relative glycemic management (from "best" to "worst"). We also asked HCPs to endorse features of CGM data that were important in making such assessments.

RESULTS

In the study, 57 HCPs (29 endocrinologists; 28 diabetes educators) participated. Hypoglycemia and glycemic variance were endorsed by nearly all HCPs to be important (91% and 88%, respectively). Time in range and daily lows and highs were endorsed more frequently by educators (all Ps < .05). On average, HCPs endorsed 3.7 of eight data features. Overall, HCPs demonstrated agreement in ranking days by relative glycemic control (Kendall's W = .52, P < .001). Rankings were similar between endocrinologists and educators (R² = .90, Cohen's kappa = .95, mean absolute error = .4 [all Ps < .05]; Mann-Whitney U = 41, P = .53).

CONCLUSIONS

Consensus in the endorsement of certain data features and agreement in assessing glycemic management were observed. While some practice-specific differences in feature endorsement were found, no differences between educators and endocrinologists were observed in assessing glycemic management. Overall, HCPs tended to consider CGM data holistically, in alignment with published recommendations, and made converging assessments regardless of practice.

Effect of frequency of sensor use on glycaemic control in individuals on sensor-augmented pump therapy with and without Predictive Low Glucose Management System

Improved frequency of sensor use improves glycaemic control. Furthermore, there is no deterioration of glycaemic control with increased sensor use in individuals on Predictive Low Glucose Management (PLGM) system. Younger children are more likely to have better sensor uptake than older children.

Association between mandatory health examination attendance and diabetes treatment initiation among employees being treated for hypertension

OBJECTIVES

It is unclear whether mandatory health examination is effective for employees who are already being treated for chronic diseases. We focused on patients being treated for hypertension and evaluated the association between employer-based health examination attendance and diabetes treatment initiation.

METHODS

Using a database that stores health insurance claims and health examination results of subscribers enrolled in society-managed health insurance plans in Japan, we identified employees aged 40-59 years who were being treated for hypertension when starting diabetes treatment from April 2012 to December 2016. A case-crossover analysis was conducted using 90, 180, and 270 days prior to diabetes treatment initiation as reference points and 90 days after the mandatory health examination as the exposure period. We conducted a subgroup analysis by hemoglobin A1c (HbA1c) level and frequency of outpatient blood glucose testing before the mandatory health examination.

RESULTS

We identified 1464 individuals starting treatment for diabetes while on antihypertensive drugs. The overall odds ratio for starting diabetes treatment within 90 days of the health examination was 1.89 (95% confidence interval: 1.70-2.10). The subgroup analysis showed that this odds ratio increased as HbA1c level increased and as blood glucose testing frequency decreased.

CONCLUSIONS

Among employees starting treatment for diabetes while being treated for hypertension, employer-based mandatory health examination attendance was associated with initiation of diabetes treatment. The health examinations may be functioning as a complement to screening in outpatient settings.

Improved well-being and decreased disease burden after 1-year use of flash glucose monitoring (FLARE-NL4)

Introduction

The FreeStyle Libre is a flash glucose monitoring (FSL-FGM) system. Compared with finger-prick based self-monitoring of blood glucose, FSL-FGM may provide benefits in terms of improved glycemic control and decreased disease burden.

Methods

Prospective nationwide registry. Participants with diabetes mellitus (DM) used the FSL-FGM system for a period of 12 months. End points included changes in HbA1c, hypoglycemia, health-related quality of life (12-Item Short Form Health Surveyv2 (SF-12v2) and 3-level version of EuroQol 5D (EQ-5D-3L)), a specifically developed patient-reported outcome measures (PROMs) questionnaire, diabetes-related hospital admission rate and work absenteeism. Measurements were performed at baseline, and after 6 months and 12 months.

Results

1365 persons (55% male) were included. Mean age was 46 (16) years, 77% of participants had type 1 DM, 16% type 2 DM and 7% other forms. HbA1c decreased from 64 (95%CI 63 to 65) mmol/mol to 60 (95%CI 60 to 61) mmol/mol with a difference of -4 (95% CI -6 to 3) mmol/mol. Persons with a baseline HbA1c >70 mmol/mol had the most profound HbA1c decrease: -9 (95% CI -12 to to 5) mmol/mol. EQ-5D tariff (0.03 (95%CI 0.01 to 0.05)), EQ-VAS (4.4 (95%CI 2.1 to 6.7)) and SF-12v2 mental component score (3.3 (95%CI 2.1 to 4.4)) improved. For most, PROMs improved. Work absenteeism rate (/6 months) and diabetes-related hospital admission rate (/year) decreased significantly, from 18.5% to 7.7% and 13.7% to 2.3%, respectively.

Conclusions

Real world data demonstrate that use of FSL-FGM results in improved well-being and decreased disease burden, as well as improvement of glycemic control.

Diabetes-specific family conflict and responsibility among emerging adults with type 1 diabetes

Emerging adulthood is a transitional period for type 1 diabetes management, and aspects of family functioning such as family conflict and responsibility for diabetes management likely change following high school graduation. This study examined changes in diabetes-specific family conflict, family responsibility for diabetes management tasks, and associations with glycemic control up to 1 year after high school. Seventy-nine emerging adults with type 1 diabetes (M age = 18.09 ± .43 years; 51% female; 71% Caucasian) and their parents (73% female) completed self-report measures on diabetes-specific family conflict and family responsibility at 3 consecutive clinic visits, beginning in the spring of their senior year of high school. Hemoglobin A1c (HbA1c) was obtained from medical records. Diabetes-specific family conflict was relatively low; scores did not significantly change from baseline to Time 3. Parent responsibility for diabetes care decreased from baseline to Time 3. Higher parent- and emerging adult-reported family conflict and higher parent responsibility for diabetes care were associated with worse glycemic control (ps < .05). Parent-reported family conflict and the interaction between parent-reported family conflict and responsibility predicted HbA1c 1 year after high school. Conversely, HbA1c did not predict diabetes-specific family conflict or responsibility 1 year after high school. Findings indicate that diabetes-specific family conflict is associated with glycemic control after high school, even when emerging adults assume greater responsibility for diabetes self-care. Diabetes-specific family conflict levels were generally low and did not change over time despite this transitional period. If diabetes-specific conflict is present, it should be an important avenue for potential intervention for emerging adults with type 1 diabetes. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Autism spectrum disorder in children with Type 1 diabetes

AIM

Links between autism spectrum disorder (ASD) and autoimmune diseases, including Type 1 diabetes have been proposed. This study assessed the frequency of ASD in children with Type 1 diabetes in the T1D Exchange (T1DX) registry and the impact of ASD on characteristics of children with Type 1 diabetes.

METHODS

Analysis included 10 032 participants aged < 18 years (median Type 1 diabetes duration 6.5 years, 48% female, 77% non-Hispanic White). Diagnosis of ASD was defined as autism, Asperger's or pervasive developmental disorder.

RESULTS

A diagnosis of ASD was recorded for 159 (1.58%) participants. Those with ASD were predominantly male (88% vs. 51% of those without ASD, P < 0.001) and slightly older (median 14 vs. 13 years, P = 0.022). Occurrence of diabetic ketoacidosis at Type 1 diabetes diagnosis was similar (35% vs. 41%, P = 0.161). Pump use was lower in those with ASD (51% vs. 63%, P = 0.005) but continuous glucose monitor use was similar (24% vs. 27%, P = 0.351). Median HbA_1c was slightly lower in those with ASD [68 vs. 69 mmol/mol (8.4% vs. 8.5%), P = 0.006]. This difference was more pronounced after adjusting for confounders.

CONCLUSIONS

The frequency of ASD in the T1DX registry was similar to that in the general population. These data show that despite deficits in communication, occurrence of diabetic ketoacidosis was similar in youth with and without ASD. Pump use was less frequent in those with ASD, possibly due to sensory issues, although CGM use did not differ. The lower HbA_1c may be due to a more regimented routine with ASD. Because comorbidities such as ASD complicate care of patients with Type 1 diabetes, further research is needed to support these children.

Use of flash glucose monitoring system in assessing safety of the SGLT2 inhibitors during Ramadan fasting in high risk insulin treated patients with type 2 diabetes

BACKGROUND

The risks of hypoglycemia, dehydration and kidney injury may theoretically be aggravated by people with type 2 diabetes treated with Insulin and SGLT2 inhibitors during Ramadan. Data on safety and efficacy of SGLT2-I in people with type 2 diabetes treated with insulin is scanty. We aimed to assess the impact of SGLT2 inhibitors during Ramadan in high-risk patients with type 2 diabetes treated with insulin, on hypoglycemia, glycemic control and kidney function.

METHODS

This is a prospective interventional study on high-risk diabetes patients who insisted on fasting. All patients were treated with insulin ± SGLT2I. All patients received a FGMS and Ramadan focused education. All patients attended clinic before and post Ramadan where they were advised on treatment modification as well as biometric and biochemical measurements.

RESULTS

95 patients enrolled in the study and 49 of them were on SGLT2i. There was a no significant change in creatinine in both groups. FGMS showed an improvement in the sensor-calculated HbA1c from 7.3 ± 1.5 to 6.8 ± 1.1 and from 8 ± 1.6 to 7.7 ± 1.5 in the SGLT2 group and the non-SGT2i groups, respectively. The hypoglycemia was predominantly reported during Ramadan between 12:00 to 18:00 h, while in pre-Ramadan readings was during 2400-0600 and 1200-1800 slots.

CONCLUSIONS

This is the first study that assesses the use of SGLT2i along with insulin during Ramadan, using FGMS in high-risk patients with type 2 diabetes under optimal care. There was minimal interruption of fasting, significant improvement in glycemic control, and no significant change in the kidney function after Ramadan.

Effects of mobile phone application combined with or without self-monitoring of blood glucose on glycemic control in patients with diabetes: A randomized controlled trial

AIMS/INTRODUCTION

There is potential for mobile applications to deliver new self-management interventions for chronic disease, especially in diabetes. The aim of the present study was to evaluate the effects of a mobile phone application (MPA) combined with or without self-monitoring of blood glucose (SMBG) on glycemic control in patients with diabetes.

MATERIALS AND METHODS

The study was a 24-week period, four-arm parallel group, non-blinded, randomized trial. A total of 185 patients with mean age of 52 years were randomized to group A (no MPA and no SMBG), group B (SMBG only), group C (MPA only) and group D (both MPA and SMBG were used). Changes in glycated hemoglobin (HbA1c), fasting plasma glucose and 1,5-anhydroglucitol from baseline to week 24 were analyzed.

RESULTS

At 24 weeks, the HbA1c levels in patients of all groups decreased significantly from baseline. There were significant differences in the proportions of patients that achieved HbA1c <7% between groups, especially in group C and group D, compared with group A at week 24 (60.4%, 62.2% vs 25.5%, all P < 0.05). 1,5-Anhydroglucitol changes were obvious in group A and group C at week 24 from baseline (all P < 0.05 within groups). Factorial analysis of anova showed that MPA intervention was the main effective factor for HbA1c change (F = 4.59, P = 0.034), and there was no effect on HbA1c change for SMBG intervention (P = 0.975).

CONCLUSIONS

Implementation of the MPA, Diabetes-Carer, is effective in improving the proportion of HbA1c <7% in patients with type 2 diabetes.

Defining High Glycemic Variability in Type 1 Diabetes: Comparison of Multiple Indexes to Identify Patients at Risk of Hypoglycemia

Background: International consensus on the use of continuous glucose monitoring (CGM) recommends coefficient of variation (CV) as the metric of choice to express glycemic variability (GV) with a cutoff of 36% to define unstable diabetes. Even though, CV is associated with hypoglycemia in type 2 diabetes patients, the evidence on the use of one particular measure of GV in type 1 diabetes (T1DM) patients as a predictor of hypoglycemia is limited. Methods: A cohort of T1DM ambulatory patients was evaluated using CGM. Number and incidence rate of events <54 and <70 mg/dL were calculated. Bivariate and multivariate analysis of different glycemic indexes and clinical variables were performed to identify those associated with hypoglycemia. Receiver operating characteristic (ROC) curve analysis for each of the glycemic indexes was performed to define the best index and its optimal cutoff threshold to discriminate patients with events of hypoglycemia. Results: Seventy-three patients were included. A total of 128 events <54 mg/dL were recorded in 34 patients, and 350 events <70 mg/dL were registered in 51 patients. CV was the only variable significantly associated with hypoglycemia <54 mg/dL in the multivariate analysis (adjusted relative risk [aRR] 1.44, 95% confidence interval [CI]: 1.10-1.88, P = 0.008). CV, HbA1c (glycated hemoglobin), and mean glucose were associated with events <70 mg/dL. ROC curve analysis showed that, among GV metrics, CV had the best performance to discriminate patients with events <54 mg/dL (area under the curve [AUC] 0.87, 95% CI: 0.79-0.95) and events <70 mg/dL (AUC 0.79, 95% CI: 0.68-0.90) with optimal cutoff thresholds values of 34% and 31%, respectively. Among glycemic risk (GR) indexes, low blood glucose index (LBGI) showed the best performance. Conclusions: This analysis shows that CV is the best GV index, and LBGI the best GR index, to identify patients at risk of clinically significant hypoglycemia and hypoglycemia alert events in T1DM patients.

Continuous Subcutaneous Insulin Infusion in Adult Type 1 Diabetes Mellitus Patients: Results from a Public Health System

Aims: To analyze prevalence and clinical effect of continuous subcutaneous insulin infusion (CSII) in adult type 1 diabetes mellitus (T1DM) patients in a public health system real-world scenario. Materials and Methods: All adult T1DM patients on CSII being followed at Castilla-La Mancha Health Public Service were included. Primary efficacy outcome was the change in HbA_1c during the follow-up. Secondary efficacy outcomes included evaluation of the following variables: insulin pump indications, diabetes complication rates, insulin and pump use, continuous glucose monitoring use, patients achieving an HbA_1c decrease ≥6 mmol/mol (0.5%) with or without severe hypoglycemia, and discontinuations. Direct patient data were typed through the web-based Spanish national registry on CSII therapy by nine diabetologists from eight different health care areas. Results: A total of 7% of T1DM adult patients were treated with insulin pumps in our region, with a regional prevalence of 18.7 CSII patients/100,000 inhabitants. Three hundred thirteen patients were analyzed with a mean age of 34.1 ± 11.0 years and T1DM duration of 16.6 ± 9.7 years. Mean duration of CSII therapy was 6.2 ± 4.0 years. Data completion was 91.2%. Main indications for treatment were high glucose variability (36%) and suboptimal glycemic control (32%). Mean duration of CSII therapy was 6.2 ± 4.0 years. Sensor-augment pump therapy was used by 26% of the patients. Glycated hemoglobin decreased to -5 mmol/mol (95% CI -6 to -3 mmol/mol; P < 0.001) during the follow-up (Mean difference in change -0.4%, 95% CI -0.5 to -0.2; P < 0.001). Percentage of patients with severe hypoglycemia decreased from 32% to 13% (P < 0.001). Frequent nonsevere hypoglycemia, severe hypoglycemia, and diabetic ketoacidosis were less frequent among patients using higher number of daily basal rates at the study end. The rate of CSII interruption was 3.8%. Conclusions: Prevalence of CSII therapy in our region remains under 10% of adult T1DM patients, although CSII treatment was associated with a sustained improvement in glycemic control.

Continuous Glucose Monitoring Predicts Progression to Diabetes in Autoantibody Positive Children

CONTEXT

Accurate measures are needed for the prediction and diagnosis of type 1 diabetes (T1D) in at-risk persons.

OBJECTIVE

The purpose of this study was to explore the value of continuous glucose monitoring (CGM) in predicting T1D onset.

DESIGN AND SETTING

The Diabetes Autoimmunity Study in the Young (DAISY) prospectively follows children at increased risk for development of islet autoantibodies (islet autoantibody positive; Ab+) and T1D.

PARTICIPANTS

We analyzed 23 Ab+ participants with available longitudinal CGM data.

MAIN OUTCOME MEASURE

CGM metrics as glycemic predictors of progression to T1D.

RESULTS

Of 23 Ab+ participants with a baseline CGM, 8 progressed to diabetes at a median age of 13.8 years during a median follow-up of 17.7 years (interquartile range, 14.6 to 22.0 years). Compared with nonprogressors, participants who progressed to diabetes had significantly increased baseline glycemic variability (SD, 29 vs 21 mg/dL; P = 0.047), daytime sensor average (122 vs 106 mg/dL; P = 0.02), and daytime sensor area under the curve (AUC, 470,370 vs 415,465; P = 0.047). They spent 24% of time at >140 mg/dL and 12% at >160 mg/dL compared with, respectively, 8% and 3% for nonprogressors (both P = 0.005). A receiver-operating characteristic curve analysis showed an AUC of 0.85 for percentage of time spent at >140 or 160 mg/dL. The cutoff of 18% time spent at >140 mg/dL had 75% sensitivity, 100% specificity, and a 100% positive predictive value for diabetes prediction, although these values could change because some nonprogressors may develop diabetes with longer follow-up.

CONCLUSIONS

Eighteen percent or greater CGM time spent at >140 mg/dL predicts progression to diabetes in Ab+ children.

Factors associated with glycemic control in community-dwelling elderly individuals with type 2 diabetes mellitus in Zhejiang, China: a cross-sectional study

BACKGROUND

Although exercise seems to be beneficial for type 2 diabetes mellitus (T2DM) patients, there is limited research elucidating the optimal accessible indices of adiposity and insulin resistance for identifying elderly T2DM patients with poor glycemic control, which could be improved by performing regular exercise.

METHODS

A community-based, cross-sectional study was conducted with 918 Chinese elderly individuals with T2DM in Zhejiang. Relevant risk factors for poor glycemic control, as determined using glycated haemoglobin A1c (HbA1c) > 7%, were explored using logistic regression analyses and included body mass index (BMI), waist circumference (WC), waist to height ratio (WHtR), fasting blood glucose (FBG), triglycerides (TGs), total cholesterol (TC), the product of fasting triglycerides and glucose (TyG), visceral adiposity index (VAI), lipid accumulation product (LAP), TyG-BMI, and TyG-WC. Comparisons of the risk factors' ability to discriminate poor glycemic control as well as their optimal cutoff values were determined using receiver operating characteristic (ROC) analyses, and then the extent of poor glycemic control risk reduction through regular exercise was examined using multivariate logistic regression analyses.

RESULTS

The overall poor glycemic control rate was 49.3%. The factors associated with poor glycemic control included FBG > 3.869, TyG > 8.73, TyG-BMI > 222.45, and TyG-WC > 713.48 in logistic regression analyses. The optimal cutoff points of FBG, TyG, TyG-WC, and TyG-BMI in discriminating poor glycemic control were 7.38, 9.22, 813.33, and 227.77, and their corresponding areas under the ROC curves were 0.864(0.840-0.886), 0.684(0.653-0.714), 0.604(0.571-0.635), and 0.574(0.541-0.606), respectively. Occasional and regular exercise reduced the odds ratios (95% confidence interval) of poor glycemic control to 0.187 (0.063-0.557) and 0.183 (0.059-0.571) for subjects with TyG-WC > 813.33 (p = 0.008), to 0.349 (0.156-0.782) and 0.284 (0.123-0.652) for subjects with TyG > 9.22 (p = 0.011), and to 0.390 (0.175-0.869) and 0.300(0.130-0.688) for subjects with TyG-BMI > 227.77 (p = 0.017), respectively, after adjusting for multiple confounding factors.

CONCLUSION

Among elderly individuals with T2DM, poor glycemic control risk might be identified using indices calculated from FBG, TG, BMI, and WC measurements, which are indicative of adiposity and insulin resistance. TyG-WC seems to be an accessible and useful indicator to identify which elderly T2DM patients would benefit from performing regular exercise to achieve good glycemic control.

Flash Glucose Monitoring Accepted in Daily Life of Children and Adolescents with Type 1 Diabetes and Reduction of Severe Hypoglycemia in Real-Life Use

Background: Flash glucose monitoring (FGM) is covered by the Belgian public health insurance for type 1 diabetes since 2016. The objective of this study was to describe the use of FGM and diabetes outcomes in type 1 diabetic children and adolescents 1 year after reimbursement. Methods: All patients had the choice to convert to FGM or to continue with self-monitoring of blood glucose (SMBG). Clinical data were collected at baseline, at the next visit, and after 12 months; glucose profiles at next visit and after 12 months. Regression analyses were performed to identify predictors of FGM acceptance and changes in metabolic control. Results: A total of 334 subjects were included, of whom 278 (83.2%) switched to FGM. They were younger (13.6 vs. 15.2 years; P = 0.012) and performed more SMBG testing at baseline than patients who did not switch (4.3 vs. 4.1 tests daily; P = 0.008). At the end of follow-up, the rate of severe hypoglycemia decreased by 53% in the group of FGM users (P = 0.012) while it remained stable in SMBG users. Median glycated hemoglobin did not change significantly in both groups. Among subjects who switched to FGM, 15.8% reverted to SMBG after a median use of 5.3 months. Adverse events, diabetes duration, and FGM utilization were independent predictors of the risk for reverting. FGM-related adverse events were associated with a fivefold increased risk to revert to SMBG (hazard ratio = 5.12; P < 0.0001). Conclusions: FGM is relatively well accepted and decreases the risk of severe hypoglycemic events in our pediatric population. FGM is more often discontinued in patients experiencing adverse events and with longer diabetes duration.

The impact of using a closed-loop system on food choices and eating practices among people with Type 1 diabetes: a qualitative study involving adults, teenagers and parents

AIMS

We explored whether, how and why moving onto and using a hybrid day-and-night closed-loop system affected people's food choices and dietary practices to better understand the impact of this technology on everyday life and inform recommendations for training and support given to future users.

METHODS

Twenty-four adults, adolescents and parents were interviewed before commencing use of the closed-loop system and following its 3-month use. Data were analysed thematically and longitudinally.

RESULTS

While participants described preparing and/or eating similar meals to those consumed prior to using a closed-loop, many described feeling more normal and less burdened by diabetes in dietary situations. Individuals also noted how the use of this technology could lead to deskilling (less precise carbohydrate counting) and less healthy eating (increased snacking and portion sizes and consumption of fatty, energy-dense foods) because of the perceived ability of the system to deal with errors in carbohydrate counting and address small rises in blood glucose without a corrective dose needing to be administered.

CONCLUSIONS

While there may be quality-of-life benefits to using a closed-loop, individuals might benefit from additional nutritional and behavioural education to help promote healthy eating. Refresher training in carbohydrate counting may also be necessary to help ensure that users are able to undertake diabetes management in situations where the technology might fail or that they take a break from using it.

Assessment of a Precision Medicine Analysis of a Behavioral Counseling Strategy to Improve Adherence to Diabetes Self-management Among Youth: A Post Hoc Analysis of the FLEX Trial

IMPORTANCE

The Flexible Lifestyles Empowering Change (FLEX) trial, an 18-month randomized clinical trial testing an adaptive behavioral intervention in adolescents with type 1 diabetes, showed no overall treatment effect for its primary outcome, change in hemoglobin A1c (HbA1c) percentage of total hemoglobin, but demonstrated benefit for quality of life (QoL) as a prespecified secondary outcome.

OBJECTIVE

To apply a novel statistical method for post hoc analysis that derives an individualized treatment rule (ITR) to identify FLEX participants who may benefit from intervention based on changes in HbA1c percentage (primary outcome), QoL, and body mass index z score (BMIz) (secondary outcomes) during 18 months.

DESIGN, SETTING, AND PARTICIPANTS

This multisite clinical trial enrolled 258 adolescents aged 13 to 16 years with type 1 diabetes for 1 or more years, who had literacy in English, HbA1c percentage of total hemoglobin from 8.0% to 13.0%, a participating caregiver, and no other serious medical conditions. From January 5, 2014, to April 4, 2016, 258 adolescents were recruited. The post hoc analysis excluded adolescents missing outcome measures at 18 months (2 participants [0.8%]) or continuous glucose monitoring data at baseline (40 participants [15.5%]). Data were analyzed from April to December 2018.

INTERVENTIONS

The FLEX intervention included a behavioral counseling strategy that integrated motivational interviewing and problem-solving skills training to increase adherence to diabetes self-management. The control condition entailed usual diabetes care.

MAIN OUTCOMES AND MEASURES

Subgroups of FLEX participants were derived from an ITR estimating which participants would benefit from intervention, which would benefit from control conditions, and which would be indifferent. Multiple imputation by chained equations and reinforcement learning trees were used to estimate the ITR. Subgroups based on ITR pertaining to changes during 18 months in 3 univariate outcomes (ie, HbA1c percentage, QoL, and BMIz) and a composite outcome were compared by baseline demographic, clinical, and psychosocial characteristics.

RESULTS

Data from 216 adolescents in the FLEX trial were reanalyzed (166 [76.9%] non-Hispanic white; 108 teenaged girls [50.0%]; mean [SD] age, 14.9 [1.1] years; mean [SD] diabetes duration, 6.3 [3.7] years). For the univariate outcomes, a large proportion of FLEX participants had equivalent predicted outcomes under intervention vs usual care settings, regardless of randomization, and were assigned to the muted group (HbA1c: 105 participants [48.6%]; QoL: 63 participants [29.2%]; BMIz: 136 participants [63.0%]). Regarding the BMIz univariate outcome, mean baseline BMIz of participants assigned to the muted group was lower than that of those assigned to the intervention and control groups (muted vs intervention: mean difference, 0.48; 95% CI, 0.21 to 0.75; P = .002; muted vs control: mean difference, 0.86; 95% CI, 0.61 to 1.11; P < .001); this group also had a higher proportion of individuals with underweight or normal weight using weight status cutoffs (95 [69.9%] in muted group vs 24 [54.6%] in intervention group and 11 [30.6%] in control group; χ24 = 24.67; P < .001). The approach identified subgroups estimated to benefit based on HbA1c percentage (54 participants [25.0%]), QoL (89 participants [41.2%]), and BMIz (44 participants [20.4%]). Regarding the HbA1c percentage outcome, participants expected to benefit from the intervention did not have significantly higher baseline HbA1c percentages than those expected to benefit from usual care (9.4% vs 9.2%; difference, 0.2%; 95% CI, -0.16% to 0.56%; P = .44). However, participants in the muted group had higher mean HbA1c percentages at baseline than those assigned to the intervention or control groups (muted vs intervention: 9.9% vs 9.4%; difference, 0.5%; 95% CI, 0.13% to 0.89%; P = .02; muted vs control; 9.9% vs 9.2%; difference, 0.7%; 95% CI, 0.34% to 1.08%; P = .001). No significant differences were found between subgroups estimated to benefit in terms of the composite outcome from the FLEX intervention (91 participants [42.1%]) vs usual care (125 participants [57.9%]).

CONCLUSIONS AND RELEVANCE

The precision medicine approach represents a conceptually and analytically novel approach to post hoc subgroup identification. More work is needed to understand markers of positive response to the FLEX intervention.

TRIAL REGISTRATION

ClinicalTrial.gov identifier: NCT01286350.

Text-message responsiveness to blood glucose monitoring reminders is associated with HbA1c benefit in teenagers with Type 1 diabetes

AIMS

To evaluate an 18-month text-messaging intervention in teenagers with Type 1 diabetes and to assess factors associated with text responsiveness and glycaemic benefit.

METHODS

Teenagers with diabetes (N = 147), aged 13-17 years, received two-way text reminders at self-selected times to check blood glucose levels and reply with blood glucose results.

RESULTS

At baseline, the participants (48% boys, 78% white, 63% pump-treated) had a mean ± sd age of 14.9 ± 1.3 years, diabetes duration of 7.1 ± 3.9 years and HbA_1c concentration of 69 ± 12 mmol/mol (8.5 ± 1.1%). The mean proportion of days with ≥1 blood glucose response declined over time (0-6 months, 60 ± 26% of days, 7-12 months, 53 ± 31% of days, 13-18 months, 43 ± 33% of days). Over 18 months, 49% responded with ≥1 blood glucose result on ≥50% of days (high responders). Regression analysis controlling for baseline HbA_1c revealed no significant change in HbA_1c from baseline to 18 months in high responders (P = 0.54) compared with a significant HbA_1c increase in low responders (+0.3%, P = 0.01). In participants with baseline HbA_1c ≥64 mmol/mol (≥8%), high responders were 2.5 times more likely than low responders to have a clinically significant [≥5.5 mmol/mol (≥0.5%)] HbA_1c decrease over 18 months (P < 0.05). In participants with baseline HbA_1c <64 mmol/mol(<8%), high responders were 5.7 times more likely than low responders to have an 18-month HbA_1c <58 mmol/mol (<7.5%; P < 0.05).

CONCLUSIONS

Teenagers with Type 1 diabetes who responded to text reminders on ≥50% of days over 18 months experienced clinically significant glycaemic benefit. There remains a need to tailor interventions to maintain teenager engagement and optimize improvements.

Socioeconomic status moderates the association between patient satisfaction with community health service and self-management behaviors in patients with type 2 diabetes: A cross-sectional survey in China

The objective of this study was to examine the association between patient satisfaction with community health service (CHS) and self-management behaviors in patients with type 2 diabetes mellitus (T2DM).In all, 1691 patients with T2DM from 8 community health centers in 5 provinces in China participated in the present study. The dependent variables included 4 measures of self-management behaviors: regular self-monitoring of blood glucose (SMBG), prescribed medication adherence, recommended dietary changes, and regular exercise. The independent variable was patient satisfaction with CHS. Multivariable logistic regression models were performed to examine the association between patient satisfaction with CHS and self-management behaviors.The mean satisfaction score in the participants was 3.14 (out of a maximum of 5). After adjusting for covariates including demographic factors, health status, health knowledge, and socioeconomic status (SES), diabetic patients with high CHS satisfaction had better medication adherence (odds ratio [OR] 1.25, 95% confidence interval [CI] 1.02-1.55), increased exercise management (OR 1.19, 95% CI 1.06-1.35), and more SMBG (OR 1.16, 95% CI 1.03-1.32); all these associations varied across SES groups. The association between satisfaction and medication adherence was significant among participants younger than 65 years with lower education (OR 2.15, 95% CI 1.37-3.37), income (OR 1.62, 95% CI 1.13-2.32), and lower-status occupations (OR 1.69, 95% CI 1.16-2.47). Among participants younger than 65 years and had lower education attainment, the association between satisfaction and diet management was observed. There were positive associations between satisfaction and regular exercise among subgroups of participants younger than 65 years, except for lower education group. A significant association between satisfaction and SMBG among participants ≥65 years old, who also had lower SES and higher-status occupations, was also observed.The study findings suggested that T2DM patient satisfaction with CHS was moderate. High satisfaction with CHS indicated better medication adherence, exercise management, and SMBG, and these associations varied by SES.

Evaluation of health utility values for diabetic complications, treatment regimens, glycemic control and other subjective symptoms in diabetic patients using the EQ-5D-5L

AIMS

This study aimed to reveal health utility values for diabetic complications and treatment regimens with adjustment for glycemic control and other clinical manifestations in a diabetic population.

METHODS

The EuroQol 5-Dimension 5-Level (EQ-5D-5L) health utility values for 4963 Japanese diabetic patients were analyzed using a multivariate regression model including major complications and treatment regiments (minimally adjusted model), and that additionally included glycemic control and other subjective symptoms (musculoskeletal, dental, respiratory, gastrointestinal, urinary, and cutaneous symptoms, and hearing impairment) (further adjusted model).

RESULTS

The mean utility value was 0.901 ± 0.137. In the minimally adjusted model, blindness, overt nephropathy, regular dialysis, cardiac symptom, sequelae of stroke, symptomatic peripheral neuropathy, decreased sensation, claudication, foot ulcer/gangrene, major amputation, and complex treatment regimens were significantly associated with lower utility values, whereas proliferative retinopathy without blindness, coronary artery disease without cardiac symptom, sequela-free cerebrovascular disease, asymptomatic peripheral artery disease, and minor amputation were not. Major complications and treatment regimens that showed significant association in the minimally adjusted model still presented significant impact on the utility decrement in the further adjusted model. However, most of their regression coefficients were lower in absolute value compared to those in the minimally adjusted model.

CONCLUSIONS

The utility decrement related to each diabetic complication varied with its severity and accompanying symptoms. Complex treatment regimens were independently associated with lower utility values. The utility decrement associated with diabetic complication and complex treatment regimens would be overestimated in the analysis without adjustment for glycemic control or other subjective symptoms.

Continuous Glucose Monitoring Linked to an Artificial Intelligence Risk Index: Early Footprints of Intraventricular Hemorrhage in Preterm Neonates

OBJECTIVE

To develop and validate a new risk score for intraventricular hemorrhage (IVH) in preterm neonates based on continuous glucose monitoring (CGM).

STUDY DESIGN

We retrospectively analyzed CGM traces obtained from 50 very preterm neonates, grouped into two sub-cohorts started on CGM within 12 and 48 h of birth, respectively. A CGM linked to an Artificial Intelligence Risk (CLAIR) index was developed to quantify glucose variability during the first 72 h of life in neonates with and without IVH. Brain-US was performed at least twice a day for the first 5 days of birth. An integrated remote monitoring platform was developed to capture major clinical events in real time and gather data for the risk index. The new score performance was further compared with other measures of glucose variability (coefficient of variation [CV] and standard deviation [SD]) and with a clinical risk index for babies II (CRIB-II) as a predictor of IVH event. The two cohorts were analyzed separately for internal validation of the method.

RESULTS

The primary cohort consisted of 26 neonates (gestational age 30 [28, 31] weeks; BW1275 g[1090, 1750]). Controls (n = 23) exhibited higher CLAIR index than cases (P = 0.004). A cut-off of 0.69 for the new CLAIR index allowed a 100% sensitivity and an 83% specificity for IVH prediction. The CLAIR index was the sole significant predictor for IVH (P = 0.003) when compared with clinical variables, CV, SD, and CRIB-II. In a subgroup analysis in very low-birth-weight infants, the CLAIR index was the sole variable significantly associated with IVH (P = 0.009). Analysis on the secondary cohort (five cases and 16 controls) confirmed a higher CLAIR index in the controls (P = 0.008), in the absence of a difference for CV, SD, and CRIB-II between the two groups.

CONCLUSION

CGM, combined with the AI-algorithm, provides a high-sensitivity index for risk detection of IVH that reflects the glycemic impairment preceding IVH.

Frequency of self-monitoring of blood glucose in relation to weight loss and A1C during intensive multidisciplinary weight management in patients with type 2 diabetes and obesity

OBJECTIVE

We evaluated the relationship between frequency of self-monitoring of blood glucose (SMBG) and body weight, A1C, and cardiovascular risk factors in patients with type 2 diabetes (T2D) and obesity enrolled in a 12-week intensive multidisciplinary weight management (IMWM) program.

RESEARCH DESIGN AND METHODS

We conducted a retrospective analysis of 42 patients who electronically uploaded their SMBG data over 12 weeks of an IMWM program and divided them into tertiles based on their average frequency of SMBG per day. Mean (range) SMBG frequencies were 2.3 (1.1-2.9) times/day, 3.4 (3-3.9) times/day, and 5 (4-7.7) times/day in the lowest, middle, and highest tertiles, respectively. Anthropometric and metabolic parameters were measured at baseline and after 12 weeks of intervention.

RESULTS

Participants in the highest tertile achieved a median change (IQR) in body weight of -10.4 kg (-7.6 to -14.4 kg) compared with -8.3 kg (-5.2 to -12.2 kg), and -6.9 kg (-4.2 to -8.9 kg) in the middle and lowest tertiles, respectively (p=0.018 for trend). Participants in the highest tertile had a median change (IQR) in A1C of -1.25% (-0.6 to -3.1%) compared with -0.8% (-0.3% to -2%) and -0.5% (-0.2% to -1.2%) in the middle and lowest tertiles, respectively (p=0.048 for trend). The association between change in body weight and SMBG frequency remained significant after adjusting for age, sex, baseline body mass index, diabetes duration, and use of insulin therapy.

CONCLUSIONS

Increased frequency of SMBG during IMWM is associated with significantly better weight loss and improvement of A1C in patients with T2D and obesity. These findings may suggest future clinical recommendations aimed at increasing SMBG frequency to achieve the most favorable outcomes.

Asymptomatic hypoglycaemia in Type 1 diabetes: incidence and risk factors

AIM

The epidemiology of asymptomatic (silent) hypoglycaemia is not well-described. We investigated incidence and risk factors for asymptomatic hypoglycaemia in Type 1 diabetes.

METHODS

A cohort of 153 people with Type 1 diabetes participated in 6 days of blinded continuous glucose monitoring (CGM) and recording of hypoglycaemia symptoms. At entry, hypoglycaemia awareness was classified (by three different methods) and HbA_1c and C-peptide were measured. Hypoglycaemic episodes were defined as interstitial glucose ≤ 3.9 mmol/l (IG_3.9 ) or ≤ 3.0 mmol/l (IG_3.0 ) for ≥ 15 min, and were considered asymptomatic if no hypoglycaemic symptoms were reported.

RESULTS

At thresholds IG_3.9 and IG_3.0 , the incidence rates of hypoglycaemic episodes were 5.0 (7.9) [median (IQR)] and 1.3 (3.4) episodes/person-week, respectively. Three-quarters of episodes were asymptomatic. In total, 77% and 52% of participants experienced one or more episode of asymptomatic hypoglycaemia at IG_3.9 and IG_3.0 [3.0 (6.2) and 1.0 (2.3) asymptomatic episodes/person-week]. At multivariate analysis, reduced awareness was positively associated with asymptomatic hypoglycaemia, particularly nocturnal events, and negatively with symptomatic hypoglycaemia. High insulin dose was associated with increased risk of both asymptomatic and symptomatic hypoglycaemia, whereas low HbA_1c and long diabetes duration were risk factors only for symptomatic hypoglycaemia.

CONCLUSIONS

Asymptomatic hypoglycaemia constitutes the majority of hypoglycaemic events in Type 1 diabetes. Reduced hypoglycaemia awareness and high insulin dose are risk factors for asymptomatic hypoglycaemia but other conventional risk factors for severe hypoglycaemia do not correlate with risk of asymptomatic episodes.

Regular performance feedback may be key to maintain good quality DKA management: results from a five-year study

OBJECTIVES

We postulate that performance feedback is a prerequisite to ensure sustained improvement in diabetic ketoacidosis (DKA) management.

DESIGN

The study was based on 'theory of change' concept that suggests changes of primary drivers determine the main outcome. A set of secondary drivers can be implemented to achieve improvements in these primary drivers and thus the main outcome.

SETTING

This study was conducted at a large tertiary care center in the West Midlands, UK. The region has above average prevalence of diabetes and DKA admissions in the country.

PARTICIPANTS

All participants diagnosed with DKA as per national guidelines, except those managed in intensive care unit from April 2014 to March 2018, were included in this study.

INTERVENTIONS

Monthly feedback of performance was the main intervention. Development of a real-time live DKA audit tool, automatic referral system of DKA to the specialist team, electronic monitoring of blood gas measurements and education and redesigning of local (trust) guidelines were the other interventions in this study.

MAIN OUTCOME MEASURES

Total DKA duration, appropriateness of fixed rate intravenous insulin infusion, fluid prescription, glucose monitoring, ketone monitoring and referral to specialists.

RESULTS

There was a significant reduction in the duration of DKA postintervention compared with baseline results. However, in the absence of regular feedback, the duration of DKA showed an upward trend nearing baseline values. Similar trends were noted in secondary drivers influencing DKA duration.

CONCLUSION

Based on these results, we recommend regular audit and feedback is required to sustain improvements in DKA management.

Real-world practice level data analysis confirms link between variability within Blood Glucose Monitoring Strip (BGMS) and glycosylated haemoglobin (HbA1c) in Type 1 Diabetes

AIMS/HYPOTHESIS

Our aim was to quantify the impact of Blood Glucose Monitoring Strips variability (BGMSV) at GP practice level on the variability of reported glycated haemoglobin (HbA1cV) levels.

METHODS

Overall GP Practice BGMSV and HbA1cV were calculated from the quantity of main types of BGMS being prescribed combined with the published accuracy, as % results within ±% bands from reference value for the selected strip type. The regression coefficient between the BGMSV and HbA1cV was calculated. To allow for the aggregation of estimated three tests/day over 13 weeks (ie, 300 samples) of actual Blood Glucose (BG) values up to the HbA1c, we multiplied HbA1cV coefficient by √300 to estimate an empirical value for impact of BGMSV on BGV.

RESULTS

Four thousand five hundred and twenty-four practice years with 159 700 T1DM patient years where accuracy data were available for more than 80% of strips prescribed were included, with overall BGMSV 6.5% and HbA1c mean of 66.9 mmol/mol (8.3%) with variability of 13 mmol/mol equal to 19% of the mean. At a GP practice level, BGMSV and HbA1cV as % of mean HbA1c (in other words, the spread of HbA1c) were closely related with a regression coefficient of 0.176, P < 0.001. Thus, greater variability in the BGMS at a GP practice level resulted in a greater spread of HbA1C readings in T1DM patients. Applying this factor for BGMS to the national ISO accepted standard where 95% results must be ≤±15% from reference, revealed that for BG, 95% results would be ≤±45% from the reference value. Thus, the variation in BG is three times that of the BGMS. For a patient with BG target @10 mmol/L using the worst performing ISO standard strips, on 1/20 occasions (average 1/week) actual blood glucose value could be >±4.5 mmol/L from target, compared with the best performing BGMS with BG >±2.2 mmol/L from reference on 1/20 occasions.

CONCLUSION

Use of more variable/less accurate BGMS is associated both theoretically and in practice with a larger variability in measured BG and HbA1c, with implications for patient confidence in their day-to-day monitoring experience.