Self-Monitoring of Blood Glucose in Youth-Onset Type 2 Diabetes: Results From the TODAY Study

A practical evidence-based approach to management of type 2 diabetes in children and young people (CYP): UK consensus

BACKGROUND

Type 2 diabetes in young people is an aggressive disease with a greater risk of complications leading to increased morbidity and mortality during the most productive years of life. Prevalence in the UK and globally is rising yet experience in managing this condition is limited. There are no consensus guidelines in the UK for the assessment and management of paediatric type 2 diabetes.

METHODS

Multidisciplinary professionals from The Association of Children's Diabetes Clinicians (ACDC) and the National Type 2 Diabetes Working Group reviewed the evidence base and made recommendations using the Grading Of Recommendations, Assessment, Development and Evaluation (GRADE) methodology.

RESULTS AND DISCUSSION

Young people with type 2 diabetes should be managed within a paediatric diabetes team with close working with adult diabetes specialists, primary care and other paediatric specialties. Diagnosis of diabetes type can be challenging with many overlapping features. Diabetes antibodies may be needed to aid diagnosis. Co-morbidities and complications are frequently present at diagnosis and should be managed holistically. Lifestyle change and metformin are the mainstay of early treatment, with some needing additional basal insulin. GLP1 agonists should be used as second-line agents once early ketosis and symptoms are controlled. Glycaemic control improves microvascular but not cardiovascular risk. Reduction in excess adiposity, smoking prevention, increased physical activity and reduction of hypertension and dyslipidaemia are essential to reduce major adverse cardiovascular events.

CONCLUSIONS

This evidence-based guideline aims to provide a practical approach in managing this condition in the UK.

Barriers and Facilitators to Uptake of Continuous Glucose Monitoring for Management of Type 2 Diabetes Mellitus in Youth

PURPOSE

The purpose of this study was to identify factors impacting the acceptability of continuous glucose monitoring (CGM) in adolescents and young adults (AYAs) with type 2 diabetes mellitus (T2DM).

METHODS

In this single-center study, semistructured interviews were conducted with AYAs with T2DM and their parents to determine attitudes about CGM, including barriers and facilitators. Interviews were audio-recorded, transcribed, and evaluated using thematic analysis.

RESULTS

Twenty AYAs and 10 parents participated (n = 30 total). AYAs were mean age 16.5 years (SD 2.2, range = 13.7-20.1) and had median diabetes duration of 1.3 years. Most were female (65%) and from minoritized background (40% non-Hispanic Black, 10% Hispanic, 5% Asian). Seven (35%) used CGM. The primary facilitator elicited was convenience over glucose meter use. Important barriers included the impact of physically wearing the device and drawing unwanted attention, desire for AYA privacy, and inadequate education about the device.

CONCLUSIONS

In this diverse sample of AYAs with T2DM and their parents, CGM was generally regarded as convenient, although concerns about worsening stigma and conflict with parents were prevalent. These findings can guide the development of patient-centered approaches to CGM for AYAs with T2DM, a critical step toward reducing inequities in diabetes technology uptake.

Telemedicine-assisted structured self-monitoring of blood glucose in management of T2DM results of a randomized clinical trial

BACKGROUND

This prospective study aimed to compare telemedicine-assisted structured self-monitoring of blood glucose(SMBG) with a traditional blood glucose meter (BGM) in adults of type 2 diabetes mellitus (T2DM).

METHODS

Adult participants with T2DM were assigned to an intervention group or a control group. The patients in the intervention group received a connected BGM with real-time data submission as well as individual needs-based tele-coaching to address and improve motivation and daily diabetes self-management. The patients in the control group received a traditional BGM. Changes in glycated hemoglobin(HbA1c), low blood glucose index(LBGI), and diabetes self-management behaviors were analyzed.

RESULTS

The study demonstrated the superiority of the telemedicine-assisted structured SMBG versus the traditional BGM for improving HbA1c. Additionally, the telemedicine-assisted SMBG reduced the risk of hypoglycemia and enhanced diabetes self-management behaviors, as differences in the LBGI and the Diabetes Self-Management Questionnaire(DSMQ) results between the groups after 6 months were found to be significant.

CONCLUSIONS

Telemedicine-assisted structured SMBG helps physicians and patients to achieve a specific level of glycemic control and reduce hypoglycemia. The use of coaching applications and telemedicine-assisted SMBG indicated beneficial effects for T2DM self-management, which may help limit disease progression.

TRIAL REGISTRATION

Chinese Clinical Trail Registry No: ChiCTR2300072356 on 12/06/2023. Retrospectively registered.

Efficacy and safety of closed-loop control system for type one diabetes in adolescents a meta analysis

This meta-analysis compares the efficacy and safety of Closed-Loop Control (CLC) to Sensor-Augmented Insulin Pump (SAP) for adolescent patients with Type 1 Diabetes Mellitus (T1DM). Eleven randomized-controlled trials were included with a total of 570 patients, from a total of 869 articles found adhering to PRISMA guidelines. The efficacy of the therapies were evaluated from the day, night and during physical activities monitoring of the of the mean blood glucose (BG), Time In Range (TIR), and Standard Deviation (SD) of the glucose variability. The safety measure of the therapies, was assessed from the day and night recording of the hypoglycemic and hyperglycemic events occurred. Pooled results of comparison of mean BG values for day, night and physical activities, - 4.33 [- 6.70, - 1.96] (P = 0.0003), - 16.61 [- 31.68, - 1.54] (P = 0.03) and - 8.27 [- 19.52, 2.99] (P = 0.15). The monitoring for day, night and physical activities for TIR - 13.18 [- 19.18, - 7.17] (P < 0.0001), - 15.36 [- 26.81, - 3.92] (P = 0.009) and - 7.39 [- 17.65, 2.87] (P = 0.16). The day and night results of SD of glucose variability was - 0.40 [- 0.79, - 0.00] (P = 0.05) and - 0.86 [- 2.67, 0.95] (P = 0.35). These values shows the superiority of CLC system in terms of efficacy. The safety evaluation, of the day, night and physical activities observations of average blood glucose goal hypoglycemic events - 0.54 [- 1.86, 0.79] (P = 0.43), 0.04 [- 0.20, 0.27] (P = 0.77) and 0.00 [- 0.25, 0.25] (P = 1.00) and hyperglycemic events - 0.04 [- 0.20, 0.27] (P = 0.77), - 7.11 [- 12.77, - 1.45] (P = 0.01) and - 0.00 [- 0.10, 0.10] (P = 0.97), highlights the commendable safety factor of CLC. The CLC systems can be considered as an ideal preference in the management of adolescents with type 1 diabetes to be used during a 24 h basis.

The association between self-monitoring of blood glucose and HbA1c in type 2 diabetes

AIMS

Fasting capillary blood glucose (FCG) and postprandial capillary blood glucose (PCG) both contribute to HbA1c in diabetes. Due to the collinearity between FCG and PCG, the HbA1c prediction model could not be developed with both FCG and PCG by linear regression. The study aimed to develop an HbA1c prediction model with both FCG and PCG to estimate HbA1c in type 2 diabetes.

METHODS

A total of 1,642 patients with type 2 diabetes who had at least three FCG and three PCG measurements in the past 3 months were enrolled in the study. The mean of FCG (MEAN_FCG) and PCG (MEAN_PCG) were calculated for each patient. The patients were randomized into exploratory and validation groups. The former was used for developing HbA1c prediction models and the latter for performance evaluation.

RESULTS

The new HbA1c prediction model using ridge regression expressed as HbA1c (%) = 0.320×MEAN_FCG (mmol/L) + 0.187×MEAN_PCG (mmol/L) + 2.979, R² = 0.668. Compared to linear regression models developed with FCG, PCG, fasting plasma glucose (FPG), and 2-hour postprandial plasma glucose (2-h PPG), respectively, the new HbA1c prediction model showed the smallest mean square error, root mean square error, mean absolute error. The concordance correlation coefficient of the new HbA1c prediction model and the linear regression models with MEAN_FCG, MEAN_PCG, FPG or 2-h PPG were 0.810,0.773,0.749,0.715,0.672.

CONCLUSION

We have developed a new HbA1c prediction model with both FCG and PCG, which showed better prediction ability and good agreement.

Time in Range Assessed by Capillary Blood Glucose in Relation to Insulin Sensitivity and β-Cell Function in Patients with Type 2 Diabetes Mellitus: A Cross-Sectional Study in China

AIMS

This study investigated the association of capillary blood glucose (CBG)-assessed time in range (TIR) (3.9-10.0 mmol/L) with insulin sensitivity and islet β-cell function (BCF).

MATERIALS AND METHODS

We recruited 455 patients with type 2 diabetes mellitus. Seven-point glucose-profile data (pre- and 120-min post-main meals, bedtime) were collected over three consecutive days. Plasma glucose and serum insulin concentrations were measured at 0, 60, and 120 min after a 100-g standard steamed bread meal test. The homeostasis model assessment of insulin resistance (HOMA-IR) and Matsuda index were computed to evaluate insulin resistance (IR). HOMA of β-cell function (HOMA-β) and the area under the curve between insulin and blood glucose (IAUC_0-120 /GAUC_0-120 ) were used to estimate BCF.

RESULTS

TIR was positively correlated with 60- and 120-min insulin values, IAUC_0-120 , the Matsuda index, HOMA-β, and IAUC_0-120 /GAUC_0-120 (r_s : 0.154, 0.129, 0.137, 0.194, 0.341, and 0.334, respectively; P <0.05) but inversely correlated with HOMA-IR (r_s : -0.239, P <0.001). After adjusting for confounders, multinomial multiple logistic regression analysis revealed that the odds ratios (ORs) of achieving the target TIR (>70%) increased by 12% (95% confidence interval [CI]: 3-21%), 7% (95% CI: 1-14%), 10% (95% CI: 5-16%), and 45% (95% CI: 25-68%) for each 10-mIU/L increase in 60- and 120-min insulin value, 10-unit increase in HOMA-β, and unit increase in IAUC_0-120 /GAUC_0-120 , respectively (P <0.05). Nevertheless, the OR decreased by 10% (95% CI: 1-18%) for each unit increase in HOMA-IR (P <0.05).

CONCLUSIONS

IR and BCF are related to CBG-assessed TIR.

Sex-Specific Associations Between Low Muscle Mass and Glucose Fluctuations in Patients With Type 2 Diabetes Mellitus

OBJECTIVE

Studies have shown that sex differences in lean mass, concentrations of sex hormones, and lifestyles influence cle health and glucose metabolism. We evaluated the sex-specific association between low muscle mass and glucose fluctuations in hospitalized patients with type 2 diabetes mellitus (T2DM) receiving continuous subcutaneous insulin infusion (CSII) therapy.

METHODS

A total of 1084 participants were included. Body composition was determined by dual-energy X-ray absorptiometry. Intraday blood glucose fluctuation was estimated by the Largest amplitude of glycemic excursions (LAGE) and standard deviation of blood glucose (SDBG).

RESULTS

The prevalence of low muscle mass was higher in males than in females (p<0.001). There was a significant sex-specific interaction between the status of low muscle mass and glucose fluctuations (LAGE and SDBG) (p for interaction=0.025 and 0.036 for SDBG and LAGE, respectively). Among males, low muscle mass was significantly associated with a higher LAGE and SDBG (difference in LAGE: 2.26 [95% CI: 1.01 to 3.51], p < 0.001; difference in SDBG: 0.45 [95% CI: 0.25 to 0.65], p < 0.001) after adjustment for HbA1c, diabetes duration, hyperlipidemia, diabetic peripheral neuropathy, diabetic nephropathy, and cardiovascular disease. These associations remained significant after further adjustment for age and C-peptide. Among females, low muscle mass was not associated with LAGE or SDBG after adjustment for all covariates.

CONCLUSION

The prevalence of low muscle mass was higher in males than in females. Low muscle mass was significantly associated with higher LAGE and SDBG among males, but not females.

Distinct associations of self-monitoring of blood glucose with glycemic control and hypoglycemia between groups of recently diagnosed and long-term follow-up type 2 diabetes: The Taiwan Diabetes Registry

BACKGROUND

We investigated the uses and frequency of self-monitoring of blood glucose (SMBG) with glycemic control and hypoglycemia in two groups of type 2 diabetes (T2D) (recently diagnosed and long-term follow-up) using real-world data in Taiwan (the Taiwan Diabetes Registry).

METHODS

Patients with T2D recently diagnosed within 6 months (n = 3297, mean age 54.4 ± 13.9 years) and T2D patients with long-term follow-up (n = 1201, mean age 65.5 ± 12.1 years, mean diabetes duration 14.3 ± 7.8 years) from the Taiwan Diabetes Registry were analysed. All patients were interviewed by certified diabetes educators. Information about SMBG and hypoglycemia was recorded. Demography, personal history, and laboratory data were obtained from electronic medical records. Logistic regression analyses were used to examine the associations of SMBG with glycated haemoglobin (HbA1c) <7% and hypoglycemia.

RESULTS

Mean HbA1c values were 8.4 ± 2.5 and 7.6 ± 1.4%, respectively, in the recently diagnosed and long-term follow-up T2D groups. The self-reported rates of hypoglycemic events within 3 months were 10.5% and 19.0%, respectively. SMBG was associated with higher odds of HbA1c <7% (OR 1.21, 95% CI 1.01-1.44) in patients with recently diagnosed T2D, but with lower odds of HbA1c <7% in T2D patients with long-term follow-up (OR 0.60, 95% CI 0.44-0.82). In both study populations, SMBG was independently associated with hypoglycemia (OR 3.90 [95% CI 2.99-5.08] and OR 3.93 [95% CI 2.73-5.66], respectively). The aforementioned findings were consistent across the strata of SMBG frequency.

CONCLUSION

We reported different associations between SMBG and glycemic control in patients recently diagnosed with T2D and in T2D patients with long-term follow-up. SMBG was associated with higher detection of hypoglycemic episodes in both study populations.

American Association of Clinical Endocrinology Clinical Practice Guideline: The Use of Advanced Technology in the Management of Persons With Diabetes Mellitus

OBJECTIVE

To provide evidence-based recommendations regarding the use of advanced technology in the management of persons with diabetes mellitus to clinicians, diabetes-care teams, health care professionals, and other stakeholders.

METHODS

The American Association of Clinical Endocrinology (AACE) conducted literature searches for relevant articles published from 2012 to 2021. A task force of medical experts developed evidence-based guideline recommendations based on a review of clinical evidence, expertise, and informal consensus, according to established AACE protocol for guideline development.

MAIN OUTCOME MEASURES

Primary outcomes of interest included hemoglobin A1C, rates and severity of hypoglycemia, time in range, time above range, and time below range.

RESULTS

This guideline includes 37 evidence-based clinical practice recommendations for advanced diabetes technology and contains 357 citations that inform the evidence base.

RECOMMENDATIONS

Evidence-based recommendations were developed regarding the efficacy and safety of devices for the management of persons with diabetes mellitus, metrics used to aide with the assessment of advanced diabetes technology, and standards for the implementation of this technology.

CONCLUSIONS

Advanced diabetes technology can assist persons with diabetes to safely and effectively achieve glycemic targets, improve quality of life, add greater convenience, potentially reduce burden of care, and offer a personalized approach to self-management. Furthermore, diabetes technology can improve the efficiency and effectiveness of clinical decision-making. Successful integration of these technologies into care requires knowledge about the functionality of devices in this rapidly changing field. This information will allow health care professionals to provide necessary education and training to persons accessing these treatments and have the required expertise to interpret data and make appropriate treatment adjustments.

Clinical Inertia and 2-Year Glycaemic Trajectories in Patients with Non-Newly Diagnosed Type 2 Diabetes Mellitus in Primary Care: A Retrospective Cohort Study

OBJECTIVE

To analyse diabetes treatment, treatment change and self-management behaviours in association with 2-year glycaemic trajectories in patients with non-newly diagnosed type 2 diabetes mellitus in Chinese primary care.

METHODS

This was an observational, multi-centre, longitudinal, retrospective cohort study. Clinical data of 4690 subjects were extracted from electronic medical records, including serial glycated haemoglobin A_1c (HbA_1c) measurements, antidiabetic medication records and compliance to exercise, diet, medications and self-monitoring of blood glucose (SMBG). Patterns of longitudinal HbA1c trajectories were identified using the percentage of HbA_1c measurements <7.5% from the second available HbA_1c measurement. Clinical relevance of the clusters was assessed through multivariable analysis.

RESULTS

Approximately half of the participants demonstrated good glycaemic control; of these, 34.5% demonstrated stable, good control, and 13.7% demonstrated relatively good control. About 16.2% demonstrated moderate control, and 35.6% demonstrated poor control. From the good to poor control groups, the percentage of subjects treated with insulin at baseline and during the follow-up period increased gradually, while the percentage of subjects adhering to exercise, diet, medications and SMBG decreased gradually. Compared with baseline, the adherence to exercise, diet, medications and SMBG improved significantly. Approximately 50% and 26% of subjects in the two poorest control groups, respectively, experienced treatment changes. After multivariable adjustments, baseline HbA_1c ≥7.5%, HbA_1c change ≥-0.5% from baseline to visit 1, insulin treatment, treatment change, poor adherence to diet, exercise, SMBG during the follow-up period and HbA_1c measurements <3 per year were significantly associated with poorer glycaemic control.

CONCLUSION

We identified four longitudinal HbA_1c trajectories in patients with non-newly diagnosed type 2 diabetes. Even if baseline HbA_1c is suboptimal, aggressive treatment changes, good adherence during the follow-up period, ≥3 HbA_1c measurements per year and reducing HbA_1c levels to a certain extent by the first follow-up visit were important for good, stable, long-term glycaemic control.

Health Care Coverage and Glycemic Control in Young Adults With Youth-Onset Type 2 Diabetes: Results From the TODAY2 Study

OBJECTIVE

To examine the relationship between health care coverage and HbA_1c in young adults with youth-onset type 2 diabetes who transitioned to community diabetes care after receiving care during the Treatment Options for type 2 Diabetes in Adolescents and Youth (TODAY) study.

RESEARCH DESIGN AND METHODS

Participants completed questionnaires annually. HbA_1c was measured in a central laboratory. Data from 2 years before and after transitioning to community care (2013-2016) were examined and compared between states with and without expanded Medicaid.

RESULTS

In 2016 (n = 427; mean age 24 years), 2 years after transitioning to community care, 93% of participants in states with Medicaid expansion had health care coverage compared with 68% (P < 0.0001) in states without Medicaid expansion. Mean HbA_1c was 9.8% in participants with government coverage, 9.3% with commercial coverage, and 10.1% in those with no coverage (P = 0.0774). Additionally, 32%, 42%, and 66% of those with government coverage, commercially covered, and no coverage, respectively, were not attending outpatient diabetes visits (P < 0.0001). Of those with government coverage, 83% reported they had adequate coverage for insulin syringes/needles/pens, and 89% for glucose-monitoring supplies, with more limited coverage in those with commercial plans. Participants with commercial coverage had higher education attainment (P < 0.0001); 52% had HbA_1c ≥9.0% compared with 64% of those who were government covered and 58% with no coverage (P = 0.0646).

CONCLUSIONS

More young adults with type 2 diabetes from the TODAY cohort had health care coverage in states with expanded Medicaid but glycemic control remained poor, regardless of coverage. New therapies and approaches are needed for this vulnerable population.

Glycemic variability indices determined by self-monitoring of blood glucose are associated with β-cell function in Chinese patients with type 2 diabetes

INTRODUCTION

Glycemic control plays an important role in diabetes management, and self-monitoring of blood glucose (SMBG) is critical to achieving good glycemic control. However, there are few studies about the relationship between SMBG-estimated glycemic indices and β-cell function. Here we investigated the association between glucose variation indices estimated by SMBG and β-cell function among Chinese patients with type 2 diabetes mellitus (T2DM).

METHODS

In this cross‑sectional study, 397 patients with T2DM were recruited from February 2015 to October 2016. β-cell function was monitored using the Homeostasis Model Assessment 2 (HOMA2)-%β index. The parameters evaluated by SMBG were the mean blood glucose (MBG), standard deviation of MBG (SDBG), largest amplitude of glycemic excursions (LAGE), and postprandial glucose excursion (PPGE).

RESULTS

HOMA2-%β was negatively correlated with SDBG, LAGE, PPGE, and MBG (r = -0.350, -0.346, -0.178, and -0.631, respectively; all p < 0.01). After adjusting for confounding characteristics (diabetic duration, triglyceride, total cholesterol, fasting C-peptide, HOMA2-insulin resistance index, hypoglycemia, and diabetic treatments) and glycated hemoglobin A1c on a continuous scale, odds ratios of SDBG, LAGE, PPGE, and MBG between the patients in the lowest and highest HOMA2-%β quartiles were 2.02 (1.14-3.57), 1.24 (1.04-1.49), 1.13 (0.86-1.51), and 2.26 (1.70-3.00). HOMA2-%β was independently associated with SDBG, LAGE, and MBG.

CONCLUSIONS

Increased SDBG and LAGE assessed by SMBG are associated with β-cell dysfunction in Chinese patients with T2DM.