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

Quality of Life of Elementary School Students with Type 1 Diabetes in a Developing Country during the COVID Pandemic

Type 1 diabetes (T1D) is a condition that affects all aspects of life, and thus is closely related to the quality of life itself. Dealing with it during the COVID-19 pandemic is a big challenge. A case-control study conducted in Montenegro at the end of 2021 included 87 elementary school students with T1D and 248 of their peers as controls matched by gender. Standardized questionnaires were distributed to participants (Peds-QL Generic core 4.0 questionnaire for all participants and Peds-QL Diabetes Module 3.2 only for cases). Based on them, the results of obtained scores were measured and compared using non-parametric statistical methods in relation to gender, region and type of household. Children with T1D reported lower quality of life comparing to matching controls with lower scores in almost all domains. Differences in the same domains among patients and their classmates were also observed in the different gender subgroups, environment type subgroups and in the central region. Results of the study provide insights to prioritizing actions for children with diabetes care as well as for public healthcare planning.

Metabolic Effects of Breastfeeding in Women with Previous Gestational Diabetes Mellitus: A Meta-Analysis

Objective: To investigate the effects of breastfeeding (BF) on metabolic-related outcomes in women with previous gestational diabetes mellitus. Methods: Databases, including PubMed, Embase, Cochrane Library, and Web of Science, were searched until March 5, 2020. Finally, 14 high-quality articles were included. Relative risk (RR) and weighted mean difference (WMD) with 95% confidence interval (CI) were pooled using Stata14.0 Software. Results: Subjects in the BF group had a lower incidence of diabetes (RR: 0.611, 95% CI: 0.452-0.826, p < 0.001) and lower fasting plasma glucose level (WMD: -4.762, 95% CI: -5.552 to -3.973, p < 0.001), fasting insulin level (WMD: -21.513, 95% CI: -37.594 to -5.431, p = 0.009), homeostasis model assessment of insulin resistance (HOMA-IR) (WMD: -1.107, 95% CI: -1.683 to -0.532, p < 0.001), and triglyceride level (WMD: -33.951, 95% CI: -50.714 to -17.189, p < 0.001) than those in the non-BF group. The high-density lipoprotein level (WMD: 3.855, 95% CI: 2.629-5.081, p < 0.001), low-density lipoprotein level (WMD: 4.223, 95% CI: 0.6712-7.774, p = 0.020), and insulin sensitivity index (WMD: 1.503, 95% CI: 0.857-2.160, p < 0.001) in the BF group were higher than that in the non-BF group. No difference was found in the 2-hour postprandial blood glucose (WMD: -3.804, 95% CI: -8.237 to 0.630, p = 0.093), incidence of prediabetes mellitus (RR: 0.870, 95% CI: 0.750-1.009, p = 0.065), or cholesterol level (WMD: 1.377, 95% CI: -8.178 to 10.931, p = 0.778) between the two groups. Conclusion: BF may improve several metabolic markers and decrease the risk of developing diabetes.

Systematic Review of Self-Monitoring of Blood Glucose in Patients with Type 2 Diabetes

BACKGROUND

The benefit of self-monitoring of blood glucose in reducing HbA1c in non-insulin-treated participants remains unclear. HbA1c may be improved in this population with self-monitoring.

OBJECTIVE

To conduct a meta-analysis of the effect in non-insulin-treated participants with type 2 diabetes of self-monitoring of blood glucose versus usual care, structured versus unstructured self-monitoring of blood glucose on glycemic control, and use of self-monitoring of blood glucose readings used to adjust therapy versus usual care.

METHODS

Medline, Embase, and Cochrane Central were electronically searched to identify articles published from January 1, 2000, to June 3, 2020. Trials investigating changes in HbA1c were selected. Screening was performed independently by two investigators. Two investigators extracted HbA1c at baseline and follow-up for each trial.

RESULTS

Nineteen trials involving 4,965 participants were included. Overall, self-monitoring of blood glucose reduced HbA1c. Preplanned subgroup analysis showed that using self-monitoring of blood glucose readings to adjust therapy contributed significantly to the reduction. No significant improvement in HbA1c was shown in self-monitoring of blood glucose without therapy adjustment. The same difference was observed in structured versus unstructured self-monitoring of blood glucose.

DISCUSSION

HbA1c is improved with therapy adjustment based on structured self-monitoring of blood glucose readings. Implications are for clinicians to prescribe structured self-monitoring of blood glucose to modify therapy adjustment based on the readings and not prescribe unstructured self-monitoring of blood glucose. Participants with suboptimal glycemic control may benefit most. A self-monitoring of blood glucose regimen that improves clinical- and cost-effectiveness is presented. Future studies can investigate this regimen specifically.

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.

Impact of flash glucose monitoring on glucose control and hospitalization in type 1 diabetes: A nationwide cohort study

BACKGROUND

We evaluated the impact of flash continuous glucose monitoring (FCGM) on glycemic control and healthcare burden in a large real-world cohort of patients with type 1 diabetes (T1D) initiating FCGM technology.

METHODS

In this retrospective cohort study, we included adults (age ≥18 years) with T1D from a large Health Maintenance Organization in Israel, who initiated FCGM during 2018. Primary outcomes included change in HbA1c ≥3 months following FCGM commencement and change in rate of internal-medicine hospitalization. Additional outcomes included changes in glucose test strip purchases, diabetes related outpatient health care visits and hospitalization for diabetic ketoacidosis (DKA) and/or severe hypoglycemia.

RESULTS

The study included 3490 patients, followed for a median of 14 (inter-quartile range 11-15) months after FCGM commencement. Among 2682 patients with an HbA1c measured both at baseline and ≥3 months after FCGM initiation, average HbA1c declined from 8.1% ± 1.46% to 7.9% ± 1.31% (P < .001) at first measurement and was maintained during follow up. Specifically, in those with HbA1c ≥8%, a mean decline of 0.5% (P < .001) was observed. A clinically significant HbA1c reduction of ≥0.5% was experienced by 25.5% of the patients. The rate of internal medicine hospitalization, visits to primary care, or visits to endocrine/diabetes specialists in the period following FCGM commencement vs the 6 months prior was significantly reduced (P < .001). Hospitalization for DKA and/or hypoglycemia declined as well (P = .004).

CONCLUSIONS

FCGM was associated with significant and durable improvement in glycemic control as well as reduced consumption of healthcare services.