Background: Self-monitoring of blood glucose (SMBG) is considered of little clinical benefit for adults with non-insulin-treated type 2 diabetes, but no comprehensive review of a structured approach to SMBG has been published to date.
Purpose: To conduct a systematic review and meta-analysis of the impact of sSMBG on HbA1c, treatment modifications, behavioral and psychosocial outcomes, and; examine the moderating effects of sSMBG protocol characteristics on HbA1c.
Data Sources: Four databases searched (November 2020; updated: February 2022).
Study Selection: Inclusion criteria: non-randomized and randomized controlled trials (RCTs) and prospective observational studies; reporting effect of sSMBG on stated outcomes; among adults (≥18 years) with non-insulin-treated type 2 diabetes. Studies excluded if involving children or people with insulin-treated or other forms of diabetes.
Data Extraction And Analysis: Outcome data extracted, and risk of bias/quality assessed independently by two researchers. Meta-analysis was conducted for RCTs, and moderators explored (HbA1c only).
Data Synthesis: From 2,078 abstracts, k=23 studies were included (N=5,372). Risk of bias was evident and study quality was low. Outcomes assessed included: HbA1c (k=23), treatment modification (k=16), psychosocial/behavioral outcomes (k=12). Meta-analysis revealed a significant mean difference favoring sSMBG in HbA1c (-0·29%, 95% CI: -0·46 to -0·11, k=13) and diabetes self-efficacy (0.17%, 95% CI: 0.01 to 0.33, k=2). Meta-analysis revealed no significant moderating effects by protocol characteristics.
Limitations: Findings limited by heterogeneity in study designs, intervention characteristics, and psychosocial assessments.
Conclusion: A small positive effect of sSMBG on HbA1c and diabetes self-efficacy was observed. Narrative synthesis of sSMBG intervention characteristics may guide future implementation.
Prospero Registration: https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42020208857, identifier CRD42020208857.
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http://dx.doi.org/10.3389/fcdhc.2023.1177030 | DOI Listing |
Diabetes Ther
December 2024
Abbott Diabetes Care, 6925 Century Ave, Suite 100, Mississauga, ON, L5N 7K2, Canada.
Introduction: For people living with diabetes, effective glucose monitoring is a key component in diabetes care, helping to reduce disease burden, complications, and healthcare utilization. Sensor-based glucose monitoring systems, which can provide more comprehensive information about glucose levels than capillary-based self-monitoring of blood glucose (SMBG), are becoming established among people living with diabetes. The objective of this study was to assess the cost-effectiveness of glucose monitoring with FreeStyle Libre systems, compared with SMBG, from the perspective of a Canadian private payer.
View Article and Find Full Text PDFSci Rep
September 2024
Center for Health Systems Research, Sutter Health, Santa Barbara, CA, USA.
The discrepancy between estimated glycemia from HbA values and actual average glucose (AG) levels has significant implications for treatment decisions and patient understanding. Factors contributing to the gap include red blood cell (RBC) lifespan and glucose uptake into the RBC. Personalized models have been proposed to enhance AG prediction accuracy by considering interpersonal variation.
View Article and Find Full Text PDFDiabetes Obes Metab
October 2024
Department of Medical Psychology and Behavioural Neurobiology, University of Tübingen, Tübingen, Germany.
Aim: To assess oxytocin's acute glucoregulatory impact in men with type 2 diabetes in the context of our previous findings that oxytocin improves β-cell responsivity in healthy men.
Methods: In a double-blind, crossover comparison, intranasal oxytocin (24 IU) and placebo, respectively, were administered to 25 fasted men with non-insulin-treated type 2 diabetes (age ± standard error of the mean, 63.40 ± 1.
J Diabetes Sci Technol
July 2024
Research & Development, Perfood GmbH, Lübeck, Germany.
Background: We present a digital therapeutic (DTx) using continuous glucose monitoring (CGM) and an advanced artificial intelligence (AI) algorithm to digitally personalize lifestyle interventions for people with type 2 diabetes (T2D).
Method: A study of 118 participants with non-insulin-treated T2D (HbA ≥ 6.5%) who were already receiving standard care and had a mean baseline (BL) HbA of 7.
Diabet Med
September 2024
Translational Health Sciences, Diabetes and Metabolism, Bristol Medical School, University of Bristol, Bristol, UK.
Aim: This study aimed to evaluate characteristics of autoimmunity in individuals who have a type 2 diagnosis and are relatives of children with type 1 diabetes.
Methods: Pre-diagnosis samples (median 17 months before onset) from relatives who were later diagnosed with type 2 diabetes were measured for autoantibodies to glutamate decarboxylase 65 (GADA), islet antigen-2 (IA-2A), zinc transporter 8 (ZnT8A) and insulin (IAA) as well as the type 1 diabetes genetic risk score (GRS2). Associations between islet autoantibodies, insulin treatment and GRS2 were analysed using Fisher's exact and t-tests.
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