Background And Aims: In type 2 diabetes (T2D) patients, the reduction of glycemic variability and postprandial glucose excursions is essential to limit diabetes complications, beyond HbA1c level. This study aimed at determining whether increasing the content of Slowly Digestible Starch (SDS) in T2D patients' diet could reduce postprandial hyperglycemia and glycemic variability compared with a conventional low-SDS diet.
Methods And Results: For this randomized cross-over pilot study, 8 subjects with T2D consumed a controlled diet for one week, containing starchy products high or low in SDS. Glycemic variability parameters were evaluated using a Continuous Glucose Monitoring System. Glycemic variability was significantly lower during High-SDS diet compared to Low-SDS diet for MAGE (Mean Amplitude of Glycemic Excursions, p < 0.01), SD (Standard Deviation, p < 0.05), and CV (Coefficient of Variation, p < 0.01). The TIR (Time In Range) [140-180 mg/dL[ was significantly higher during High-SDS diet (p < 0.0001) whereas TIRs ≥180 mg/dL were significantly lower during High-SDS diet. Post-meals tAUC (total Area Under the Curve) were significantly lower during High-SDS diet.
Conclusion: One week of High-SDS Diet in T2D patients significantly improves glycemic variability and reduces postprandial glycemic excursions. Modulation of starch digestibility in the diet could be used as a simple nutritional tool in T2D patients to improve daily glycemic control. REGISTRATION NUMBER: in clinicaltrials.gov: NCT03289494.
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http://dx.doi.org/10.1016/j.numecd.2020.08.010 | DOI Listing |
Br J Hosp Med (Lond)
January 2025
Nursing Department, Zhang Ye People's Hospital Affiliated to Hexi University, Zhangye, Gansu, China.
Diabetes is a chronic lifelong condition that requires consistent self-care and daily lifestyle adjustments. Effective disease management involves regular blood glucose monitoring and ongoing nursing support. Inadequate education and poor self-management are key factors contributing to increased mortality among diabetic individuals.
View Article and Find Full Text PDFInt J Mol Sci
January 2025
Department of Pharmacy, University of Limpopo, Mankweng 0727, South Africa.
This narrative review examines the dynamic interplay between carbohydrate intake and diabetes medications, highlighting their combined molecular and clinical effects on glycemic control. Carbohydrates, a primary energy source, significantly influence postprandial glucose regulation and necessitate careful coordination with pharmacological therapies, including insulin, metformin, glucagon-like peptide (GLP-1) receptor agonists, and sodium-glucose cotransporter-2 (SGLT2) inhibitors. Low-glycemic-index (GI) foods enhance insulin sensitivity, stabilize glycemic variability, and optimize medication efficacy, while high-GI foods exacerbate glycemic excursions and insulin resistance.
View Article and Find Full Text PDFHealthcare (Basel)
January 2025
Department of Experimental and Clinical Pharmacology, Medical University of Warsaw, 02-091 Warsaw, Poland.
Type 1 diabetes mellitus (T1DM) is a chronic metabolic disorder primarily managed through insulin therapy, which is crucial for achieving optimal glycemic control in children and adolescents. Therapeutic education is essential, equipping patients and their families with the knowledge and skills necessary for effective self-management. This familial support plays a critical role in the success of therapy and in fostering an environment conducive to the child's self-management of the condition.
View Article and Find Full Text PDFJMIR Mhealth Uhealth
January 2025
Xiangya School of Nursing, Central South University, Changsha, China.
Background: Among people with abdominal obesity, women are more likely to develop diabetes than men. Mobile health (mHealth)-based technologies provide the flexibility and resource-saving opportunities to improve lifestyles in an individualized way. However, mHealth-based diabetes prevention programs tailored for busy mothers with abdominal obesity have not been reported yet.
View Article and Find Full Text PDFJ Clin Res Pediatr Endocrinol
January 2025
Narasaraopeta Engineering College, Computer Science and Engineering, India.
Objective: The honeymoon phase in Type 1 Diabetes (T1D) presents a temporary improvement in glycemic control, complicating insulin management. This study aims to develop and validate a machine learning-driven method for accurately detecting this phase to optimize insulin therapy and prevent adverse outcomes.
Methods: Data from pediatric T1D patients aged 6-17 years, including continuous glucose monitoring (CGM) data, Glucose Management Indicator (GMI) reports, HbA1c values, and patient medical history, were used to train machine learning models.
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