Clinical and Lifestyle Determinants of Continuous Glucose Monitoring Metrics in Insulin-Treated Patients with Type 2 Diabetes Mellitus.
暂无分享,去创建一个
H. J. Yoo | K. Choi | S. Baik | D. Lee | N. Kim | J. Yu | S. Kim | Kyeong Jin Kim | Inha Jung | Sung-Min Park | S. Park | J. Seo | N. H. Kim | Namho Kim | Jihee Kim
[1] Eric L. Johnson,et al. 6. Glycemic Targets: Standards of Care in Diabetes-2023. , 2022, Diabetes care.
[2] M. Dollé,et al. A randomized crossover trial assessing time of day snack consumption and resulting postprandial glycemic response in a real-life setting among healthy adults , 2022, Chronobiology international.
[3] Sang-Man Jin,et al. Effect of structured individualized education on continuous glucose monitoring use in poorly controlled patients with type 1 diabetes: A randomized controlled trial. , 2022, Diabetes research and clinical practice.
[4] C. Whitton,et al. Diet and Physical Activity as Determinants of Continuously Measured Glucose Levels in Persons at High Risk of Type 2 Diabetes , 2022, Nutrients.
[5] Ichiro Kishimoto,et al. Impact of Lifestyle Behaviors on Postprandial Hyperglycemia during Continuous Glucose Monitoring in Adult Males with Overweight/Obesity but without Diabetes , 2021, Nutrients.
[6] D. Jakubowicz,et al. Role of High Energy Breakfast “Big Breakfast Diet” in Clock Gene Regulation of Postprandial Hyperglycemia and Weight Loss in Type 2 Diabetes , 2021, Nutrients.
[7] Yoichi M Ito,et al. Log-linear relationship between endogenous insulin secretion and glycemic variability in patients with type 2 diabetes on continuous glucose monitoring , 2021, Scientific Reports.
[8] D. West,et al. A Comparison of Sedentary Behavior as Measured by the Fitbit and ActivPAL in College Students , 2021, International journal of environmental research and public health.
[9] M. Rondón,et al. Clinical Factors Associated with High Glycemic Variability Defined by Coefficient of Variation in Patients with Type 2 Diabetes , 2021, Medical devices.
[10] I. Shimomura,et al. Associations between continuous glucose monitoring-derived metrics and arterial stiffness in Japanese patients with type 2 diabetes , 2021, Cardiovascular Diabetology.
[11] Meng Bian,et al. Glycemic variability: adverse clinical outcomes and how to improve it? , 2020, Cardiovascular Diabetology.
[12] B. Schwikowski,et al. Associations between consumption of dietary fibers and the risk of cardiovascular diseases, cancers, type 2 diabetes, and mortality in the prospective NutriNet-Santé cohort. , 2020, The American journal of clinical nutrition.
[13] J. Little,et al. A low-carbohydrate protein-rich bedtime snack to control fasting and nocturnal glucose in type 2 diabetes: A randomized trial. , 2020, Clinical nutrition.
[14] S. Yamagishi,et al. Relationship between glucose variability evaluated by continuous glucose monitoring and clinical factors, including glucagon-stimulated insulin secretion in patients with type 2 diabetes. , 2019, Diabetes research and clinical practice.
[15] Hoh Peter In,et al. Mood Prediction of Patients With Mood Disorders by Machine Learning Using Passive Digital Phenotypes Based on the Circadian Rhythm: Prospective Observational Cohort Study , 2019, Journal of medical Internet research.
[16] G. Brinkworth,et al. Effects of an energy‐restricted low‐carbohydrate, high unsaturated fat/low saturated fat diet versus a high‐carbohydrate, low‐fat diet in type 2 diabetes: A 2‐year randomized clinical trial , 2018, Diabetes, obesity & metabolism.
[17] Eyal Dassau,et al. International Consensus on Use of Continuous Glucose Monitoring , 2017, Diabetes Care.
[18] J. Holst,et al. Short‐term effects of a low carbohydrate diet on glycaemic variables and cardiovascular risk markers in patients with type 1 diabetes: A randomized open‐label crossover trial , 2017, Diabetes, obesity & metabolism.
[19] Roy W Beck,et al. The Fallacy of Average: How Using HbA1c Alone to Assess Glycemic Control Can Be Misleading , 2017, Diabetes Care.
[20] Tsutomu Hirano,et al. Relationship between daily and day-to-day glycemic variability and increased oxidative stress in type 2 diabetes. , 2016, Diabetes research and clinical practice.
[21] Yoshiya Tanaka,et al. Factors influencing inter‐day glycemic variability in diabetic outpatients receiving insulin therapy , 2016, Journal of diabetes investigation.
[22] Y. Saisho. Postprandial C-Peptide to Glucose Ratio as a Marker of β Cell Function: Implication for the Management of Type 2 Diabetes , 2016, International journal of molecular sciences.
[23] N. Kaba,et al. Study of the Effects of Snack-Centered Dietary Education on First-Grade Elementary Students and Duration of These Effects , 2015 .
[24] M. Orsini Federici,et al. Assessment of the association between glycemic variability and diabetes-related complications in type 1 and type 2 diabetes. , 2014, Diabetes research and clinical practice.
[25] Sang-Man Jin,et al. Clinical factors associated with absolute and relative measures of glycemic variability determined by continuous glucose monitoring: an analysis of 480 subjects. , 2014, Diabetes research and clinical practice.
[26] E. Kang,et al. Postprandial C‐peptide to glucose ratio as a predictor of β‐cell function and its usefulness for staged management of type 2 diabetes , 2014, Journal of diabetes investigation.
[27] D. Klonoff,et al. Recommendations for standardizing glucose reporting and analysis to optimize clinical decision making in diabetes: the Ambulatory Glucose Profile (AGP). , 2013, Diabetes technology & therapeutics.
[28] Y. Chung,et al. Comparison of nutritional status by energy level of night snack in Korean adults: using the data from 2005 Korean National Health and Nutrition Examination Survey , 2012 .
[29] Frits Holleman,et al. Glucose variability; does it matter? , 2010, Endocrine reviews.
[30] C. Schmid,et al. A new equation to estimate glomerular filtration rate. , 2009, Annals of internal medicine.