Investigating the Relationship between Morning Glycemic Variability and Patient Characteristics Using Continuous Glucose Monitoring Data in Patients with Type 2 Diabetes

Abstract

Objective To investigate the relationship between patient characteristics and morning glycemic variability. Methods We retrospectively evaluated 106 patients with type 2 diabetes who underwent continuous glucose monitoring during admission. The highest postprandial glucose level (within 3 hours after breakfast; ‘highest level’), the time from the start of breakfast to the highest postprandial glucose level (‘highest time’), the difference between the pre-breakfast and highest postprandial breakfast glucose level (‘increase’), the area under the curve (AUC; ≥180 mg/dL) for the glycemic variability within 3 hours after breakfast (‘morning AUC’), and the post-breakfast glucose gradient (‘gradient’) were calculated. We analyzed the associations between these factors and nocturnal hypoglycemia and the patients’ characteristics by using a regression analysis. Results After stepwise multivariate adjustment, significant independent associations were found between ‘highest level’ and high age, low BMI, and high HbA1c; ‘highest time’ and high HbA1c, low C-peptide immunoreactivity (CPR), and low fasting plasma glucose (FPG); the ‘increase’ and high age, low BMI, high HbA1c, low FPG and hypoglycemia; ‘morning AUC’ and high age, high HbA1c and hypoglycemia; and ‘gradient’ and long duration of diabetes and low BMI. Conclusion Higher age and lower BMI are associated with higher ‘highest’ and ‘increase’ levels. Higher HbA1c levels were linked to a longer ‘highest time’, and longer durations of the diabetes, while lower BMI values were related to a higher ‘gradient’.

Predicting Hypoglycemia in Elderly Inpatients with Type 2 Diabetes: The ADOCHBIU Model

“…Cognitive impairment is also an essential factor in predicting hypoglycemia in elderly inpatients with T2DM, and cognitive impairment increases the risk of hypoglycemia. For older adults with T2DM, cognitive impairment can lead to di culties in controlling blood glucose and identifying and treating hypoglycemia, and frequent hypoglycemia attacks can further exacerbate cognitive decline, forming a vicious cycle [41] . In addition, hypertension is a predictor for hypoglycemia.…”

Assessing hypoglycemia frequency using flash glucose monitoring in older Japanese patients with type 2 diabetes receiving oral hypoglycemic agents

“…Hypoglycemia among older individuals can lead to falls, bone fractures, depression, arrhythmias and reduced quality of life, with severe hypoglycemia being a risk factor for dementia and cognitive decline . Although only few studies have directly compared the frequency of hypoglycemia between young and old patients with type 2 diabetes, several reports using multivariate analysis have shown that age is not a factor associated with hypoglycemia . However, compared with younger patients with type 2 diabetes, older patients with type 2 diabetes have fewer autonomic and central nervous symptoms at the time of hypoglycemia.…”

“…5 Although only few studies have directly compared the frequency of hypoglycemia between young and old patients with type 2 diabetes, several reports using multivariate analysis have shown that age is not a factor associated with hypoglycemia. 15,16 However, compared with younger patients with type 2 diabetes, older patients with type 2 diabetes have fewer autonomic and central nervous symptoms at the time of hypoglycemia. It is possible that a great deal of undiagnosed hypoglycemia might have appeared.…”

Comparison of morning basal + 1 bolus insulin therapy (insulin glulisine + insulin glargine 300 U/mL vs insulin lispro + insulin glargine biosimilar) using continuous glucose monitoring: A randomized crossover study

“…In any case the following are necessary in order to reduce increases in post‐breakfast glucose levels: (i) adjusting treatment to avoid nocturnal hypoglycemia when nocturnal hypoglycemia causes increased morning glucose levels; and (ii) decreasing post‐breakfast glucose levels directly by adjusting treatment. Regarding (ii), knowledge of a patient's morning glycemic variability status is important for improving increased glycemic variability over 24 h. We focused on using patient characteristics to predict morning glycemic variability, and we have reported the relationship between patient characteristics and morning glycemic variability in a previous study . In that study, higher age and lower body mass index (BMI) were observed to be associated with higher highest increased post‐breakfast glucose levels.…”