Glycemic Excursions in Diabetic Kidney Disease: Comparison of Three Therapeutic Arms (original) (raw)
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Management of Glycemia in Diabetic Patients with Stage IV and V Chronic Kidney Disease
Current Diabetes Reports, 2015
Diabetic kidney disease is a leading cause of endstage kidney disease worldwide. Data suggest that prevention of progression to end-stage may lie in excellent blood glucose control; however, as kidney disease progresses, the risk of hypoglycemia increases, due to unpredictable insulin kinetics and altered pharmacokinetics of hypoglycemic agents. In addition, whole classes of hypoglycemic agents become contraindicated and regimens must be adjusted for declining kidney function. There is no consensus regarding the best therapy for the patient with advanced chronic kidney disease. In the best of circumstances, the care of these patients will involve intensive monitoring, with the input of a team of health care providers creating a coordinated care plan, including dietary advice and a drug regimen tailored to the specific issues faced by the individual patient. An open dialogue is necessary at all times, as patients may become frustrated and attempt selftreatment using over the counter alternatives.
Romanian Journal of Diabetes Nutrition and Metabolic Diseases, 2013
Background and Aims. In diabetic patients, chronic kidney disease (CKD) requires special attention due to the multitude of factors that determine glycemic variability. We aimed to assess glycemic variability in patients with CKD and type 2 diabetes mellitus (T2DM) using a continuous glucose monitoring system (CGMS) and identify the predictive value of inter-day and intra-day glycemic variability indices for metabolic imbalance. Material and method. We included 20 diabetic patients (10 CKD patients/10 patients without CKD) and 10 healthy volunteers. Anthropometric parameters, glycated hemoglobin (HbA1c), and glycemic variability indices on CGMS readings were registered. Results. CKD diabetic patients presented significantly higher inter-day and intra-day glycemic variability compared to the diabetic patients without CKD. HbA1c was not significantly different between diabetic subjects with/without CKD. ROC curves indicated that just some CGMS parameters had higher predictive value for...
Achieving glycemic control in patients with type 2 diabetes and renal impairment
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Diabetologia, 1991
The European NIDDM Policy Group states that the lowest target for good control of Type 2 (non-insulin-dependent) diabetic patients is a blood glucose level 4.4 mmol/1, both fasting and postprandially. The aim of this study is to evaluate the occurrence and temporal distribution of values under this target in the clinical records of 463 Type 2 diabetic patients, treated by diet or diet and oral hypoglycaemic agents, monitored for at least 2 years. The protocol includes blood glucose measurements after overnight fasting (08.00 hours), 120-150 rain after breakfast (11.00 hours) and 120 and 240 min after lunch (14.00 and 16.00 hours). At least one blood glucose concentration of less than 4.4 mmol/1 was presented by 42% of the patients. The only difference between patients showing and not showing glycaemic levels under this target was the higher percentage on oral hypoglycaemic agents in the first group (68.4% vs 56.9% ,p = 0.016). We considered 299 blood glucose profiles containing at least one value of less than 4.4 retool/l, observing that a) 46.9% of profiles from patients treated by diet alone and 68.7% of profiles from patients treated both by diet and oral hypoglycaemic agents presented the lowest blood glucose concentration at 16.00 hours (p = 0.002). b) No correlation existed between fasting blood glucose and values at 16.00 hours in profiles from diet-treated patients, whereas a negative correlation was present in patients on diet and oral hypoglycaemic agents, indicating that an excess of oral agents, administered to correct fasting hyperglycaemia, was the cause of the low glycaemic values in the afternoon, c) 37.9% of profiles on a diet and 83.3% of profiles on diet and oral agents showed fasting glucose concentrations > 6.7 mmol/1, the upper limit of good control according to the European NIDDM Policy Group. This indicates that fasting hyperglycaemia does not exclude the occurrence of low glucose values throughout the day and that it is necessary to monitor blood glucose profiles.
Arquivos Brasileiros de Endocrinologia & Metabologia, 2013
OBJECTIVE: To better explore the relationship between parameters of glycemic control of T2DM in RRT, we studied 23 patients on hemodialysis (HD), 22 on peritoneal dialysis (PD), and compared them with 24 T2DM patients with normal renal function (NRF). MATERIALS AND METHODS: We performed, on four consecutive days, 10 assessments of capillary blood glucose [4 fasting, 2 pre- and 4 postprandial (post-G) and average (AG)], random glycemia, and HbA1c in all patients. RESULTS: Preprandial blood glucose was greater in patients on RRT compared with NRF. Correlations between AG and HbA1c were 0.76 for HD, 0.66 for PD, and 0.82 for NRF. The regression lines between AG and HbA1c were similar for patients on HD and with NFR, but they were displaced upward for PD. CONCLUSION: Similar HbA1c values in PD patients may correspond to greater levels of AG than in HD or NRF patients.
Assessing glycemic control in patients with diabetes and end-stage renal failure
American Journal of Kidney Diseases, 2003
Blood glucose monitoring is important in optimizing long-term outcomes in diabetic patients. Reliance on near-patient testing and the use of longer term measures of glycation are the current cornerstones. However, as this review details, there are significant problems using blood tests as measures of metabolic control in uremic diabetic patients. Am J Kidney Dis 41:523-531.
Medical Devices: Evidence and Research, 2021
Background: High glycemic Variability (HGV) has become a stronger predictor of hypoglycemia. However, clinical factors associate with HGV still are unknown. Objective: To determine clinical variables that were associated with a coefficient of variation (CV) above 36% evaluated by continuous glucose monitoring (CGM) in a group of patients with diabetes mellitus. Methods: A cohort of patients with type 2 diabetes (T2D) was evaluated. Demographic variables, HbA1c, glomerular filtration rate (GFR) and treatment regimen were assessed. A bivariate analysis was performed, to evaluate the association between the outcome variable (CV> 36%) and each of the independent variables. A multivariate model was constructed to evaluate associations after controlling for confounding variables. Results: CGM data from 274 patients were analyzed. CV> 36% was present in 56 patients (20.4%). In the bivariate analysis, demographic and clinical variables were included, such as time since diagnosis, hypoglycemia history, A1c, GFR and treatment established. In the multivariate analysis, GFR <45 mL/min (OR 2.81; CI 1.27,6.23; p:0.01), A1c > 9% (OR 2.81; CI 1.05,7.51; p:0.04) and hypoglycemia history (OR 2.09; CI 1.02,4.32; p:0.04) were associated with HGV. Treatment with iDPP4 (OR 0.39; CI 0.19,0.82; p:0.01) and AGLP1 (OR 0.08; CI 0.01,0.68; p:0.02) was inversely associated with GV. Conclusion: Clinical variables such as GFR <45 mL/min, HbA1C>9% and a history of hypoglycemia are associated with a high GV. Our data suggest that the use of technology and treatments able to reduce glycemic variability could be useful in this population to reduce the risk of hypoglycemia and to improve glycemic control.