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      Targeting Predialysis Glucose up to 180 mg/dl Reduces Glycemic Variability in End Stage Diabetic Nephropathy

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          Abstract

          Context:

          Glycemic variability plays a major role in the development as well as the progression of cardiovascular disease in diabetes.

          Aims:

          We compared the mean plasma glucose and glycemic variability (GV) parameters on and off hemodialysis (HD) in patients with End-Stage Diabetic Nephropathy (ESDN) and End-Stage Renal Disease (ESRD).

          Settings and Design:

          Cross-sectional study.

          Methods and Material:

          We included 23 ESDN and 6 ESRD patients who underwent continuous glucose monitoring (CGM) (iPro2) for 6 days and a glucose-free dialysate for 4 hours thrice weekly. EasyGV software was used to calculate the variability parameters {mean glucose, Time in range (TIR), Time above and below range (TAR/TBR), CV (Coefficient of Variation) and MAGE}.

          Statistical Analysis Used:

          The quantitative data variables were expressed by using mean and SD. Unpaired t-test was used to compare the two groups. P value <0.05 was considered significant.

          Results:

          In the ESDN group, TIR was significantly lower whereas TAR and TBR were significantly higher on HD day. MAGE (101.88 ± 40.5 v/s 89.46 ± 30.0, P < 0.007) and CV (29.41% v/s 21.67%) were higher on HD day. Subjects with pre-HD glucose values ≥180 mg/dl (Group B, n = 24) had a rapid drop with a delayed higher rise in glucose values than those with pre-HD glucose values <180 mg/dl (Group A, n = 27). Ten patients had 13 episodes of hypoglycemia. The CGM parameters were not different in the ESRD group.

          Conclusions:

          Targeting a pre- HD glucose value <180 mg/dl could be a good strategy to prevent larger fluctuation during and post HD.

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          Most cited references25

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          Clinical Targets for Continuous Glucose Monitoring Data Interpretation: Recommendations From the International Consensus on Time in Range

          Improvements in sensor accuracy, greater convenience and ease of use, and expanding reimbursement have led to growing adoption of continuous glucose monitoring (CGM). However, successful utilization of CGM technology in routine clinical practice remains relatively low. This may be due in part to the lack of clear and agreed-upon glycemic targets that both diabetes teams and people with diabetes can work toward. Although unified recommendations for use of key CGM metrics have been established in three separate peer-reviewed articles, formal adoption by diabetes professional organizations and guidance in the practical application of these metrics in clinical practice have been lacking. In February 2019, the Advanced Technologies & Treatments for Diabetes (ATTD) Congress convened an international panel of physicians, researchers, and individuals with diabetes who are expert in CGM technologies to address this issue. This article summarizes the ATTD consensus recommendations for relevant aspects of CGM data utilization and reporting among the various diabetes populations.
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            Activation of oxidative stress by acute glucose fluctuations compared with sustained chronic hyperglycemia in patients with type 2 diabetes.

            Glycemic disorders, one of the main risk factors for cardiovascular disease, are associated with activation of oxidative stress. To assess the respective contributions of sustained chronic hyperglycemia and of acute glucose fluctuations to oxidative stress in type 2 diabetes. Case-control study of 21 patients with type 2 diabetes (studied 2003-2005) compared with 21 age- and sex-matched controls (studied in 2001) in Montpellier, France. Oxidative stress, estimated from 24-hour urinary excretion rates of free 8-iso prostaglandin F2alpha (8-iso PGF2alpha). Assessment of glucose fluctuations was obtained from continuous glucose monitoring system data by calculating the mean amplitude of glycemic excursions (MAGE). Postprandial contribution to glycemic instability was assessed by determining the postprandial increment of glucose level above preprandial values (mean postprandial incremental area under the curve [AUCpp]). Long-term exposure to glucose was estimated from hemoglobin A1c, from fasting glucose levels, and from mean glucose concentrations over a 24-hour period. Mean (SD) urinary 8-iso PGF2alpha excretion rates were higher in the 21 patients with diabetes (482 [206] pg/mg of creatinine) compared with controls (275 [85] pg/mg of creatinine). In univariate analysis, only MAGE (r = 0.86; P<.001) and AUCpp (r = 0.55; P = .009) showed significant correlations with urinary 8-iso PGF2alpha excretion rates. Relationships between 8-iso PGF2alpha excretion rates and either MAGE or AUCpp remained significant after adjustment for the other markers of diabetic control in multiple linear regression analysis (multiple R2 = 0.72 for the model including MAGE and multiple R2 = 0.41 for the model including AUCpp). Standardized regression coefficients were 0.830 (P<.001) for MAGE and 0.700 (P = .003) for AUCpp. Glucose fluctuations during postprandial periods and, more generally, during glucose swings exhibited a more specific triggering effect on oxidative stress than chronic sustained hyperglycemia. The present data suggest that interventional trials in type 2 diabetes should target not only hemoglobin A1c and mean glucose concentrations but also acute glucose swings.
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              Mean amplitude of glycemic excursions, a measure of diabetic instability.

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                Author and article information

                Journal
                Indian J Endocrinol Metab
                Indian J Endocrinol Metab
                IJEM
                Indian J Endocr Metab
                Indian Journal of Endocrinology and Metabolism
                Wolters Kluwer - Medknow (India )
                2230-8210
                2230-9500
                Sep-Oct 2022
                22 November 2022
                : 26
                : 5
                : 439-445
                Affiliations
                [1]Department of Endocrinology, Room No. 419, 4 th Floor, College Building, Topiwala National Medical College and BYL Nair Charitable Hospital, A.L. Nair Road, Mumbai Central, Mumbai, Maharashtra, India
                [1 ]Department of Nephrology, Sushrut Hospital and Research Centre, Mumbai, Maharashtra, India
                [2 ]Department of Nephrology, P.D. Hinduja Hospital and Research Centre, Mumbai, Maharashtra, India
                [3 ]Department of Nephrology, Head of Nephrology, Bombay Hospital and Medical Research Centre, Mumbai, Maharashtra, India
                Author notes
                Address for correspondence: Dr. Jugal V. Gada, Department of Endocrinology, Room No. 419, 4 th Floor, College Building, Topiwala National Medical College and BYL Nair Charitable Hospital, AR Nair Road, Mumbai Central, Mumbai, Maharashtra - 400 008, India. E-mail: jugal.gada@ 123456gmail.com
                Article
                IJEM-26-439
                10.4103/ijem.ijem_157_22
                9815189
                37215267
                aa12a470-87e6-44f3-8447-f8d07996ab85
                Copyright: © 2022 Indian Journal of Endocrinology and Metabolism

                This is an open access journal, and articles are distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 License, which allows others to remix, tweak, and build upon the work non-commercially, as long as appropriate credit is given and the new creations are licensed under the identical terms.

                History
                : 19 April 2022
                : 15 July 2022
                : 26 August 2022
                Categories
                Original Article

                Endocrinology & Diabetes
                continuous glucose monitoring system,end stage diabetic nephropathy,glycemic variability,hemodialysis,mean amplitude of glycemic excursion (mage),type 2 diabetes mellitus

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