Literature DB >> 30694076

Glycemic Variability: Risk Factors, Assessment, and Control.

Boris Kovatchev1.   

Abstract

Glycemic variability (GV) a well-established risk factor for hypoglycemia and a suspected risk factor for diabetes complications. GV is also a marker of the instability of a person's metabolic system, expressed as frequent high and low glucose excursions and overall volatile glycemic control. In this review, the author discusses topics related to the assessment, quantification, and optimal control of diabetes, including (1) the notion that optimal control of diabetes, that is, lowering of HbA1c-the commonly accepted gold-standard outcome-can be achieved only if accompanied by simultaneous reduction of GV; (2) assessment and visualization of the two principal dimensions of GV, amplitude and time, which is now possible via continuous glucose monitoring (CGM) and various metrics quantifying GV and the risks associated with hypo- and hyperglycemic excursions; and (3) the evolution of diabetes science and technology beyond quantifying GV and into the realm of GV control via pharmacological agents, for example, GLP-1 receptor agonists and DPP-4 inhibitors, which have pronounced variability-reducing effect, or real-time automated closed-loop systems commonly referred to as the "artificial pancreas." The author concludes that CGM allows close tracking over time, and therefore precise quantification, of glycemic variability in diabetes. The next step-optimal control of glucose fluctuations-is also taken by medications with pronounced GV-lowering effect primarily in type 2 diabetes, and by automated insulin delivery in type 1 diabetes. Contemporary CGM-based artificial pancreas systems use specific GV representations as input signals, and thus their main objective is to minimize GV and, from there, optimize glycemic control.

Entities:  

Keywords:  artificial pancreas; closed-loop control; continuous glucose monitoring; glycemic variability; hyperglycemia; hypoglycemia

Mesh:

Substances:

Year:  2019        PMID: 30694076      PMCID: PMC6610616          DOI: 10.1177/1932296819826111

Source DB:  PubMed          Journal:  J Diabetes Sci Technol        ISSN: 1932-2968


  70 in total

1.  THE M-VALVE, AN INDEX OF BLOOD-SUGAR CONTROL IN DIABETICS.

Authors:  J SCHLICHTKRULL; O MUNCK; M JERSILD
Journal:  Acta Med Scand       Date:  1965-01

2.  Glycemic variability: a hemoglobin A1c-independent risk factor for diabetic complications.

Authors:  Michael Brownlee; Irl B Hirsch
Journal:  JAMA       Date:  2006-04-12       Impact factor: 56.272

3.  Evaluation of a new measure of blood glucose variability in diabetes.

Authors:  Boris P Kovatchev; Erik Otto; Daniel Cox; Linda Gonder-Frederick; William Clarke
Journal:  Diabetes Care       Date:  2006-11       Impact factor: 19.112

Review 4.  Should minimal blood glucose variability become the gold standard of glycemic control?

Authors:  Irl B Hirsch; Michael Brownlee
Journal:  J Diabetes Complications       Date:  2005 May-Jun       Impact factor: 2.852

5.  Epidemiology of Diabetes Interventions and Complications (EDIC). Design, implementation, and preliminary results of a long-term follow-up of the Diabetes Control and Complications Trial cohort.

Authors: 
Journal:  Diabetes Care       Date:  1999-01       Impact factor: 19.112

6.  A novel analytical method for assessing glucose variability: using CGMS in type 1 diabetes mellitus.

Authors:  Anthony L McCall; Daniel J Cox; John Crean; Maury Gloster; Boris P Kovatchev
Journal:  Diabetes Technol Ther       Date:  2006-12       Impact factor: 6.118

Review 7.  The incretin system: glucagon-like peptide-1 receptor agonists and dipeptidyl peptidase-4 inhibitors in type 2 diabetes.

Authors:  Daniel J Drucker; Michael A Nauck
Journal:  Lancet       Date:  2006-11-11       Impact factor: 79.321

8.  Methods for quantifying self-monitoring blood glucose profiles exemplified by an examination of blood glucose patterns in patients with type 1 and type 2 diabetes.

Authors:  Boris P Kovatchev; Daniel J Cox; Linda Gonder-Frederick; William L Clarke
Journal:  Diabetes Technol Ther       Date:  2002       Impact factor: 6.118

Review 9.  Hypoglycaemia: the limiting factor in the glycaemic management of Type I and Type II diabetes.

Authors:  P E Cryer
Journal:  Diabetologia       Date:  2002-04-26       Impact factor: 10.122

10.  Assessment of the severity of hypoglycemia and glycemic lability in type 1 diabetic subjects undergoing islet transplantation.

Authors:  Edmond A Ryan; Tami Shandro; Kristy Green; Breay W Paty; Peter A Senior; David Bigam; A M James Shapiro; Marie-Christine Vantyghem
Journal:  Diabetes       Date:  2004-04       Impact factor: 9.461

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  19 in total

1.  Cgmquantify: Python and R Software Packages for Comprehensive Analysis of Interstitial Glucose and Glycemic Variability from Continuous Glucose Monitor Data.

Authors:  Brinnae Bent; Maria Henriquez; Jessilyn Dunn
Journal:  IEEE Open J Eng Med Biol       Date:  2021-08-18

2.  Association between dysglycemia and mortality by diabetes status and risk factors of dysglycemia in critically ill patients: a retrospective study.

Authors:  Haoming Ma; Guo Yu; Ziwen Wang; Peiru Zhou; Weitao Lv
Journal:  Acta Diabetol       Date:  2021-11-11       Impact factor: 4.280

3.  Non-invasive wearables for remote monitoring of HbA1c and glucose variability: proof of concept.

Authors:  Brinnae Bent; Peter J Cho; April Wittmann; Connie Thacker; Srikanth Muppidi; Michael Snyder; Matthew J Crowley; Mark Feinglos; Jessilyn P Dunn
Journal:  BMJ Open Diabetes Res Care       Date:  2021-06

4.  Glycemic Variability Within 1 Year Following Surgery for Stage II-III Colon Cancer.

Authors:  Natalie Rasmussen Mandolfo; Ann M Berger; Leeza Struwe; Kathleen M Hanna; Whitney Goldner; Kelsey Klute; Sean Langenfeld; Marilyn Hammer
Journal:  Biol Res Nurs       Date:  2021-10-05       Impact factor: 2.318

5.  Acute glycemic variability on admission predicts the prognosis in hospitalized patients with coronary artery disease: a meta-analysis.

Authors:  Zhaokun Pu; Lihong Lai; Xishan Yang; Yanyu Wang; Pingshuan Dong; Dan Wang; Yingli Xie; Zesen Han
Journal:  Endocrine       Date:  2019-12-11       Impact factor: 3.633

6.  Glycemic Variability Assessment with a 14-Day Continuous Glucose Monitoring System: When and How Long to Measure MAGE (Mean Amplitude of Glucose Excursion) for Optimal Reliability?

Authors:  Bruno Vergès; Elise Pignol; Alexia Rouland; Benjamin Bouillet; Sabine Baillot-Rudoni; Emilienne Quilot; Abdelmadjid Djeffal; Jean Michel Petit
Journal:  J Diabetes Sci Technol       Date:  2021-02-10

7.  Acute glycemic variability and mortality of patients with acute stroke: a meta-analysis.

Authors:  Jinbo Lin; Chunsheng Cai; Yituan Xie; Li Yi
Journal:  Diabetol Metab Syndr       Date:  2022-05-10       Impact factor: 5.395

8.  Time in Range: How to Measure It, How to Report It, and Its Practical Application in Clinical Decision-Making.

Authors:  Eugene E Wright; Kayla Morgan; Danny K Fu; Nick Wilkins; William J Guffey
Journal:  Clin Diabetes       Date:  2020-12

9.  Associations of Time in Range and Other Continuous Glucose Monitoring-Derived Metrics With Well-Being and Patient-Reported Outcomes: Overview and Trends.

Authors:  Dominic Ehrmann; Lilli Priesterroth; Andreas Schmitt; Bernhard Kulzer; Norbert Hermanns
Journal:  Diabetes Spectr       Date:  2021-05-25

10.  Engineering digital biomarkers of interstitial glucose from noninvasive smartwatches.

Authors:  Brinnae Bent; Peter J Cho; Maria Henriquez; April Wittmann; Connie Thacker; Mark Feinglos; Matthew J Crowley; Jessilyn P Dunn
Journal:  NPJ Digit Med       Date:  2021-06-02
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