Literature DB >> 27383181

The impact of glycemic variability on diabetic peripheral neuropathy.

Heung Yong Jin1, Kyung Ae Lee1, Tae Sun Park2.   

Abstract

Mean glucose values alone cannot explain the patterns of morbidity and mortality due to dysglycemia in diabetes. Development of continuous glucose monitoring systems has improved the analysis and interpretation of glycemic variability. The roles of glycemic components other than constant hyperglycemia in diabetic complications must be investigated because large clinical studies have indicated that risk factors besides the average glucose value of HbA1c are involved in chronic macrocomplications/microcomplications of diabetes. Among these complications, the pathogenesis of diabetic peripheral neuropathy is particularly complex, and several factors related to glucose and nonglucose pathways have been suggested as risk factors. There is little information regarding the effect of glycemic variability on diabetic peripheral neuropathy, unlike other microvascular complications of retinopathy and nephropathy, and whether glycemic variability causes harmful effects is still a matter of debate. In this review, we discuss the relationships between glycemic variability and diabetic peripheral neuropathy, focusing on somatosensory peripheral neuropathies rather than autonomic neuropathies.

Entities:  

Keywords:  Continuous glucose monitoring system (CGMS); Diabetic peripheral neuropathy (DPN); Glycemic variability

Mesh:

Substances:

Year:  2016        PMID: 27383181     DOI: 10.1007/s12020-016-1005-7

Source DB:  PubMed          Journal:  Endocrine        ISSN: 1355-008X            Impact factor:   3.633


  40 in total

1.  Glycemic variability is higher in type 1 diabetes patients with microvascular complications irrespective of glycemic control.

Authors:  Jan Šoupal; Jan Škrha; Martin Fajmon; Eva Horová; Miloš Mráz; Jan Škrha; Martin Prázný
Journal:  Diabetes Technol Ther       Date:  2014-01-08       Impact factor: 6.118

2.  Comparison of glucose variability assessed by a continuous glucose-monitoring system in patients with type 2 diabetes mellitus switched from NPH insulin to insulin glargine: the COBIN2 study.

Authors:  Denisa Janickova Zdarska; Milan Kvapil; Zdenek Rusavy; Michal Krcma; Jan Broz; Bohumila Krivska; Pavla Kadlecova
Journal:  Wien Klin Wochenschr       Date:  2014-02-22       Impact factor: 1.704

3.  Decreased blood glucose excursion by nateglinide ameliorated neuropathic changes in Goto-Kakizaki rats, an animal model of non-obese type 2 diabetes.

Authors:  Yoshiro Kitahara; Kyoko Miura; Kaori Takesue; Tomoyuki Mine; Ryuichi Wada; Yoshiaki Uchida; Satoru Ito; Soroku Yagihashi
Journal:  Metabolism       Date:  2002-11       Impact factor: 8.694

4.  Diabetic endothelial dysfunction: the role of poly(ADP-ribose) polymerase activation.

Authors:  L Virág; P Jagtap; E Szabó; J G Mabley; L Liaudet; A Marton; D G Hoyt; K G Murthy; A L Salzman; G J Southan; C Szabó
Journal:  Nat Med       Date:  2001-01       Impact factor: 53.440

Review 5.  For debate. Glucose variability and diabetes complication risk: we need to know the answer.

Authors:  E S Kilpatrick; A S Rigby; S L Atkin
Journal:  Diabet Med       Date:  2010-08       Impact factor: 4.359

6.  Chronic hyperglycemia but not glucose variability determines HbA1c levels in well-controlled patients with type 2 diabetes.

Authors:  Klaus-Dieter Kohnert; Petra Augstein; Peter Heinke; Eckhard Zander; Karolina Peterson; Ernst-Joachim Freyse; Eckhard Salzsieder
Journal:  Diabetes Res Clin Pract       Date:  2007-02-28       Impact factor: 5.602

7.  Intermittent high glucose enhances apoptosis related to oxidative stress in human umbilical vein endothelial cells: the role of protein kinase C and NAD(P)H-oxidase activation.

Authors:  Lisa Quagliaro; Ludovica Piconi; Roberta Assaloni; Lucia Martinelli; Enrico Motz; Antonio Ceriello
Journal:  Diabetes       Date:  2003-11       Impact factor: 9.461

8.  A1C variability and the risk of microvascular complications in type 1 diabetes: data from the Diabetes Control and Complications Trial.

Authors:  Eric S Kilpatrick; Alan S Rigby; Stephen L Atkin
Journal:  Diabetes Care       Date:  2008-07-23       Impact factor: 17.152

Review 9.  Glycemic Variability: How Do We Measure It and Why Is It Important?

Authors:  Sunghwan Suh; Jae Hyeon Kim
Journal:  Diabetes Metab J       Date:  2015-08       Impact factor: 5.376

10.  Simulation and qualitative analysis of glucose variability, mean glucose, and hypoglycemia after subcutaneous insulin therapy for stress hyperglycemia.

Authors:  Richard J Strilka; Mamie C Stull; Michael S Clemens; Stewart C McCaver; Scott B Armen
Journal:  Theor Biol Med Model       Date:  2016-01-27       Impact factor: 2.432

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  21 in total

1.  Comparison of peripheral nerve protection between insulin-based glucose control and alpha lipoic acid (ALA) in the streptozotocin (STZ)-induced diabetic rat.

Authors:  Kyung Ae Lee; Na Young Lee; Tae Sun Park; Heung Yong Jin
Journal:  Endocrine       Date:  2018-05-07       Impact factor: 3.633

2.  Associations of serum glucagon levels with glycemic variability in type 1 diabetes with different disease durations.

Authors:  Ke Li; Wen-Jing Song; Xia Wu; Dan-Yang Gu; Pu Zang; Ping Gu; Bin Lu; Jia-Qing Shao
Journal:  Endocrine       Date:  2018-06-18       Impact factor: 3.633

3.  Serum uric acid and diabetic peripheral neuropathy: a double-edged sword.

Authors:  Yong Zhuang; Huibin Huang; Xin Hu; Jinying Zhang; Qingyan Cai
Journal:  Acta Neurol Belg       Date:  2022-05-29       Impact factor: 2.396

4.  Association of glycaemic variability evaluated by continuous glucose monitoring with diabetic peripheral neuropathy in type 2 diabetic patients.

Authors:  Yu-Ming Hu; Li-Hua Zhao; Xiu-Lin Zhang; Hong-Li Cai; Hai-Yan Huang; Feng Xu; Tong Chen; Xue-Qin Wang; Ai-Song Guo; Jian-An Li; Jian-Bin Su
Journal:  Endocrine       Date:  2018-02-06       Impact factor: 3.633

5.  Effects of Immunocytokine Combined with Cattle Encephalon Glycoside and Ignotin on CTGF, HO-1 and NT-3 in Patients with Type 2 Diabetic Peripheral Neuropathy.

Authors:  Jianguo Sun; Hui Zheng; Xiuxia Qin; Liqin Qi
Journal:  Iran J Public Health       Date:  2017-12       Impact factor: 1.429

6.  Association of lower body mass index with increased glycemic variability in patients with newly diagnosed type 2 diabetes: a cross-sectional study in China.

Authors:  Jian Wang; Rengna Yan; Juan Wen; Xiaocen Kong; Huiqin Li; Peihua Zhou; Honghong Zhu; Xiaofei Su; Jianhua Ma
Journal:  Oncotarget       Date:  2017-04-14

7.  HbA1c variability and diabetic peripheral neuropathy in type 2 diabetic patients.

Authors:  Jian-Bin Su; Li-Hua Zhao; Xiu-Lin Zhang; Hong-Li Cai; Hai-Yan Huang; Feng Xu; Tong Chen; Xue-Qin Wang
Journal:  Cardiovasc Diabetol       Date:  2018-03-29       Impact factor: 9.951

8.  The Association between Serum Uric Acid and Peripheral Neuropathy in Patients with Type 2 Diabetes Mellitus: A Multicenter Nationwide CrossSectional Study.

Authors:  Wisit Kaewput; Charat Thongprayoon; Ram Rangsin; Sarawut Jindarat; Ploypun Narindrarangkura; Tarun Bathini; Michael A Mao; Wisit Cheungpasitporn
Journal:  Korean J Fam Med       Date:  2020-05-20

9.  Diabetic Neuropathy Evaluated by a Novel Device: Sural Nerve Conduction Is Associated with Glycemic Control and Ankle-Brachial Pressure Index in Japanese Patients with Diabetes.

Authors:  Hidetaka Hamasaki; Yasuteru Hamasaki
Journal:  Front Endocrinol (Lausanne)       Date:  2017-08-15       Impact factor: 5.555

10.  Cardiovascular Autonomic Neuropathy and Glucose Variability in Patients With Type 1 Diabetes: Is There an Association?

Authors:  Szabolcs Nyiraty; Fruzsina Pesei; Andrea Orosz; Sara Coluzzi; Orsolya Eszter Vági; Csaba Lengyel; György Ábrahám; Simona Frontoni; Peter Kempler; Tamás Várkonyi
Journal:  Front Endocrinol (Lausanne)       Date:  2018-04-19       Impact factor: 5.555

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