Literature DB >> 30151979

Going beyond HbA1c to understand the benefits of advanced diabetes therapies.

Robert A Vigersky1,2.   

Abstract

The gold standard for monitoring overall glycemia is HbA1c. However, HbA1c has several important limitations, giving more weight to the prior 2 to 3 months rather than short-term glycemic control. In addition, the level of the HbA1c does not reflect the important interpersonal differences in its relationship with mean glucose, and HbA1c is affected by many common clinical conditions (anemia, uremia) that can interfere with the accuracy of its measurement in the laboratory. The development and refinement of continuous glucose monitoring (CGM), a glucose- and patient-centric technology, over the past two decades have permitted the creation of new single and composite metrics, such as the percentage of time in range and the glucose pentagon, respectively, which provide clinically relevant insights into short-term glycemic control. In addition, CGM creates new outcome metrics for clinical management and investigational studies (percentage of time in hypoglycemia, percentage of time in target range) that can accurately and meaningfully report the effects of an intervention, whether that is a drug, a device, or a psychosocial program, and CGM provides the key input to drive algorithm-based insulin delivery. Finally, CGM linked with artificial intelligence permits real-time feedback to patients about modifiable patterns of glycemic excursions.
© 2018 Ruijin Hospital, Shanghai Jiaotong University School of Medicine and John Wiley & Sons Australia, Ltd.

Entities:  

Keywords:  beyond HbA1c; composite metrics; continuous glucose monitoring; diabetes technology; 动态血糖监测; 复合指标; 糖尿病诊疗技术; 超越HbA1c

Mesh:

Substances:

Year:  2018        PMID: 30151979     DOI: 10.1111/1753-0407.12846

Source DB:  PubMed          Journal:  J Diabetes        ISSN: 1753-0407            Impact factor:   4.006


  8 in total

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2.  The variability of glycated hemoglobin is associated with renal function decline in patients with type 2 diabetes.

Authors:  Chia-Lin Lee; Cheng-Hsu Chen; Ming-Ju Wu; Shang-Feng Tsai
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Review 3.  Individualizing Time-in-Range Goals in Management of Diabetes Mellitus and Role of Insulin: Clinical Insights From a Multinational Panel.

Authors:  Sanjay Kalra; Shehla Shaikh; Gagan Priya; Manas P Baruah; Abhyudaya Verma; Ashok K Das; Mona Shah; Sambit Das; Deepak Khandelwal; Debmalya Sanyal; Sujoy Ghosh; Banshi Saboo; Ganapathi Bantwal; Usha Ayyagari; Daphne Gardner; Cecilia Jimeno; Nancy E Barbary; Khadijah A Hafidh; Jyoti Bhattarai; Tania T Minulj; Hendra Zufry; Uditha Bulugahapitiya; Moosa Murad; Alexander Tan; Selim Shahjada; Mijinyawa B Bello; Prasad Katulanda; Gracjan Podgorski; Wajeeha I AbuHelaiqa; Rima Tan; Ali Latheef; Sedeshan Govender; Samir H Assaad-Khalil; Cecilia Kootin-Sanwu; Ansumali Joshi; Faruque Pathan; Diana A Nkansah
Journal:  Diabetes Ther       Date:  2020-12-26       Impact factor: 2.945

4.  Relationship of continuous glucose monitoring-related metrics with HbA1c and residual β-cell function in Japanese patients with type 1 diabetes.

Authors:  Naru Babaya; Shinsuke Noso; Yoshihisa Hiromine; Yasunori Taketomo; Fumimaru Niwano; Sawa Yoshida; Sara Yasutake; Yumiko Kawabata; Hiroshi Ikegami
Journal:  Sci Rep       Date:  2021-02-17       Impact factor: 4.379

5.  The Correlation between Time in Range and Diabetic Microvascular Complications Utilizing Information Management Platform.

Authors:  Xia Sheng; Guo-Hui Xiong; Peng-Fei Yu; Jian-Ping Liu
Journal:  Int J Endocrinol       Date:  2020-12-15       Impact factor: 3.257

6.  Association of Time in Range with Endothelial Injury in Patients with Type 2 Diabetes Treated with Exenatide.

Authors:  Yunyi Le; Kun Yang; Jin Yang; Wei Fu; Wenhua Xiao; Rui Wei; Tianpei Hong
Journal:  Diabetes Ther       Date:  2022-08-13       Impact factor: 3.595

Review 7.  Fit-for-Purpose Biometric Monitoring Technologies: Leveraging the Laboratory Biomarker Experience.

Authors:  Alan Godfrey; Benjamin Vandendriessche; Jessie P Bakker; Cheryl Fitzer-Attas; Ninad Gujar; Matthew Hobbs; Qi Liu; Carrie A Northcott; Virginia Parks; William A Wood; Vadim Zipunnikov; John A Wagner; Elena S Izmailova
Journal:  Clin Transl Sci       Date:  2020-08-25       Impact factor: 4.689

8.  A Systematic Review of Collective Evidences Investigating the Effect of Diabetes Monitoring Systems and Their Application in Health Care.

Authors:  Maria Kamusheva; Konstantin Tachkov; Maria Dimitrova; Zornitsa Mitkova; Gema García-Sáez; M Elena Hernando; Wim Goettsch; Guenka Petrova
Journal:  Front Endocrinol (Lausanne)       Date:  2021-03-16       Impact factor: 5.555

  8 in total

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