Literature DB >> 28322063

Discrepancies Between Blood Glucose and Interstitial Glucose-Technological Artifacts or Physiology: Implications for Selection of the Appropriate Therapeutic Target.

Thorsten Siegmund1, Lutz Heinemann2, Ralf Kolassa3, Andreas Thomas4.   

Abstract

BACKGROUND: For decades, the major source of information used to make therapeutic decisions by patients with diabetes has been glucose measurements using capillary blood samples. Knowledge gained from clinical studies, for example, on the impact of metabolic control on diabetes-related complications, is based on such measurements. Different to traditional blood glucose measurement systems, systems for continuous glucose monitoring (CGM) measure glucose in interstitial fluid (ISF). The assumption is that glucose levels in blood and ISF are practically the same and that the information provided can be used interchangeably. Thus, therapeutic decisions, that is, the selection of insulin doses, are based on CGM system results interpreted as though they were blood glucose values.
METHODS: We performed a more detailed analysis and interpretation of glucose profiles obtained with CGM in situations with high glucose dynamics to evaluate this potentially misleading assumption.
RESULTS: Considering physical activity, hypoglycemic episodes, and meal-related differences between glucose levels in blood and ISF uncover clinically relevant differences that can make it risky from a therapeutic point of view to use blood glucose for therapeutic decisions.
CONCLUSIONS: Further systematic and structured evaluation as to whether the use of ISF glucose is more safe and efficient when it comes to acute therapeutic decisions is necessary. These data might also have a higher prognostic relevance when it comes to long-term metabolic consequences of diabetes. In the long run, it may be reasonable to abandon blood glucose measurements as the basis for diabetes management and switch to using ISF glucose as the appropriate therapeutic target.

Entities:  

Keywords:  blood glucose; continuous glucose monitoring; glucose variability; interstitial glucose; physiology of glucose regulation

Mesh:

Substances:

Year:  2017        PMID: 28322063      PMCID: PMC5588840          DOI: 10.1177/1932296817699637

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


  14 in total

1.  Assessing the Accuracy of Continuous Glucose Monitoring (CGM) Calibrated With Capillary Values Using Capillary or Venous Glucose Levels as a Reference.

Authors:  Mervi Andelin; Jort Kropff; Viktorija Matuleviciene; Jeffrey I Joseph; Stig Attvall; Elvar Theodorsson; Irl B Hirsch; Henrik Imberg; Sofia Dahlqvist; David Klonoff; Börje Haraldsson; J Hans DeVries; Marcus Lind
Journal:  J Diabetes Sci Technol       Date:  2016-06-28

2.  Graphical and numerical evaluation of continuous glucose sensing time lag.

Authors:  Boris P Kovatchev; Devin Shields; Marc Breton
Journal:  Diabetes Technol Ther       Date:  2009-03       Impact factor: 6.118

Review 3.  Delays in minimally invasive continuous glucose monitoring devices: a review of current technology.

Authors:  D Barry Keenan; John J Mastrototaro; Gayane Voskanyan; Garry M Steil
Journal:  J Diabetes Sci Technol       Date:  2009-09-01

4.  Significance and Reliability of MARD for the Accuracy of CGM Systems.

Authors:  Florian Reiterer; Philipp Polterauer; Michael Schoemaker; Guenther Schmelzeisen-Redecker; Guido Freckmann; Lutz Heinemann; Luigi Del Re
Journal:  J Diabetes Sci Technol       Date:  2016-09-25

5.  Rate-of-Change Dependence of the Performance of Two CGM Systems During Induced Glucose Swings.

Authors:  Stefan Pleus; Michael Schoemaker; Karin Morgenstern; Günther Schmelzeisen-Redeker; Cornelia Haug; Manuela Link; Eva Zschornack; Guido Freckmann
Journal:  J Diabetes Sci Technol       Date:  2015-04-07

6.  Contribution of an intrinsic lag of continuous glucose monitoring systems to differences in measured and actual glucose concentrations changing at variable rates in vitro.

Authors:  Raymond J Davey; Chee Low; Timothy W Jones; Paul A Fournier
Journal:  J Diabetes Sci Technol       Date:  2010-11-01

Review 7.  Can interstitial glucose assessment replace blood glucose measurements?

Authors:  K Rebrin; G M Steil
Journal:  Diabetes Technol Ther       Date:  2000       Impact factor: 6.118

8.  Subcutaneous glucose predicts plasma glucose independent of insulin: implications for continuous monitoring.

Authors:  K Rebrin; G M Steil; W P van Antwerp; J J Mastrototaro
Journal:  Am J Physiol       Date:  1999-09

9.  Unrecognized hypo- and hyperglycemia in well-controlled patients with type 2 diabetes mellitus: the results of continuous glucose monitoring.

Authors:  L C Hay; E G Wilmshurst; Gregory Fulcher
Journal:  Diabetes Technol Ther       Date:  2003       Impact factor: 6.118

10.  Time lag of glucose from intravascular to interstitial compartment in humans.

Authors:  Ananda Basu; Simmi Dube; Michael Slama; Isabel Errazuriz; Jose Carlos Amezcua; Yogish C Kudva; Thomas Peyser; Rickey E Carter; Claudio Cobelli; Rita Basu
Journal:  Diabetes       Date:  2013-09-05       Impact factor: 9.461

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  13 in total

1.  Benefits and Limitations of MARD as a Performance Parameter for Continuous Glucose Monitoring in the Interstitial Space.

Authors:  Lutz Heinemann; Michael Schoemaker; Günther Schmelzeisen-Redecker; Rolf Hinzmann; Adham Kassab; Guido Freckmann; Florian Reiterer; Luigi Del Re
Journal:  J Diabetes Sci Technol       Date:  2019-06-19

2.  Discrepancies Between Blood Glucose and Interstitial Glucose: Technological Artifacts or Physiology: A Reply.

Authors:  Eberhard Biermann
Journal:  J Diabetes Sci Technol       Date:  2018-05-20

3.  Response to "Discrepancies Between Blood Glucose and Interstitial Glucose-Technological Artifacts or Physiology: A Reply".

Authors:  Thorsten Siegmund; Lutz Heinemann; Ralph Kolassa; Andrea Thomas
Journal:  J Diabetes Sci Technol       Date:  2018-04-18

Review 4.  Improving the clinical value and utility of CGM systems: issues and recommendations : A joint statement of the European Association for the Study of Diabetes and the American Diabetes Association Diabetes Technology Working Group.

Authors:  John R Petrie; Anne L Peters; Richard M Bergenstal; Reinhard W Holl; G Alexander Fleming; Lutz Heinemann
Journal:  Diabetologia       Date:  2017-10-25       Impact factor: 10.122

5.  Microneedle Aptamer-Based Sensors for Continuous, Real-Time Therapeutic Drug Monitoring.

Authors:  Yao Wu; Farshad Tehrani; Hazhir Teymourian; John Mack; Alexander Shaver; Maria Reynoso; Jonathan Kavner; Nickey Huang; Allison Furmidge; Andrés Duvvuri; Yuhang Nie; Lori M Laffel; Francis J Doyle; Mary-Elizabeth Patti; Eyal Dassau; Joseph Wang; Netzahualcóyotl Arroyo-Currás
Journal:  Anal Chem       Date:  2022-06-02       Impact factor: 8.008

6.  Can Type 2 Diabetes Sufferers Actually Estimate Serum Glucose Level From Interstitial Fluid Glucose Level: A Diabetes Patient's Experience.

Authors:  Dennis A Fried; Robert Fried
Journal:  J Patient Exp       Date:  2019-05-21

Review 7.  Algorithms for Automated Insulin Delivery: An Overview.

Authors:  Andreas Thomas; Lutz Heinemann
Journal:  J Diabetes Sci Technol       Date:  2021-05-06

Review 8.  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

Review 9.  Use of continuous glucose monitoring trend arrows in the younger population with type 1 diabetes.

Authors:  Nancy Elbarbary; Othmar Moser; Saif Al Yaarubi; Hussain Alsaffar; Adnan Al Shaikh; Ramzi A Ajjan; Asma Deeb
Journal:  Diab Vasc Dis Res       Date:  2021 Nov-Dec       Impact factor: 3.291

Review 10.  Leveraging advances in diabetes technologies in primary care: a narrative review.

Authors:  Bruce Bode; Aaron King; David Russell-Jones; Liana K Billings
Journal:  Ann Med       Date:  2021-12       Impact factor: 4.709

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