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Friedman JG, Smith EP, Awasty SS, Behan M, Genco MT, Hempel H, Jafri S, Jandarov R, Nagaraj T, Franco RS, Cohen RM. Primary care diabetes assessment when HbA1c and other measures of glycemia disagree. Prim Care Diabetes 2024; 18:151-156. [PMID: 38172007 DOI: 10.1016/j.pcd.2023.12.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/19/2023] [Revised: 12/08/2023] [Accepted: 12/23/2023] [Indexed: 01/05/2024]
Abstract
AIMS Although diabetes management decisions in primary care are typically based largely on HbA1c, mismatches between HbA1c and other measures of glycemia that are increasingly more available present challenges to optimal management. This study aimed to assess a systematic approach to identify the frequency of mismatches of potential clinical significance amongst various measures of glycemia in a primary care setting. METHODS Following screening to exclude conditions known to affect HbA1c interpretation, HbA1c, and fructosamine were obtained and repeated after ∼90 days on 53 adults with prediabetes or type 2 diabetes. A subset of 13 participants with repeat labs wore continuous glucose monitoring (CGM) for 10 days. RESULTS As expected, HbA1c and fructosamine only modestly correlated (initial R2 = 0.768/repeat R2 = 0.655). The HbA1c/fructosamine mismatch frequency of ± 0.5% (using the following regression HbA1c = 0.015 *fructosamine + 2.994 calculated from the initial sample) was 27.0%. Of the 13 participants with CGM data, HbA1c and CGM-based Glucose Management Indicator correlated at R2 = 0.786 with a mismatch frequency of ± 0.5% at 46.2% compared to a HbA1c/fructosamine mismatch frequency of ± 0.5% at 30.8%. CONCLUSIONS HbA1c is frequently mismatched with fructosamine and CGM data. As each of the measures has strengths and weaknesses, the utilization of multiple different measures of glycemia may be informative for diabetes assessment in the clinical setting.
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Affiliation(s)
- Jared G Friedman
- Department of Internal Medicine, University of Cincinnati College of Medicine, Cincinnati, OH, USA; Division of Endocrinology, Metabolism, and Molecular Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL USA.
| | - Eric P Smith
- Department of Internal Medicine, University of Cincinnati College of Medicine, Cincinnati, OH, USA
| | - Sanjana S Awasty
- Department of Internal Medicine, University of Cincinnati College of Medicine, Cincinnati, OH, USA; Division of Endocrinology, Diabetes, and Metabolism, The Ohio State University College of Medicine, Columbus, OH, USA
| | | | - Matthew T Genco
- Division of Endocrinology, Diabetes, and Metabolism, University of Cincinnati College of Medicine, Cincinnati, OH, USA; Cincinnati VA Medical Center, Cincinnati, OH, USA
| | - Hannah Hempel
- Department of Internal Medicine, University of Cincinnati College of Medicine, Cincinnati, OH, USA
| | - Sabih Jafri
- Department of Internal Medicine, University of Cincinnati College of Medicine, Cincinnati, OH, USA; Division of Endocrinology, Diabetes and Nutrition, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Roman Jandarov
- Department of Internal Medicine, University of Cincinnati College of Medicine, Cincinnati, OH, USA
| | | | - Robert S Franco
- Department of Internal Medicine, University of Cincinnati College of Medicine, Cincinnati, OH, USA
| | - Robert M Cohen
- Division of Endocrinology, Diabetes, and Metabolism, University of Cincinnati College of Medicine, Cincinnati, OH, USA; Cincinnati VA Medical Center, Cincinnati, OH, USA
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Friedman JG, Coyne K, Aleppo G, Szmuilowicz ED. Beyond A1C: exploring continuous glucose monitoring metrics in managing diabetes. Endocr Connect 2023; 12:e230085. [PMID: 37071558 PMCID: PMC10305570 DOI: 10.1530/ec-23-0085] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/14/2023] [Accepted: 04/18/2023] [Indexed: 04/19/2023]
Abstract
Hemoglobin A1c (HbA1c) has long been considered a cornerstone of diabetes mellitus (DM) management, as both an indicator of average glycemia and a predictor of long-term complications among people with DM. However, HbA1c is subject to non-glycemic influences which confound interpretation and as a measure of average glycemia does not provide information regarding glucose trends or about the occurrence of hypoglycemia and/or hyperglycemia episodes. As such, solitary use of HbA1c, without accompanying glucose data, does not confer actionable information that can be harnessed to guide targeted therapy in many patients with DM. While conventional capillary blood glucose monitoring (BGM) sheds light on momentary glucose levels, in practical use the inherent infrequency of measurement precludes elucidation of glycemic trends or reliable detection of hypoglycemia or hyperglycemia episodes. In contrast, continuous glucose monitoring (CGM) data reveal glucose trends and potentially undetected hypo- and hyperglycemia patterns that can occur between discrete BGM measurements. The use of CGM has grown significantly over the past decades as an ever-expanding body of literature demonstrates a multitude of clinical benefits for people with DM. Continually improving CGM accuracy and ease of use have further fueled the widespread adoption of CGM. Furthermore, percent time in range correlates well with HbA1c, is accepted as a validated indicator of glycemia, and is associated with the risk of several DM complications. We explore the benefits and limitations of CGM use, the use of CGM in clinical practice, and the application of CGM to advanced diabetes technologies.
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Affiliation(s)
- Jared G Friedman
- Division of Endocrinology, Metabolism and Molecular Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, United States
| | - Kasey Coyne
- Division of Endocrinology, Metabolism and Molecular Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, United States
| | - Grazia Aleppo
- Division of Endocrinology, Metabolism and Molecular Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, United States
| | - Emily D Szmuilowicz
- Division of Endocrinology, Metabolism and Molecular Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, United States
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Friedman JG, Cardona Matos Z, Szmuilowicz ED, Aleppo G. Use of Continuous Glucose Monitors to Manage Type 1 Diabetes Mellitus: Progress, Challenges, and Recommendations. Pharmgenomics Pers Med 2023; 16:263-276. [PMID: 37025558 PMCID: PMC10072139 DOI: 10.2147/pgpm.s374663] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2022] [Accepted: 02/25/2023] [Indexed: 04/08/2023] Open
Abstract
Type 1 diabetes (T1D) management has been revolutionized with the development and routine utilization of continuous glucose monitoring (CGM). CGM technology has allowed for the ability to track dynamic glycemic fluctuations and trends over time allowing for optimization of medical therapy and the prevention of dangerous hypoglycemic events. This review details currently-available real-time and intermittently-scanned CGM devices, clinical benefits, and challenges of CGM use, and current guidelines supporting its use in the clinical care of patients with T1D. We additionally describe future issues that will need to be addressed as CGM technology continues to evolve.
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Affiliation(s)
- Jared G Friedman
- Division of Endocrinology, Metabolism and Molecular Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | - Zulma Cardona Matos
- Division of Endocrinology, Metabolism and Molecular Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | - Emily D Szmuilowicz
- Division of Endocrinology, Metabolism and Molecular Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | - Grazia Aleppo
- Division of Endocrinology, Metabolism and Molecular Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
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