Impact of Continuous Glucose Monitoring Versus Blood Glucose Monitoring to Support a Carbohydrate-Restricted Nutrition Intervention in People with Type 2 Diabetes

<b><i>Introduction:</i></b> Low- and very-low-carbohydrate eating patterns, including ketogenic eating, can reduce glycated hemoglobin (HbA1c) in people with type 2 diabetes (T2D). Continuous glucose monitoring (CGM) has also been shown to improve glycemic outcomes, such as time in range (TIR; % time with glucose 70-180 mg/dL), more than blood glucose monitoring (BGM). CGM-guided nutrition interventions are sparse. The primary objective of this study was to compare differences in change in TIR when people with T2D used either CGM or BGM to guide dietary intake and medication management during a medically supervised ketogenic diet program (MSKDP) delivered via continuous remote care. <b><i>Methods:</i></b> IGNITE (Impact of Glucose moNitoring and nutrItion on Time in rangE) study participants were randomized to use CGM (<i>n</i> = 81) or BGM (<i>n</i> = 82) as part of a MSKDP. Participants and their care team used CGM and BGM data to support dietary choices and medication management. Glycemia, medication use, ketones, dietary intake, and weight were assessed at baseline (Base), month 1 (M1), and month 3 (M3); differences between arms and timepoints were evaluated. <b><i>Results:</i></b> Adults (<i>n</i> = 163) with a mean (standard deviation) T2D duration of 9.7 (7.7) years and HbA1c of 8.1% (1.2%) participated. TIR improved from Base to M3, 61-89% for CGM and 63%-85% for BGM (<i>P</i> < 0.001), with no difference in change between arms (<i>P</i> = 0.26). Additional CGM metrics also improved by M1, and improvements were sustained through M3. HbA1c decreased by ≥1.5% from Base to M3 for both CGM and BGM arms (<i>P</i> < 0.001). Diabetes medications were de-intensified based on change in medication effect scores from Base to M3 (<i>P</i> < 0.001). Total energy and carbohydrate intake decreased (<i>P</i> < 0.001), and participants in both arms lost clinically significant weight (<i>P</i> < 0.001). <b><i>Conclusion:</i></b> Both the CGM and BGM arms saw similar and significant improvements in glycemia and other diabetes-related outcomes during this MSKDP. Additional CGM-guided nutrition intervention research is needed.

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Publication Details

Journal
Diabetes Technology & Therapeutics
Published
2024-11-11
DOI
https://doi.org/10.1089/dia.2024.0406
Citations
7
Primary Topic
Diabetes Management and Research
Type
article
Field-Weighted Citation Impact
2.50
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article

Impact of Continuous Glucose Monitoring Versus Blood Glucose Monitoring to Support a Carbohydrate-Restricted Nutrition Intervention in People with Type 2 Diabetes

Shaminie J. Athinarayanan, Rebecca N. Adams, Stephen E. Asche, Richard M. Bergenstal et al.
7 citations
Diabetes Technology & Therapeutics
Diabetes Management and Research
2.50
article

Impact of Continuous Glucose Monitoring Versus Blood Glucose Monitoring to Support a Carbohydrate-Restricted Nutrition Intervention in People with Type 2 Diabetes

Shaminie J. Athinarayanan, Rebecca N. Adams, Stephen E. Asche, Richard M. Bergenstal, Amy L. McKenzie, Caroline G. P. Roberts, Holly Willis, Brittanie M. Volk, Shannon Krizka, Alison R. Zoller
article en
7 citations

Abstract

<b><i>Introduction:</i></b> Low- and very-low-carbohydrate eating patterns, including ketogenic eating, can reduce glycated hemoglobin (HbA1c) in people with type 2 diabetes (T2D). Continuous glucose monitoring (CGM) has also been shown to improve glycemic outcomes, such as time in range (TIR; % time with glucose 70-180 mg/dL), more than blood glucose monitoring (BGM). CGM-guided nutrition interventions are sparse. The primary objective of this study was to compare differences in change in TIR when people with T2D used either CGM or BGM to guide dietary intake and medication management during a medically supervised ketogenic diet program (MSKDP) delivered via continuous remote care. <b><i>Methods:</i></b> IGNITE (Impact of Glucose moNitoring and nutrItion on Time in rangE) study participants were randomized to use CGM (<i>n</i> = 81) or BGM (<i>n</i> = 82) as part of a MSKDP. Participants and their care team used CGM and BGM data to support dietary choices and medication management. Glycemia, medication use, ketones, dietary intake, and weight were assessed at baseline (Base), month 1 (M1), and month 3 (M3); differences between arms and timepoints were evaluated. <b><i>Results:</i></b> Adults (<i>n</i> = 163) with a mean (standard deviation) T2D duration of 9.7 (7.7) years and HbA1c of 8.1% (1.2%) participated. TIR improved from Base to M3, 61-89% for CGM and 63%-85% for BGM (<i>P</i> < 0.001), with no difference in change between arms (<i>P</i> = 0.26). Additional CGM metrics also improved by M1, and improvements were sustained through M3. HbA1c decreased by ≥1.5% from Base to M3 for both CGM and BGM arms (<i>P</i> < 0.001). Diabetes medications were de-intensified based on change in medication effect scores from Base to M3 (<i>P</i> < 0.001). Total energy and carbohydrate intake decreased (<i>P</i> < 0.001), and participants in both arms lost clinically significant weight (<i>P</i> < 0.001). <b><i>Conclusion:</i></b> Both the CGM and BGM arms saw similar and significant improvements in glycemia and other diabetes-related outcomes during this MSKDP. Additional CGM-guided nutrition intervention research is needed.

Diabetes Technology & TherapeuticsVol. 27(5)
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Diabetes Management and Research
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