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Bolus Estimation—Rethinking the Effect of Meal Fat Content

Background: Traditionally, insulin bolus calculations for managing postprandial glucose levels in individuals with type 1 diabetes rely solely on the carbohydrate content of a meal. However, recent studies have reported that other macronutrients in a meal can alter the insulin required for good post...

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Autores principales: Laxminarayan, Srinivas, Reifman, Jaques, Edwards, Stephanie S., Wolpert, Howard, Steil, Garry M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Mary Ann Liebert, Inc. 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4677112/
https://www.ncbi.nlm.nih.gov/pubmed/26270134
http://dx.doi.org/10.1089/dia.2015.0118
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author Laxminarayan, Srinivas
Reifman, Jaques
Edwards, Stephanie S.
Wolpert, Howard
Steil, Garry M.
author_facet Laxminarayan, Srinivas
Reifman, Jaques
Edwards, Stephanie S.
Wolpert, Howard
Steil, Garry M.
author_sort Laxminarayan, Srinivas
collection PubMed
description Background: Traditionally, insulin bolus calculations for managing postprandial glucose levels in individuals with type 1 diabetes rely solely on the carbohydrate content of a meal. However, recent studies have reported that other macronutrients in a meal can alter the insulin required for good postprandial control. Specifically, studies have shown that high-fat (HF) meals require more insulin than low-fat (LF) meals with identical carbohydrate content. Our objective was to assess the mechanisms underlying the higher insulin requirement observed in one of these studies. Materials and Methods: We used a combination of previously validated metabolic models to fit data from a study comparing HF and LF dinners with identical carbohydrate content in seven subjects with type 1 diabetes. For each subject and dinner type, we estimated the model parameters representing the time of peak meal-glucose appearance (τ(m)), insulin sensitivity (S(I)), the net hepatic glucose balance, and the glucose effect at zero insulin in four time windows (dinner, early night, late night, and breakfast) and assessed the differences in model parameters via paired Wilcoxon signed-rank tests. Results: During the HF meal, the τ(m) was significantly delayed (mean and standard error [SE]: 102 [14] min vs. 71 [4] min; P = 0.02), and S(I) was significantly lower (7.25 × 10(−4) [1.29 × 10(−4)] mL/μU/min vs. 8.72 × 10(−4) [1.08 × 10(−4)] mL/μU/min; P = 0.02). Conclusions: In addition to considering the putative delay in gastric emptying associated with HF meals, we suggest that clinicians reviewing patient records consider that the fat content of these meals may alter S(I).
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spelling pubmed-46771122015-12-15 Bolus Estimation—Rethinking the Effect of Meal Fat Content Laxminarayan, Srinivas Reifman, Jaques Edwards, Stephanie S. Wolpert, Howard Steil, Garry M. Diabetes Technol Ther Original Articles Background: Traditionally, insulin bolus calculations for managing postprandial glucose levels in individuals with type 1 diabetes rely solely on the carbohydrate content of a meal. However, recent studies have reported that other macronutrients in a meal can alter the insulin required for good postprandial control. Specifically, studies have shown that high-fat (HF) meals require more insulin than low-fat (LF) meals with identical carbohydrate content. Our objective was to assess the mechanisms underlying the higher insulin requirement observed in one of these studies. Materials and Methods: We used a combination of previously validated metabolic models to fit data from a study comparing HF and LF dinners with identical carbohydrate content in seven subjects with type 1 diabetes. For each subject and dinner type, we estimated the model parameters representing the time of peak meal-glucose appearance (τ(m)), insulin sensitivity (S(I)), the net hepatic glucose balance, and the glucose effect at zero insulin in four time windows (dinner, early night, late night, and breakfast) and assessed the differences in model parameters via paired Wilcoxon signed-rank tests. Results: During the HF meal, the τ(m) was significantly delayed (mean and standard error [SE]: 102 [14] min vs. 71 [4] min; P = 0.02), and S(I) was significantly lower (7.25 × 10(−4) [1.29 × 10(−4)] mL/μU/min vs. 8.72 × 10(−4) [1.08 × 10(−4)] mL/μU/min; P = 0.02). Conclusions: In addition to considering the putative delay in gastric emptying associated with HF meals, we suggest that clinicians reviewing patient records consider that the fat content of these meals may alter S(I). Mary Ann Liebert, Inc. 2015-12-01 /pmc/articles/PMC4677112/ /pubmed/26270134 http://dx.doi.org/10.1089/dia.2015.0118 Text en © The Author(s) 2015; Published by Mary Ann Liebert, Inc. This Open Access article is distributed under the terms of the Creative Commons Attribution Noncommercial License (http://creativecommons.org/licenses/by-nc/4.0/) which permits any noncommercial use, distribution, and reproduction in any medium, provided the original author(s) and the source are credited.
spellingShingle Original Articles
Laxminarayan, Srinivas
Reifman, Jaques
Edwards, Stephanie S.
Wolpert, Howard
Steil, Garry M.
Bolus Estimation—Rethinking the Effect of Meal Fat Content
title Bolus Estimation—Rethinking the Effect of Meal Fat Content
title_full Bolus Estimation—Rethinking the Effect of Meal Fat Content
title_fullStr Bolus Estimation—Rethinking the Effect of Meal Fat Content
title_full_unstemmed Bolus Estimation—Rethinking the Effect of Meal Fat Content
title_short Bolus Estimation—Rethinking the Effect of Meal Fat Content
title_sort bolus estimation—rethinking the effect of meal fat content
topic Original Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4677112/
https://www.ncbi.nlm.nih.gov/pubmed/26270134
http://dx.doi.org/10.1089/dia.2015.0118
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