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In Silico Validation of Personalized Safe Intervals for Carbohydrate Counting Errors
For patients with Type 1 diabetes mellitus (T1DM), accurate carbohydrate counting (CC) is essential for successful blood glucose regulation. Unfortunately, mistakes are common and may lead to an incorrect dosage of prandial insulin. In this work, we aim to demonstrate that each person has their own...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10574758/ https://www.ncbi.nlm.nih.gov/pubmed/37836392 http://dx.doi.org/10.3390/nu15194110 |
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author | Amorim, Débora Miranda, Francisco Abreu, Carlos |
author_facet | Amorim, Débora Miranda, Francisco Abreu, Carlos |
author_sort | Amorim, Débora |
collection | PubMed |
description | For patients with Type 1 diabetes mellitus (T1DM), accurate carbohydrate counting (CC) is essential for successful blood glucose regulation. Unfortunately, mistakes are common and may lead to an incorrect dosage of prandial insulin. In this work, we aim to demonstrate that each person has their own limits for CC errors, which can be computed using patient-specific data. To validate the proposed method, we tested it using several scenarios to investigate the effect of different CC errors on postprandial blood glucose. Virtual subjects from the T1DM Simulator were used in a clinical trial involving 450 meals over 90 days, all following the same daily meal plan but with different intervals for CC errors near, below, and above the limit computed for each patient. The results show that CC errors within personalized limits led to acceptable postprandial glycemic fluctuations. In contrast, experiments where 50% and 97.5% of the meals present a CC error outside the computed safe interval revealed a pronounced degradation of the time in range. Given these results, we consider the proposed method for obtaining personalized limits for CC errors an excellent starting point for an initial assessment of patients’ capabilities in CC and to provide appropriate ongoing education. |
format | Online Article Text |
id | pubmed-10574758 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-105747582023-10-14 In Silico Validation of Personalized Safe Intervals for Carbohydrate Counting Errors Amorim, Débora Miranda, Francisco Abreu, Carlos Nutrients Article For patients with Type 1 diabetes mellitus (T1DM), accurate carbohydrate counting (CC) is essential for successful blood glucose regulation. Unfortunately, mistakes are common and may lead to an incorrect dosage of prandial insulin. In this work, we aim to demonstrate that each person has their own limits for CC errors, which can be computed using patient-specific data. To validate the proposed method, we tested it using several scenarios to investigate the effect of different CC errors on postprandial blood glucose. Virtual subjects from the T1DM Simulator were used in a clinical trial involving 450 meals over 90 days, all following the same daily meal plan but with different intervals for CC errors near, below, and above the limit computed for each patient. The results show that CC errors within personalized limits led to acceptable postprandial glycemic fluctuations. In contrast, experiments where 50% and 97.5% of the meals present a CC error outside the computed safe interval revealed a pronounced degradation of the time in range. Given these results, we consider the proposed method for obtaining personalized limits for CC errors an excellent starting point for an initial assessment of patients’ capabilities in CC and to provide appropriate ongoing education. MDPI 2023-09-22 /pmc/articles/PMC10574758/ /pubmed/37836392 http://dx.doi.org/10.3390/nu15194110 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Amorim, Débora Miranda, Francisco Abreu, Carlos In Silico Validation of Personalized Safe Intervals for Carbohydrate Counting Errors |
title | In Silico Validation of Personalized Safe Intervals for Carbohydrate Counting Errors |
title_full | In Silico Validation of Personalized Safe Intervals for Carbohydrate Counting Errors |
title_fullStr | In Silico Validation of Personalized Safe Intervals for Carbohydrate Counting Errors |
title_full_unstemmed | In Silico Validation of Personalized Safe Intervals for Carbohydrate Counting Errors |
title_short | In Silico Validation of Personalized Safe Intervals for Carbohydrate Counting Errors |
title_sort | in silico validation of personalized safe intervals for carbohydrate counting errors |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10574758/ https://www.ncbi.nlm.nih.gov/pubmed/37836392 http://dx.doi.org/10.3390/nu15194110 |
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