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...
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-09-01
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| Series: | Nutrients |
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| Online Access: | https://www.mdpi.com/2072-6643/15/19/4110 |
| _version_ | 1797575385785827328 |
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| author | Débora Amorim Francisco Miranda Carlos Abreu |
| author_facet | Débora Amorim Francisco Miranda Carlos Abreu |
| author_sort | Débora Amorim |
| collection | DOAJ |
| 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. |
| first_indexed | 2024-03-10T21:38:44Z |
| format | Article |
| id | doaj.art-770cd922c28246b7b9c52785d11d861b |
| institution | Directory Open Access Journal |
| issn | 2072-6643 |
| language | English |
| last_indexed | 2024-03-10T21:38:44Z |
| publishDate | 2023-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Nutrients |
| spelling | doaj.art-770cd922c28246b7b9c52785d11d861b2023-11-19T14:50:18ZengMDPI AGNutrients2072-66432023-09-011519411010.3390/nu15194110In Silico Validation of Personalized Safe Intervals for Carbohydrate Counting ErrorsDébora Amorim0Francisco Miranda1Carlos Abreu2ADiT-LAB, Instituto Politécnico de Viana do Castelo, Rua Escola Industrial e Comercial de Nun’Álvares, 4900-347 Viana do Castelo, PortugalInstituto Politécnico de Viana do Castelo, Rua Escola Industrial e Comercial de Nun’Álvares, 4900-347 Viana do Castelo, PortugalADiT-LAB, Instituto Politécnico de Viana do Castelo, Rua Escola Industrial e Comercial de Nun’Álvares, 4900-347 Viana do Castelo, PortugalFor 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.https://www.mdpi.com/2072-6643/15/19/4110type 1 diabetes mellitusinsulin therapypersonalized medicinecarbohydrate counting errors |
| spellingShingle | Débora Amorim Francisco Miranda Carlos Abreu In Silico Validation of Personalized Safe Intervals for Carbohydrate Counting Errors Nutrients type 1 diabetes mellitus insulin therapy personalized medicine 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 | type 1 diabetes mellitus insulin therapy personalized medicine carbohydrate counting errors |
| url | https://www.mdpi.com/2072-6643/15/19/4110 |
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