Automatic computation of the glycemic index: data driven analysis of the glucose standard
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arXiv
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| Main Authors: | , , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866917376368312320 |
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| author | Credali, Fabio Venuti, Maria Teresa Boffi, Daniele Rossi, Paola |
| author_facet | Credali, Fabio Venuti, Maria Teresa Boffi, Daniele Rossi, Paola |
| contents | The Glycemic Index (GI) is a tool for classifying carbohydrates based on their impact on postprandial glycemia, useful for diabetes prevention and management. This study applies a mathematical model for a data driven simulation of the glycemic response following glucose ingestion. The analysis is performed on a dataset of 35 healthy subjects undergone a standard 50 g oral glucose test. The results reveal a direct correlation between glucose response profiles and parameters describing glucose absorption, enabling the classification of subjects into three groups based on the timing of their glycemic peak: <30 min, 30-50 min, >50 min. These findings highlight the ability of a physiology-based mathematical model to capture inter-individual variability in postprandial glucose dynamics and represent a step toward simulation-based approaches for GI estimation. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2506_15471 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Automatic computation of the glycemic index: data driven analysis of the glucose standard Credali, Fabio Venuti, Maria Teresa Boffi, Daniele Rossi, Paola Dynamical Systems Quantitative Methods 92B05, 92C30, 92C42 The Glycemic Index (GI) is a tool for classifying carbohydrates based on their impact on postprandial glycemia, useful for diabetes prevention and management. This study applies a mathematical model for a data driven simulation of the glycemic response following glucose ingestion. The analysis is performed on a dataset of 35 healthy subjects undergone a standard 50 g oral glucose test. The results reveal a direct correlation between glucose response profiles and parameters describing glucose absorption, enabling the classification of subjects into three groups based on the timing of their glycemic peak: <30 min, 30-50 min, >50 min. These findings highlight the ability of a physiology-based mathematical model to capture inter-individual variability in postprandial glucose dynamics and represent a step toward simulation-based approaches for GI estimation. |
| title | Automatic computation of the glycemic index: data driven analysis of the glucose standard |
| topic | Dynamical Systems Quantitative Methods 92B05, 92C30, 92C42 |
| url | https://arxiv.org/abs/2506.15471 |