Background/Objectives: In pregnancy, beta-cell function is of interest since not only insulin resistance but also beta-cell dysfunction is common, especially when gestational diabetes mellitus (GDM) occurs. Typically, model-based beta-cell function is assessed with (at least) five-sample oral glucose tolerance test (OGTT). The aim of this study was to investigate whether the clinically common three-sample OGTT is sufficient for model-based beta-cell function assessment in pregnancy. Methods: We studied a group of pregnant women undergoing a 2 h five-sample OGTT with glucose, insulin, and C-peptide measurement at early and/or mid-pregnancy, for a total of 152 OGTTs. The five-sample OGTT was used for model-based beta-cell function assessment, yielding three beta-cell function parameters, i.e., glucose sensitivity (GSENS), potentiation factor ratio (PFR), and rate sensitivity (RSENS). GSENS, PFR, and RSENS assessment was repeated with the three-sample OGTT (at 0, 60, 120 min) and related values were compared to those from the five-sample OGTT (reference). Results: We found that, for GSENS, regression and Bland–Altman analyses showed satisfactory results (conditional and marginal R2 values: 0.56 and 0.75, p < 0.0001, and limits of agreement containing 94.2% of samples). Moreover, five-sample and three-sample OGTT GSENS versions were fully consistent in patient subgroup analyses. Results for PFR were less satisfactory but acceptable, whereas those for RSENS were not reliable. Conclusions: The three-sample OGTT is acceptable for model-based beta-cell function assessment in pregnancy, although not for all parameters. Our methodology may be used to explore the effect of time sample reduction in other in-silico models.

Beta-Cell Function Assessment by In-Silico Modeling Using Three Samples from an Oral Glucose Tolerance Test During Pregnancy Possibly Complicated by Gestational Diabetes / Gobl, C., Piersanti, A., Heinzl, F., Linder, T., Morettini, M., Tura, A.. - In: DIABETOLOGY. - ISSN 2673-4540. - 7:3(2026). [10.3390/diabetology7030048]

Beta-Cell Function Assessment by In-Silico Modeling Using Three Samples from an Oral Glucose Tolerance Test During Pregnancy Possibly Complicated by Gestational Diabetes

Piersanti A.;Morettini M.;
2026-01-01

Abstract

Background/Objectives: In pregnancy, beta-cell function is of interest since not only insulin resistance but also beta-cell dysfunction is common, especially when gestational diabetes mellitus (GDM) occurs. Typically, model-based beta-cell function is assessed with (at least) five-sample oral glucose tolerance test (OGTT). The aim of this study was to investigate whether the clinically common three-sample OGTT is sufficient for model-based beta-cell function assessment in pregnancy. Methods: We studied a group of pregnant women undergoing a 2 h five-sample OGTT with glucose, insulin, and C-peptide measurement at early and/or mid-pregnancy, for a total of 152 OGTTs. The five-sample OGTT was used for model-based beta-cell function assessment, yielding three beta-cell function parameters, i.e., glucose sensitivity (GSENS), potentiation factor ratio (PFR), and rate sensitivity (RSENS). GSENS, PFR, and RSENS assessment was repeated with the three-sample OGTT (at 0, 60, 120 min) and related values were compared to those from the five-sample OGTT (reference). Results: We found that, for GSENS, regression and Bland–Altman analyses showed satisfactory results (conditional and marginal R2 values: 0.56 and 0.75, p < 0.0001, and limits of agreement containing 94.2% of samples). Moreover, five-sample and three-sample OGTT GSENS versions were fully consistent in patient subgroup analyses. Results for PFR were less satisfactory but acceptable, whereas those for RSENS were not reliable. Conclusions: The three-sample OGTT is acceptable for model-based beta-cell function assessment in pregnancy, although not for all parameters. Our methodology may be used to explore the effect of time sample reduction in other in-silico models.
2026
beta-cell function; diagnostic oral glucose tolerance test; gestational diabetes; glucose sensitivity; mathematical modeling; pregnancy
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11566/364289
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