Predictive models of post‐prandial glucose response in persons with prediabetes and early onset type 2 diabetes: A pilot study
Authors' conclusion
These data support a CGM-guided personalized nutrition and medicine approach to control PPGR in older individuals with prediabetes and diet and/or metformin-treated type 2 diabetes.
Study context
- Population
- Older adults (age 60 ± 7, BMI 33.0 ± 6.6 kg/m²) with prediabetes or early onset T2D
- Participants
- 35 vs 3
- Comparison
- Prediabetes vs Early onset T2D
- Prediabetesn = 35
- Early onset T2Dn = 3
- Outcome
- Predictive value of habitual CGM glucose excursions and fasting glucose on post-prandial glucose response (PPGR) after a research meal (MEAL-PPGR) and during an OGTT (OGTT-PPGR)
Methodological detailsfree-living conditions, continuous glucose monitor (CGM) over 2 weeks, actigraphy
- Free-living conditions
- CGM over 2 weeks
- Actigraphy
Main finding
As reported in the abstract
Prediction of PPGR
Mean amplitude of glucose excursions (MAGE) and fasting glucose predicting all measures of OGTT-PPGR (AUC, peak, delta, mean glucose, glucose at 120 min), R2
between 0.616 and 0.786
Adding Matsuda index, HOMA-B and HOMA-IR to fasting glucose and MAGE, R2
0.651 to 0.832
MAGE and premeal glucose predicting MEAL-PPGR, R2
0.546 to 0.722
Adding meal carbohydrates to prediction of 3 h AUC, R2 increase
from 0.723 to 0.761
Original publication
Predictive models of post‐prandial glucose response in persons with prediabetes and early onset type 2 diabetes: A pilot study. Diabetes Obes Metab. Published 2 January 2025. doi:10.
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