ArticleDiabetes, obesity & metabolism2025
Predictive models of post-prandial glucose response in persons with prediabetes and early onset type 2 diabetes: A pilot study.
Article in Diabetes, obesity & metabolism, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
5 citing papers in PubMed.
- Incorporating 25 g/d of Pea Fiber into Food for 4 Wk Reduces Glucose Area under the Curve in Individuals with Overweight and Obesity.The Journal of nutrition · 2026Trial
- A Randomized Controlled Trial to Evaluate the Effects of Full-Fat and Low-Fat Fermented Dairy Foods on Markers of Cardiometabolic Health in Adults with Overweight or Obesity and Elevated Fasting Triglycerides.Current developments in nutrition · 2026Article
- Beyond HbA1c: A CGM-centred three-pillar framework for glycaemic variability in pre-diabetes and type 2 diabetes.Diabetic medicine : a journal of the British Diabetic Association · 2026Review
- Postprandial Glucose Spikes in Free-Living Adults With Normoglycaemia Are Associated With Modifiable Dietary and Temporal Factors: A Real-World CGM Study.Diabetes, obesity & metabolism · 2026Article
- Post-translational modifications orchestrate mTOR-driven cell death in cardiovascular disease.Frontiers in cardiovascular medicine · 2025Review
Corrections and comments
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Authors and funding
10 authors.
Funding
Abstract
objectivePost-prandial glucose response (PPGR) is a risk factor for cardiovascular disease. Meal carbohydrate content is an important predictor of PPGR, but dietary interventions to mitigate PPGR are not always successful. A personalized approach, considering behaviour and habitual pattern of glucose excursions assessed by continuous glucose monitor (CGM), may be more effective. RESEARCH DESIGN AND
methodsData were collected under free-living conditions, over 2 weeks, in older adults (age 60 ± 7, BMI 33.0 ± 6.6 kg/m
resultsMean amplitude of glucose excursions (MAGE) and fasting glucose were highly predictive of all measures of OGTT-PPGR (AUC, peak, delta, mean glucose and glucose at 120 min; R
conclusionThese 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.
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Registered trials
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