Mixed
A personalized postprandial-targeting (PPT) diet, which uses machine learning to predict individual glycemic responses based on clinical and microbiome data, significantly improves glycemic control and metabolic health in newly diagnosed type 2 diabetes (T2DM) patients compared to a standard Mediterranean-style (MED) diet.
For newly diagnosed T2DM patients, a standard Mediterranean diet may not be sufficient. A personalized diet that predicts your specific blood sugar response to foods (using your microbiome and health data) is significantly more effective at lowering blood sugar and achieving remission than standard dietary advice. This approach requires technology (CGM and an app) but offers a path to diabetes remission (61% of participants in the long-term study) that standard diets do not guarantee.
In this crossover trial in subjects with newly diagnosed T2DM, a PPT diet improved CGM-based glycemic measures significantly more than a Mediterranean-style MED diet. Additional 6-month PPT intervention further improved glycemic control and metabolic health parameters, supporting the clinical efficacy of this approach.
Why this rating
The study is a randomized crossover trial with a small sample size (n=23 for crossover, n=16 for long-term) and is described as a 'pilot study' and 'proof-of-concept'.
Source
Effects of personalized diets by prediction of glycemic responses on glycemic control and metabolic health in newly diagnosed T2DM: a randomized dietary intervention pilot trial
Michal Rein et al. · BMC Medicine · 2022
DOI 10.1186/s12916-022-02254-y
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