Use of a diabetes-specific nutritional shake to replace a daily breakfast and afternoon snack improves glycemic responses assessed by continuous glucose monitoring in people with type 2 diabetes: a randomized clinical pilot study
Bibliographic record
Abstract
INTRODUCTION: This pilot study evaluated the impact of a diabetes-specific nutritional shake (DSNS) used twice daily by people with type 2 diabetes (T2D) on glycemic response assessed by continuous glucose monitoring (CGM). RESEARCH DESIGN AND METHODS: Adults (n=81) with T2D managed by oral medications were studied in a randomized, open-label, three-group parallel study design. The study was conducted in two phases over 14 days: Baseline (days 1-6), during which study participants consumed their habitual self-selected diets (SSD), followed by the Intervention (days 7-14), during which participants were randomized as follows: (1) SSD group received no study product (n=32); (2) DSNS breakfast/afternoon snack (Bkfst/AS) group consumed one DSNS as a breakfast meal replacement and a second to replace their mid-afternoon snack (n=24); (3) DSNS breakfast/prebed snack (Bkfst/PBS) group consumed one DSNS as a breakfast meal replacement and added a second as a prebed snack (n=25). Glucose was assessed by CGM throughout the study. Additionally, participants were asked about snacking behaviors, cravings, and other questions related to the use of DSNS as meal replacements and snacks. RESULTS: )) and adjusted peak value (mg/dL) when compared with the baseline phase. Participants consuming DSNS in place of their usual breakfast showed greater reductions in pAUC compared with the SSD group (p=0.008) for the DSNS Bkfst/AS group with a trend (p=0.069) for the DSNS Bkfst/PBS group. Adjusted peak value showed greater reductions in both DSNS groups as compared with the SSD group (p=0.002 for DSNS Bkfst/AS and p=0.010 for DSNS Bkfst/PBS). Nocturnal glucose variability was significantly decreased during the intervention phase compared with baseline phase in the DSNS Bkfst/AS group (p=0.020), with no significant differences between groups. After intervention, the DSNS Bkfst/AS group had a significantly lower percentage of participants (17%) reporting cravings for starchy meals/sides compared with before the study (33%) (p=0.046). This group also reported a significant increase in confidence in choosing foods to control their diabetes (from 58.3% to 91.7%, preintervention vs postintervention, respectively, p=0.005). CONCLUSIONS: Use of DSNS to replace breakfast and as an afternoon snack improves both glycemic control and behavioral factors related to dietary management of diabetes. TRAIL REGISTRATION NUMBER: NCT04230889.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".