A Slow-Digesting, Low-Glycemic Load Nutritional Beverage Improves Glucose Tolerance in Obese Pregnant Women Without Gestational Diabetes
Bibliographic record
Abstract
BACKGROUND: Obesity is a risk factor for gestational diabetes (gestational diabetes). Low-glycemic index diets attenuate hyperglycemia. We designed a study to determine whether a slow-digesting, low-glycemic load (SD-LGL) beverage improves glucose tolerance in obese pregnant women without GDM. METHODS: ) were recruited at 24-28 weeks to receive either the SD-LGL or eucaloric control beverage. This was consumed with breakfast and as a midafternoon snack over 2 days with a controlled diet. Following a 2-day washout period of habitual diet, women completed 2 days on the alternative beverage with controlled diet. A 10-h fast preceded each intervention phase. Twenty-four hour glucose was measured using continuous glucose monitoring. RESULTS: Consumption of the lower GL beverage was associated with improved measures of glycemia, compared with the control beverage and habitual diet at different time periods. Glucose estimates for control versus SD-LDL at 24 h (0.23 mmol/L [0.16 to 0.31], P < 0.001), daytime (0.26 mmol/L [0.18 to 0.34], P < 0.001), and nighttime (0.05 mmol/L [-0.01 to 0.11], P = 0.09). Postprandial glucose was lower after breakfast but not after dinner, compared with the control beverage (0.09 mmol/L [0.01 to 0.18], P = 0.03). CONCLUSION: A slow-digesting, low-glycemic nutritional beverage may facilitate improved glucose control in obese pregnant women. To address potential benefit for clinical outcomes, a randomized controlled trial is warranted.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".