The effect of a low glycemic index diet on gestational hyperglycemia: A pilot trial
Bibliographic record
Abstract
The main objective of this study was to determine the effect of a low glycemic index (low‐GI) diet on fasting glucose, HbA1c and self monitored blood glucose (SMBG). Secondary outcomes included intervention feasibility, maternal weight gain and infant birth‐weight. Women (n=47) with gestational diabetes or impaired glucose tolerance of pregnancy were randomized to low‐GI (n=23) or control (n=24) diets and were followed from 28 weeks gestation until delivery. This study was conducted at St. Michael's Hospital, Toronto. Diet GI was significantly higher on control, 58 (95% CI:56,60) than low‐GI, 49 (47,51; p=0.001). Glycemic control improved in both groups (p<0.05) with no significant difference between groups. SMBG after breakfast was directly related to pre‐pregnancy BMI in the control but not the Low‐GI group (p=0.021). Mean infant birth weight on low‐GI was less than on control (not significant). Maternal weight gain was not significantly different between groups. Study foods were rated “good” by participants. Participants were willing to consume them post‐intervention. A low‐GI diet was accepted by participants and attenuated the relationship between pre‐pregnancy BMI and postprandial SMBG.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".