Effects of a Lifestyle Intervention in Young Women with GDM and Subsequent Diabetes
Bibliographic record
Abstract
The purpose of this study was to examine whether a 9-month intensive lifestyle intervention could lead to weight loss and improve cardiovascular risk factors among young women with both gestational diabetes mellitus (GDM) and newly diagnosed diabetes. A total of 83 young women, who had GDM and were subsequently diagnosed as type 2 diabetes at an average of 2.6 years after delivery, participated in a 9-month intensive lifestyle intervention and a follow-up survey at 6-9 years postintervention. After the 9-month intervention, these women had a weight loss of 2.90 kg (-4.02% of initial weight), decreased waist circumference (-3.12 cm), body fat (-1.75%), diastolic blood pressure (-3.49 mmHg), fasting glucose (-0.98 mmol/L) and HbA1c (-0.72%). During the 6-9 years postintervention period, they still had lower weight (-3.71 kg; -4.62% of initial weight), decreased waist circumference (-4.56 cm) and body fat (-2.10%), but showed a slight increase in HbA1c (0.22%). The prevalence of using glucose-lowering agents increased from 2.4% at baseline to 34.6% after the 9-month lifestyle intervention, and to 48.4% at 6-9 years postintervention. A 9-month intensive lifestyle intervention can produce beneficial effects on body weight, HbA1c and other cardiovascular risk factors among young women with previous GDM who subsequently developed new diabetes.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".