Weight Gain Measures in Women with Gestational Diabetes Mellitus
Bibliographic record
Abstract
BACKGROUND: Gestational diabetes mellitus (GDM) and excessive gestational weight gain have significant implications for the health of both mother and child. Our objective was to detail gestational weight gain in women in relationship to GDM. METHODS: Data were collected by retrospective reviews of medical records in women who delivered between January and December 2007 at the Laval University Medical Center (Quebec, Canada). The analysis included 294 women (55 GDM and 239 controls) for whom gestational weight gain was calculated by the difference between maternal weight measured at delivery, or at the last prenatal visit (≥37th week), and prepregnancy self-reported weight. Gestational weight gain and rate of weight gain were also calculated for each trimester and until GDM screening. Gestational weight gain was compared to the 2009 recommendations by the Institute of Medicine (IOM). Women with GDM were diagnosed and treated according to the Canadian Diabetes Association guidelines. RESULTS: Weight gain in the first trimester was significantly higher in GDM patients compared to controls (3.40 ± 0.42 vs. 1.87 ± 0.16 kg, p ≤ 0.01) and was above IOM recommendations, whereas weight gain in the third trimester was significantly lower in GDM patients compared to controls (4.11 ± 0.36 vs. 6.35 ± 0.18 kg, p ≤ 0.0001). Prepregnancy body mass index (BMI) and first trimester weight gain were both significant and independent predictors of GDM (odds ratio [OR] 1.11, 95% confidence interval [CI] 1.05-1.17, and OR 1.25, 95% CI 1.10-1.42, respectively). CONCLUSIONS: First trimester gestational weight gain may need more clinical attention, as it has been identified as an independent and significant risk factor for GDM independent of traditional risk factors, including preconception obesity.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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) | 0.001 | 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".