Aquatic Activities During Pregnancy Prevent Excessive Maternal Weight Gain and Preserve Birth Weight: A Randomized Clinical Trial
Bibliographic record
Abstract
PURPOSE: The aim of the present study was to examine the influence of a supervised and regular program of aquatic activities throughout gestation on maternal weight gain and birth weight. DESIGN: A randomized clinical trial. SETTING: Instituto de Obstetricia, Ginecología y Fertilidad Ghisoni (Buenos Aires, Argentina). PARTICIPANTS: One hundred eleven pregnant women were analyzed (31.6 ± 3.8 years). All women had uncomplicated and singleton pregnancies; 49 were allocated to the exercise group (EG) and 62 to the control group (CG). INTERVENTION: The intervention program consisted of 3 weekly sessions of aerobic and resistance aquatic activities from weeks 10 to 12 until weeks 38 to 39 of gestation. MEASURES: Maternal weight gain, birth weight, and other maternal and fetal outcomes were obtained by hospital records. ANALYSIS: test were used; P values ≤.05 indicated statistical significance. Cohen's d was used to determinate the effect size. RESULTS: There was a higher percentage of women with excessive maternal weight gain in the CG (45.2%; n = 28) than in the EG (24.5%; n = 12; odds ratio = 0.39; 95% confidence interval: 0.17-0.89; P = .02). Birth weight and other pregnancy outcomes showed no differences between groups. CONCLUSION: Three weekly sessions of water activities throughout pregnancy prevents excessive maternal weight gain and preserves birth weight. TRIAL REGISTRATION: The clinicaltrial.gov identifier: NCT 02602106.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".