The Potential Impact of Physical Activity During Pregnancy on Maternal and Neonatal Outcomes
Bibliographic record
Abstract
INTRODUCTION: Pregnancy is a critical period of body weight regulation. Maternal obesity and excessive gestational weight gain have become increasingly common and contribute to poor obstetrical outcomes for mother and baby. Regular participation in physical activity may improve risk profiles in pregnant women. PURPOSE AND METHODS: Our objectives were to provide an overview of maternal-fetal exercise physiology, summarize current evidence on the effects of physical activity during pregnancy on maternal-fetal outcomes, and review the most recent clinical practice guidelines. In addition, we summarize the findings in the context of the current obesity epidemic and discuss implications for clinical practice. A literature review was completed in which we queried OVID (Medline), EMBASE, and PSYCHINFO databases with title words "exercise or physical activity" and "pregnancy or gestation" from 1950 to March 1, 2010. A total of 212 articles were selected for review. RECOMMENDATIONS: Care providers should recommend physical activity to most pregnant women (i.e., those without contraindications) and view participation as a safe and beneficial component of a healthy pregnancy. TARGET AUDIENCE: Obstetricians & Gynecologists and Family Physicians. LEARNING OBJECTIVES: After participating in this CME activity, physicians should be better able to classify the potential impact of physical activity on maternal glycemic control and fetal growth outcomes. Assess maternal lifestyle and provide recommendations on appropriate gestational weight gain, evaluate pregnant women for contraindications to physical activity participation, make individualized recommendations for exercise participation, and educate patients on the merits of physical activity for health benefit.
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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 | 0.003 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".