Physical exertion at work during pregnancy did not increase risk of preterm delivery or fetal growth restriction
Bibliographic record
Abstract
Pompeii LA, Savitz DA, Evenson KR, et al . Physical exertion at work and the risk of preterm delivery and small-for-gestational-age birth. Obstet Gynecol 2005;106:1279–88. [OpenUrl][1][PubMed][2][Web of Science][3] Q In pregnant working women, does physical exertion at work (standing, lifting, night work, and long hours) increase the risk of preterm delivery or fetal growth restriction? Clinical impact ratings GP/FP/Primary care ★★★★★★☆ Obstetrics ★★★★★★☆ Paediatrics ★★★★★★☆ Occupational & environmental health ★★★★★★☆ ### ![Graphic][4]</img>Design: prospective cohort study. ### ![Graphic][5]</img>Setting: prenatal clinics at 3 hospitals in North Carolina, USA. ### ![Graphic][6]</img>Participants: 1908 English speaking women ⩾16 years of age who were 24–29 weeks pregnant with a singleton gestation and had worked ⩾28 days in the first 2 trimesters of pregnancy. ### ![Graphic][7]</img>Risk factors: physical exertion at work during the first (1–12 wk) or second (13–27 wk) trimester, including standing, heavy lifting (>11 kg), regular night work (10:00 PM–7:00 AM), and long hours (exposure determined by telephone interview at 24–31 wk gestation). ### ![Graphic][8]</img>Outcomes: preterm delivery (<37 wk gestation) and small for gestational age (SGA) infant (birth weight <10th percentile) (evaluated only in Caucasian and African-American … [1]: {openurl}?query=rft.jtitle%253DObstetrics%2B%2526%2BGynecology%26rft.stitle%253DObstet%2BGynecol%26rft.issn%253D0029-7844%26rft.aulast%253DPompeii%26rft.auinit1%253DL.%2BA.%26rft.volume%253D106%26rft.issue%253D6%26rft.spage%253D1279%26rft.epage%253D1288%26rft.atitle%253DPhysical%2Bexertion%2Bat%2Bwork%2Band%2Bthe%2Brisk%2Bof%2Bpreterm%2Bdelivery%2Band%2Bsmall-for-gestational-age%2Bbirth.%26rft_id%253Dinfo%253Apmid%252F16319253%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [2]: /lookup/external-ref?access_num=16319253&link_type=MED&atom=%2Febmed%2F11%2F5%2F156.atom [3]: /lookup/external-ref?access_num=000233695200011&link_type=ISI [4]: /embed/inline-graphic-1.gif [5]: /embed/inline-graphic-2.gif [6]: /embed/inline-graphic-3.gif [7]: /embed/inline-graphic-4.gif [8]: /embed/inline-graphic-5.gif
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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, unvalidatedLabeled directly by 2 models reading the full record.
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".