Physical Exertion Immediately Before Early Preterm Delivery
Bibliographic record
Abstract
BACKGROUND: Occupational exertion is associated with a higher risk of preterm delivery, although studies of leisure time activities generally document reduced risks. Less is known about the risk of preterm delivery immediately following episodes of moderate or heavy physical exertion. METHODS: We conducted a case-crossover study of 722 women interviewed during their hospital stay for early preterm delivery, defined by a gestational age before 34 weeks, and after 20 weeks. Interviews occurred between March 2013 and December 2015 in seven hospitals in Lima, Peru. RESULTS: The incidence rate ratio (RR) of early preterm delivery was 5.82-fold higher (95% confidence interval [CI] = 4.29, 7.36) in the hour following moderate or heavy physical exertion compared with other times and returned to baseline in the hours thereafter. The RR of early preterm delivery within an hour of physical exertion was lower for exertion at moderate intensity (RR = 2.43; 95% CI = 1.50, 3.96) than at heavy intensity (RR = 23.62; 95% CI = 15.54, 35.91; P-homogeneity < 0.001). The RR of early preterm delivery was lower in the hour following moderate physical exertion among women who habitually engaged in physical exertion >3 times per week in the year before pregnancy (RR = 1.56; 95% CI = 0.81, 3.00) compared with more sedentary women (RR = 6.91; 95% CI = 3.20, 14.92; P-homogeneity = 0.003). CONCLUSIONS: Our study showed a heightened risk of early preterm delivery in the hour following moderate or heavy physical exertion.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".