Low-intensity physical activity may protect pregnant women against spontaneous preterm labour: a prospective case-control study
Bibliographic record
Abstract
The innate immune system plays a significant role in onset of parturition. Maternal antenatal physical activity can influence immune function and timing of labour. We examined physical activity patterns and concentration of 19 cytokines at 16 and 27 weeks gestational age (GA), in peripheral plasma of 28 asymptomatic women who later had spontaneous preterm labour (SPTL, <37 weeks GA) and 52 women who later delivered at term (TL; ≥37 weeks GA). This nested case-control study used data from the Ontario Birth Study cohort. Exercise was assessed using the International Physical Activity Questionnaire, and cytokines were analyzed using Luminex assays. There was no significant difference in exercise patterns between SPTL and TL subjects. Plasma concentration of interleukin (IL)-10 was significantly higher in SPTL women at 16 and 27 weeks, while tumour necrosis factor alpha (TNF-α), IL-8, and monocyte chemoattractant protein (MCP)-1 concentrations were increased at 27 weeks GA (p < 0.05). Concentration of IL-10 was negatively correlated with the amount of reported walking (ρ = −0.264, p = 0.03). Women should be encouraged to partake in low-intensity exercise throughout pregnancy, as it may confer a protective effect against SPTL through IL-10–mediated pathways. Additionally, plasma cytokine analysis at 27 weeks GA may be useful for predicting SPTL in asymptomatic women. Novelty: In women that delivered preterm, plasma levels of anti-inflammatory cytokine IL-10 were significantly elevated at 16 and 27 weeks of gestation. Plasma levels of IL-10 were negatively correlated with the amount of reported walking. Concentration of IL-8, MCP-1 and TNF-α were increased in plasma of asymptomatic women that subsequently deliver preterm.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".