Notice bibliographique
Résumé
Although risk factors and determinants of spontaneous preterm birth have been identified, effective primary and secondary prevention strategies to reduce the global incidence and neonatal consequences of prematurity remain elusive. Physically demanding work (prolonged standing, heavy lifting, physical exertion, occupational fatigue, demanding posture) during pregnancy has been associated with an increased risk of preterm birth (van Beukering et al. Int Arch Occup Environ Health 2014;87:809–34). In the past, exercise was discouraged during pregnancy because of concerns that increased physical activity might increase release of catecholamines and stimulate myometrial activity, leading to preterm labour. More recently, it has been suggested that exercise may actually reduce the risk of preterm birth by reducing oxidative stress or improving placental vascularisation. The potential beneficial effects of leisure-time physical activity have been evaluated in a growing number of randomised controlled trials and observational studies with conflicting results. Consequently, the safety and effectiveness of physical exercise in preventing preterm birth remains controversial. D. Aune et al. use well-established scientific methods for systematic review and meta-analysis of randomised controlled trails (RCT), prospective cohort studies and case-control studies to evaluate the association and dose–response relationship between physical activity and preterm birth (D Aune et al. BJOG 2017;124:1816–1826). Although other systematic reviews and meta-analyses assessing the effect of physical activity and aerobic exercise exist (Kramer et al. Cochrane Library 2006:CD000180; Di Mascio et al. Am J Obstet Gynecol 2016;215:561–71), this study presents a comprehensive analysis of the relation between various types of physical activity before and during pregnancy and preterm birth risk. Higher levels of leisure-time physical activity during pregnancy reduced the risk of preterm birth per three-hour increment, whereas physical activity before pregnancy and moderate, vigorous, occupational and total physical activity, walking, and bicycling during pregnancy did not. Recognising the methodological limitations of combining RCTs and observational studies in a meta-analysis and issues of heterogeneity, bias, statistical power and quality raised by the authors, the protective effect of increased leisure-time physical activity during pregnancy for women exposed in cohort studies compared with the lack of a beneficial effect among women prescribed physical exercise is striking. This observation has been supported in meta-analyses of RCTs by Kramer and Di Mascio and in a recent systematic review of RCTs and cohort studies (da Silva et al. Sports Med 2017;47:295–317). These findings suggest that women who choose to engage in physical activity during pregnancy may be different from those who are placed on an exercise regime. Self-motivated physical activity is associated with other healthy behaviours including diet and lower prevalence of risk factors such as smoking and obesity that cannot be adequately controlled for. As with any prescription, compliance with exercise programs is often inconsistent and potential beneficial effects may not be realised. To determine whether physical activity can be used as an effective intervention to prevent preterm birth, further in-depth study of the psychological and behavioural characteristics of women who choose to be physically active during pregnancy as well as large RCTs where physical activity is accurately measured are warranted. None declared. Completed disclosure of interests form available to view online as supporting information. Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,011 | 0,042 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,011 | 0,006 |
| Bibliométrie | 0,003 | 0,003 |
| Études des sciences et des technologies | 0,001 | 0,002 |
| Communication savante | 0,003 | 0,003 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,006 | 0,006 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,014 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».