Modelling prior reproductive history to improve prediction of risk for very preterm birth
Pourquoi ce travail est dans la base
Une base qui oublie comment elle a trouvé un travail ne peut pas être vérifiée. Voici les voies qui ont admis celui-ci.
Notice bibliographique
Résumé
In published studies of preterm birth, analyses have usually been centred on individual reproductive events and do not account for the joint distributions of these events. In particular, spontaneous and induced abortions have often been studied separately and have been variously reported as having no increased risk, increased risk or different risks for subsequent preterm birth. In order to address this inconsistency, we categorised women into mutually exclusive groups according to their reproductive history, and explored the range of risks associated with different reproductive histories and assessed similarities of risks between different pregnancy histories. The data were from a population-based case-control study, conducted in Victoria, Australia. The study recruited women giving birth between April 2002 and April 2004 from 73 maternity hospitals. Detailed reproductive histories were collected by interview a few weeks after the birth. The cases were 603 women who had had a singleton birth between 20 and less than 32 weeks gestation (very preterm births including terminations of pregnancy) and the controls were 796 randomly selected women from the population who had had a singleton birth of at least 37 completed weeks gestation. All birth outcomes were included. Unconditional logistic regression was used to assess the association of very preterm birth with type and number of prior abortions, prior preterm births and sociodemographic factors. Using the complex combinations of prior pregnancy experiences of women (including nulligravidity), we showed that a history of prior childbirth (at term) with no preterm births gave the lowest risk of very preterm birth. With this group as the reference category, odds ratios of more than two were associated with all other prior reproductive histories. There was no evidence of difference in risk between types of abortion (i.e. spontaneous or induced) although the risk increased if a prior preterm birth had also occurred. There was an increasing risk of very preterm birth associated with increasing numbers of abortions. This method of data analysis reveals consistent and similar risks for very preterm birth following spontaneous or induced abortions. The findings point to the need to explore commonalities rather than differences in regard to the impact of abortion on subsequent births.
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.
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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 découle