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Enregistrement W4382542090 · doi:10.1093/humrep/dead093.323

O-269 Reproductive and Neonatal Outcomes in Women with Adenomyosis: A Population-based Study

2023· article· en· W4382542090 sur OpenAlexaff
M Bazarah, Ahmad Badeghiesh, Angelos G. Vilos, George A. Vilos, Michael H. Dahan

Notice bibliographique

RevueHuman Reproduction · 2023
Typearticle
Langueen
DomaineMedicine
ThématiqueEndometriosis Research and Treatment
Établissements canadiensMcGill UniversityWestern University
Organismes subventionnairesnon disponible
Mots-clésAdenomyosisMedicineObstetricsLogistic regressionPopulationInfertilityEndometriosisGynecologyRetrospective cohort studyPregnancyDiagnosis codeHealthcare Cost and Utilization ProjectCohort studyHealth careSurgeryEnvironmental healthInternal medicine

Résumé

récupéré en direct d'OpenAlex

Abstract Study question Does adenomyosis impact reproductive and neonatal outcomes? Summary answer Adenomyosis increases risk of infertility and pregnancy/delivery complications. Increased surveillance may aid in prevention and/or decreasing risk of maternal and neonatal morbidity and mortality. What is known already Patients with adenomyosis experience greater adverse obstetric and gynecological events which include but are not limited to, infertility and preterm delivery, as well as other adverse gynecological conditions such as endometriosis. Currently, existing literature provides a limited guide regarding obstetric and gynecological surveillance and management of patients diagnosed with adenomyosis. The current study aims at providing an in-depth analysis of a population database to expand and provide evidence-based insight on maternal, pregnancy and neonatal outcomes in women with adenomyosis. Study design, size, duration Retrospective population-based study. Data from the Health Care Cost and Utilization Project-Nationwide Inpatient Sample database (HCUP-NIS) were extracted from 2004 through 2014 using the ICD-9 codes to create a delivery cohort. Code 617.0 was used to identify women with adenomyosis, and reproductive outcomes were then compared to pregnancies without adenomyosis. A multivariate logistic regression model was utilized to adjust for statistically significant variables (P-value <0.05) Participants/materials, setting, methods Data was obtained from HCUP-NIS databse. Delivery records for the study and control groups were extracted using international classification of diseases Clinical Modification diagnostic codes(ICD-9-CM). The study group consisted of patients with adenomyosis and the control was patients without a diagnosis of adenomyosis. Logistic-regression-analysss was conducted to explore associations between adenomyosis and maternal&neonatal obstetrical outcomes through the estimation of odds ratio (OR) and 95%-confidence intervals(CI). The regression models were adjusted for the potential confounding factors. Main results and the role of chance Of the 9,096,788 deliveries in the study period, 2467 women had adenomyosis. Women with adenomyosis were more likely to be older (P < 0.0001), obese (P < 0.0001), have chronic hypertension (P < 0.0001), thyroid disease (P < 0.0001), pre-gestational diabetes mellitus (P < 0.0001), to have had previous caesarean section (P < 0.0001) and in-vitro fertilization (IVF) (P < 0.0001). Patients with adenomyosis had a statistically significant risk of developing pregnancy induced hypertension, preeclampsia, and placenta previa relative to the controls, after controlling for baseline risk factors; aOR 1.55 (95% CI 1.33-1.82), aOR 1.69 (95% CI 1.38-2.08), and aOR 5.86 (95% CI 4.62-7.43), respectively. Moreover, the rates of abruptio placenta, caesarean section, hysterectomy, post-partum hemorrhage, wound complications, blood transfusions and maternal infection were higher in the adenomyosis group relative to the controls, after controlling for confounding factors, aOR 2.17 (95% CI 1.60-2.95), aOR 21.63 (95% CI 17.99-26.02), aOR 6.39 (95% CI 4.22-9.68), aOR 1.97 (95% CI 1.60-2.42), aOR 2.37 (95% CI 1.52-3.69), aOR 2.25 (95% CI 1.71-2.95), and 1.82 (95% CI 1.39-2.39), respectively. At birth 1.5% of neonates born to adenomyosis patients had congenital anomalies, relative to 0.4% within the controls (aOR 2.94 (95% CI 2.02-4.28)). Limitations, reasons for caution Code were utilized to identify patients with adenomyosis. This may present as a limitation given the possibility that a number of adenomyosis patients were grouped within the controls. Inability to differentiate between severity and extent of adenomyosis, presents as a limitation within the HCUP-NIS database. Wider implications of the findings This is the first study of its kind to provide an in-depth analysis with substantial statistical power and over nine-million deliveries, in order to provide clinical guidance for patient surveillance and management. Trial registration number Not applicable

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 distillée sur la base complète

Imitation des enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,001
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,014
Score d'incertitude au seuil0,416

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,001
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0010,001
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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.

Tête enseignante Opus0,035
Tête enseignante GPT0,337
Écart entre enseignants0,302 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2023
Routes d'admission1
Résumé présentoui

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