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Enregistrement W4293032596 · doi:10.1016/j.ajog.2022.08.038

Clinical risk factors of adverse outcomes among women with COVID-19 in the pregnancy and postpartum period: a sequential, prospective meta-analysis

2022· review· en· W4293032596 sur OpenAlex

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Notice bibliographique

RevueAmerican Journal of Obstetrics and Gynecology · 2022
Typereview
Langueen
DomaineMedicine
ThématiqueCOVID-19 Impact on Reproduction
Établissements canadiensUniversity of British Columbia
Organismes subventionnairesNational Health and Medical Research CouncilHorizon 2020 Framework ProgrammeFerring PharmaceuticalsWorld Health OrganizationNational Institute of Allergy and Infectious DiseasesMedical Research CouncilPublic Health AgencyCanadian Institutes of Health ResearchNational Institute for Health and Care ResearchPublic Health Agency of CanadaBundesamt für GesundheitBill and Melinda Gates Foundation
Mots-clésMedicinePregnancyProspective cohort studyObstetricsCoronavirus disease 2019 (COVID-19)Postpartum periodAdverse effectMeta-analysisDiseaseInternal medicineInfectious disease (medical specialty)

Résumé

récupéré en direct d'OpenAlex

OBJECTIVE: This sequential, prospective meta-analysis sought to identify risk factors among pregnant and postpartum women with COVID-19 for adverse outcomes related to disease severity, maternal morbidities, neonatal mortality and morbidity, and adverse birth outcomes. DATA SOURCES: We prospectively invited study investigators to join the sequential, prospective meta-analysis via professional research networks beginning in March 2020. STUDY ELIGIBILITY CRITERIA: Eligible studies included those recruiting at least 25 consecutive cases of COVID-19 in pregnancy within a defined catchment area. METHODS: We included individual patient data from 21 participating studies. Data quality was assessed, and harmonized variables for risk factors and outcomes were constructed. Duplicate cases were removed. Pooled estimates for the absolute and relative risk of adverse outcomes comparing those with and without each risk factor were generated using a 2-stage meta-analysis. RESULTS: We collected data from 33 countries and territories, including 21,977 cases of SARS-CoV-2 infection in pregnancy or postpartum. We found that women with comorbidities (preexisting diabetes mellitus, hypertension, cardiovascular disease) vs those without were at higher risk for COVID-19 severity and adverse pregnancy outcomes (fetal death, preterm birth, low birthweight). Participants with COVID-19 and HIV were 1.74 times (95% confidence interval, 1.12-2.71) more likely to be admitted to the intensive care unit. Pregnant women who were underweight before pregnancy were at higher risk of intensive care unit admission (relative risk, 5.53; 95% confidence interval, 2.27-13.44), ventilation (relative risk, 9.36; 95% confidence interval, 3.87-22.63), and pregnancy-related death (relative risk, 14.10; 95% confidence interval, 2.83-70.36). Prepregnancy obesity was also a risk factor for severe COVID-19 outcomes including intensive care unit admission (relative risk, 1.81; 95% confidence interval, 1.26-2.60), ventilation (relative risk, 2.05; 95% confidence interval, 1.20-3.51), any critical care (relative risk, 1.89; 95% confidence interval, 1.28-2.77), and pneumonia (relative risk, 1.66; 95% confidence interval, 1.18-2.33). Anemic pregnant women with COVID-19 also had increased risk of intensive care unit admission (relative risk, 1.63; 95% confidence interval, 1.25-2.11) and death (relative risk, 2.36; 95% confidence interval, 1.15-4.81). CONCLUSION: We found that pregnant women with comorbidities including diabetes mellitus, hypertension, and cardiovascular disease were at increased risk for severe COVID-19-related outcomes, maternal morbidities, and adverse birth outcomes. We also identified several less commonly known risk factors, including HIV infection, prepregnancy underweight, and anemia. Although pregnant women are already considered a high-risk population, special priority for prevention and treatment should be given to pregnant women with these additional risk factors.

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 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)0,003
score de la tête « metaresearch » (Gemma)0,033
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMétarecherche
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Synthèse · Signal consensuel: Synthèse
Score de désaccord entre enseignants0,340
Score d'incertitude au seuil0,976

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0030,033
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0060,001
Bibliométrie0,0020,003
Études des sciences et des technologies0,0000,001
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,001
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 Opus0,113
Tête enseignante GPT0,410
Écart entre enseignants0,297 · 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