Neišnešiotų naujagimių gimstamumo pokyčiai Covid-19 infekcijos laikotarpiu
Notice bibliographique
Résumé
Author: Roaa Izzeldin Elmahi Title of thesis: Changes in Preterm Birth Rates During the Period of the Covid-19 Pandemic. Aim: To evaluate the available data on the rate of preterm births in different countries during the COVID-19 global pandemic. Background: The COVID-19 pandemic posed many challenges to healthcare systems around the world and caused significant changes in the way healthcare was delivered. To control the spread of the novel virus, telemedicine, social distancing, and restrictions were implemented on non-emergency medical appointments and procedures. These adjustments changed the way care was delivered in various medical specialties, including obstetrics and neonatal care. Changes such as fewer antenatal checkups and stressors associated with the pandemic may have affected maternal and neonatal outcomes, particularly in preterm birth rates. Several studies on the changes in preterm birth rates during the pandemic have reported some reductions, while others found no significant impact. Understanding the extent and underlying factors of these changes is essential in improving maternal and neonatal care and for preparing for similar crises in the future. This systematic review aims to evaluate the current evidence on changes in preterm birth rates during the COVID-19 pandemic. During the assessment of the changed preterm labour rates, this review will also explore the links between economic factors, settings, and pandemic-related measures. Methodology: This systematic review was conducted from December 2023 to March 2024. This research was conducted following PRISMA guidelines. This review focuses on articles that analyzed the changes in maternal and neonatal outcomes during the COVID-19 pandemic. The search for different articles was done using different databases: Pubmed, Web of Science, and Cochrane. After searching through the database, articles that fulfilled the inclusion criteria and did not meet the exclusion criteria were included in the analysis. A total of 60 articles were included in this systematic review. Analyses for risk of bias in these articles followed the Newcastle-Ottawa Scale in this review. Participants: Participants were those who delivered before the COVID-19 pandemic vs during. Results: A total of 60 studies were included in this systematic review. Thirty-six out of sixty studies have found a significant change in the preterm labor rates in their study settings (60%), twenty- six found a decrease in preterm rates while thirteen found an increase. 16 countries out of 24 had experienced a change in preterm labor in this review. Regarding the economic status that saw a change in PTB, 76.7% of the high-income countries saw a decrease in PTB instead of an increase while middle-income countries saw an increase in PTB labor (80% out of all the studies in this review with a significant change in PTB). Only 8 studies saw a change in extremely PTB (<28 weeks) with 75% seeing a decrease in rates, 6 studies saw a change in very preterm (28-32 weeks), with 100% seeing a decrease in rates, and 8 studies saw a change in Moderate to late preterm (32-37 weeks) with 87.5% of them seeing a decrease. Regarding the study setting, the percentage of PTB decreasing was the same when compared to the facility, regional, and national levels (66.5% vs 62.5% vs 75%, respectfully) Conclusion: This systematic review provides a comprehensive analysis of the changes in preterm birth rates during the COVID-19 pandemic, including across various countries and income levels. The results indicate that many high-income countries experienced a reduction in preterm birth rates during the pandemic, evenly distributed extreme preterm (<28 weeks), very preterm (28-32 weeks), and moderate to late preterm (32-37 weeks) labor. However, middle-income countries that were included in this study saw an increase in preterm births. These findings suggest that the pandemic's impact on preterm birth rates varies depending on economic factors and how the healthcare systems respond to pandemics. These findings highlight the importance of further research to understand the factors contributing to these changes and guide healthcare strategies and policies for future global crises. However, further investigations are needed to closely analyze which factors had the strongest influence.
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Comment cette classification a été obtenuedéplier
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 | 0,002 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, 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 ».