Neišnešiotų naujagimių gimstamumo pokyčiai Covid-19 infekcijos laikotarpiu
Bibliographic record
Abstract
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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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".