Dengue infection during pregnancy and the occurrence of pathological neonatal outcome: a systematic review and meta-analysis
Bibliographic record
Abstract
<ns3:p>Background Dengue infection during pregnancy increases the risk of maternal and neonatal complications; therefore, the objective of this research is to determine these outcomes and describe the clinical manifestations of the infection. Methods A systematic review of studies published in PubMed, MEDLINE, LILACS, Web of Science, Scopus and thesis repositories published between 2013 and October 2023 was performed. DeCS and MeSH dengue and maternal-neonatal outcome were used. Thirteen studies were selected and the New Castle-Ottawa scale was used to assess their quality. Mantel-Haenszel hazard ratios were calculated to report the overall effect size using random-effects models. All analyses were performed in Rev Man 5.4.1 Results The 13 studies involved a population of 18,724 pregnant women, with cohorts ranging from 25 to 17,673 pregnant women. The most frequent outcomes in the pregnant women were cesarean section and postpartum hemorrhage, and in the newborns, preterm delivery and low birth weight. According to the New Castle-Ottawa scale, six studies were considered low risk and seven studies moderate risk. Dengue is a risk factor for postpartum hemorrhage (OR: 2.24), premature rupture of membranes (OR: 1.04) and cesarean section (OR: 1.13). It could not be concluded that dengue is a risk factor for the neonatal outcomes studied. The clinical picture of pregnant women with dengue was predominantly fever, abdominal pain, vomiting and nausea, anemia, dyspnea and myalgia. Conclusions Pregnancy-related changes in the immune, cardiovascular and coagulation systems, among others, increase the probability of adverse maternal and neonatal outcomes in case of DENV infection, such as postpartum hemorrhage, premature rupture of membranes, cesarean section, low birth weight and preterm delivery. Pregnant women should be considered a population at risk and should be included in dengue control, diagnosis and treatment policies.</ns3:p>
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.007 | 0.003 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".