Maternal and Neonatal Outcomes after Vaccination with SARS-CoV-2: ASystematic Review and Meta-analysis of Cohort Studies
Bibliographic record
Abstract
: SARS-CoV-2 infection among pregnant women causes maternal and neonatal complications. Professional societies endorse the vaccination among pregnant women. This review of the cohort studies aims to assess the short-term maternal and neonatal outcomes among vaccinated vs. non-vaccinated pregnant women with SARS-CoV-2 vaccination. We searched Cochrane Central Registry of Controlled Trials, Scopus, Google Scholar, and PubMed databases. The observational cohort studies published from July 2021 to December 2022 were included. The eligibility criteria were assessed. The studies documenting maternal and neonatal outcomes and the relative risk, and 95% confidence interval were considered. Joanna Briggs Institute data extraction form was used, and the quality assessment of the included study was conducted using the Newcastle-Ottawa quality assessment scale. The quality of the grading was summarised with GradePro software. Data from the five cohort studies are considered. 56% of the un-vaccinated pregnant women experience composite adverse maternal outcomes (RR: 3.97; 95% CI:0.73,21.49; p-value: ˂0.11). There was a reduced risk of occurrence of the meconium-stained amniotic fluid who are vaccinated (RR: 0.89; 95% CI:0.71, 1.12; p value=0.33). The unvaccinated group is 3.16 times more likely to take infertility treatment (RR: 3.54; 95% CI:2.04, 6.12; p-value: ˂0.00001). There was no significant difference concerning neonatal outcomes between both groups. The pregnant women who were not vaccinated against SARS-CoV had an increased risk for a composite adverse maternal outcome and meconium-stained amniotic fluid. The vaccine has effectively prevented the disease in the first six months. Additional studies are needed to understand the safety of the SARS-CoV vaccine.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.009 | 0.001 |
| Bibliometrics | 0.001 | 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 | 0.000 |
| 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".