Impact of SARS-CoV-2 on the clinical outcomes and placental pathology of pregnant women and their infants: A systematic review
Bibliographic record
Abstract
Pregnant women are susceptible to viral infections due to physiological changes such as cell-mediated immunity. No severe adverse pregnancy or neonatal outcomes have been consistently reported in 2019 novel coronavirus disease (COVID-19) positive pregnancy cases. There are controversies around the role of COVID-19 in pregnancy. A systematic review was conducted to examine clinical maternal and neonatal clinical outcomes. Studies were included if they reported SARS-CoV-2 infection among pregnant women and/or COVID-19 positive neonates as validated by positive antibody testing or viral testing using polymerase chain reaction. Case series, case reports, case-control studies, and comparative studies were included. Eight hundred and thirty-seven records were identified, resulting in 525 records for level I screening. Forty-one were included after full-text review. Results suggest elevated rates of intensive care unit (ICU) admission, gestational diabetes, preeclampsia, C-sections, pre-term birth, and C-reactive protein (CRP) in comparison to pregnant women without SARS-CoV-2. Careful monitoring of pregnancies with SARS-CoV-2 is recommended.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.007 | 0.009 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 source (direct Gemma or distilled Codex), 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".