Vertical transmission risk of SARS-CoV-2 infection in the third trimester: a systematic scoping review
Bibliographic record
Abstract
BACKGROUND: Studies on COVID-19 infection in pregnancy thus far have largely focused on characterizing maternal and neonatal clinical characteristics. However, another evolving focus is assessing and mitigating the risk of vertical transmission amongst COVID-19-positive mothers. The objective of this review was to summarize the current evidence on the vertical transmission potential of COVID-19 infection in the third trimester and its effects on the neonate. METHODS: OVID MEDLINE, EMBASE, and Cochrane Central Register of Controlled Trial (CENTRAL) were searched from January 2020 to May 2020, with continuous surveillance. RESULTS: 18 studies met the inclusion criteria, consisting of 157 mothers and 160 neonates. The mean age of the pregnant patients was 30.8 years and the mean gestational period was 37 weeks and 1 d. Currently, there is currently no conclusive evidence to suggest that vertical transmission of SARS-CoV-2 occurs. Amongst 81 (69%) neonates who were tested for SARS-CoV-2, 5 (6%) had a positive result. However, amongst these 5 neonates, the earliest test was performed at 16 h after birth, and only 1 neonate was positive when they were later re-tested. However, this neonate initially tested negative at birth, suggesting that the SARS-CoV-2 infection was likely hospital-acquired rather than vertically transmitted. 13 (8%) neonates had complications or symptoms. CONCLUSIONS: The findings of this rapid descriptive review based on early clinical evidence suggest that vertical transmission of SARS-CoV-2 from mother to neonate/newborn did not occur. Future studies are needed to determine the optimal management of neonates born to COVID-19-positive mothers.
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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 | 0.006 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.007 |
| Bibliometrics | 0.012 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 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".