Impact of SARS-CoV-2 on the clinical outcomes of pregnant women and their infants: Systematic Review and Meta-analysis Protocol
Bibliographic record
Abstract
An investigation into placental pathology in pregnant women with SARS-CoV-2 has not yet been examined extensively, yet this knowledge would be beneficial in understanding the potential for vertical transmission of SARS-CoV-2 during pregnancy. Currently, results are conflicting, with some evidence suggesting rare placental infection. However, compared to controls, one study determined that third trimester placentas were significantly more likely to show one feature of maternal vascular malperfusion (MVM). In light of the inconclusive evidence, the burden of illness of SARS-CoV-2 in pregnant women and their neonates or infants, remains a critical concern. The aim of this systematic review is to inform future obstetric guidelines, which should help provide SARS-CoV-2 clinical recommendations to the medical caregivers of pregnant women and their infants. This protocol outlines our objectives, which are to: examine the presence and frequency of any placental finding in the placentas of SARS-CoV-2 pregnant women, relative to controls recruited during the pandemic period; investigate the mean count and evolution of lymphocytes (including their T, B and NK differential counts), monocytes, eosinophils, basophils, neutrophils, and red blood cells in pregnant women with SARS-CoV-2 at various stages of pregnancy; and compare the fetal mortality outcome at early versus late trimester of pregnancy in pregnant women who test positive for SARS-CoV-2 versus controls. Our study will identify case series and case-control studies of asymptomatic and symptomatic pregnant women, and their neonates and/or infants, who test positive for SARS-CoV-2 during any stage of their pregnancy, as validated by laboratory confirmed positive antibody testing or using real-time reverse-transcriptase-polymerase chain reaction (rRT-PCR). Only articles written in English, French or Chinese will be included. Literature reviews, systematic reviews, editorials, letters to the editor, conference abstracts, and commentaries will be excluded. Early scoping searches were run in April 2020 with MEDLINE and Embase using the OVID interface, and the Ovid interface and Global Health using the CAB Direct interface Disaster Lit: Database for Disaster Medicine and Public Health, MedRxiv and OSF Preprints. An update with adjusted terminology and refined database selection was run in July using MEDLINE, Embase and the WHO and CDC specialized COVID 19 database (July 2020). Search alerts for MEDLINE, Embase and Google Scholar will be in place throughout the review to identify newly emerging research, with a final search occurring in January 2021. Primary extracted outcomes include: mean counts of T-cells, B-cells, monocytes, eosinophils, neutrophils, basophils, and red blood cells, placental pathology findings, and mortality frequency such as number of abortions (<20 weeks) and stillbirths (20+ weeks). Observational studies will be assessed using the Ottawa-Newcastle scale. Forest plots will be utilized to visualize the data. Statistical heterogeneity of the included studies will be assessed using the I-squared test with 95% confidence intervals, and publication bias will be determined using a funnel plot and Egger’s test when possible (>10 included studies). If a meta-analysis will be undertaken, the strength of the body of evidence will be assessed using GRADE. Understanding the impact of SARS-CoV-2 on the health of neonates and infants can aid in identifying optimal management strategies to prevent adverse clinical outcomes.
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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 | 0.027 | 0.054 |
| Meta-epidemiology (narrow) | 0.004 | 0.003 |
| Meta-epidemiology (broad) | 0.016 | 0.021 |
| Bibliometrics | 0.009 | 0.008 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.036 | 0.003 |
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".