Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 671

The DOI matches its Crossref record.

Clinical characteristics and intrauterine vertical transmission potential of COVID-19 infection in nine pregnant women: a retrospective review of medical records

Open access
Eastin, Carly, Eastin, Travis·2020·The Journal of Emergency Medicine

Abstract

Multiple reports have been published recently on characteristics of patients with COVID-19 in the general population, but there is little information on pregnancy-related presenting symptoms and outcomes. The goal of this study was to report clinical data as well as incidence of vertical transmission in pregnant patients with COVID-19. This retrospective chart review was performed on pregnant women admitted to Zhongnan Hospital of Wuhan University in China with confirmed COVID-19 between January 20 through January 31, 2020. Clinical, laboratory, and radiologic records were reviewed by two investigators. Additionally, analyses from amniotic fluid, cord blood samples, and neonatal throat samples from the time of delivery were included. Vertical transmission was defined as positive testing for COVID-19 in these samples. Descriptive statistics were used. There were nine patients included in the analysis. All were in the third trimester on admission, the earliest presenting at 36 weeks, 2 days and all had a known source of exposure to COVID-19. None of the patients had baseline comorbidities, but one patient had gestational hypertension and another developed pre-eclampsia. The most common symptoms of COVID-19 were fever on admission (78%), postpartum fever (67%), cough (44%), myalgia (33%), and sore throat (22%). Most had low or normal leukocyte count (78%) and 5 (56%) had lymphopenia. C-reactive protein was greater than 10mg/L in 75% of patients. One was found to be co-infected with influenza, and all were diagnosed with COVID-19 pneumonia and required oxygen therapy and antibiotics. Many (67%) also received antivirals. Regarding delivery, all nine were live births delivered via cesarean section with 1-min Apgar scores of 8-9 and 5-min Apgar scores of 9-10. Four of the 9 were delivered prematurely at 36 weeks (44%) for a variety of reasons including premature rupture of membranes, pre-eclampsia, or pneumonia. None of the fluid samples at birth were positive for COVID-19. Additionally, all of the mothers and babies were discharged from the hospital. Limitations discussed include the retrospective nature of data abstraction and small sample size. Additionally all patients enrolled were in the third trimester. The authors concluded that pregnant patients with COVID-19 present with similar symptoms as nonpregnant patients. Also, based on this limited sample, the mothers had a low risk of complications and all of the infants tested negative for COVID-19 after birth, suggesting that vertical transmission is unlikely. Comment: There are still many uncertainties about the disease course of COVID-19 in pregnant patients. This review is reassuring, however this is a very small sample size so caution should be used in applying these results to our day to day patients, especially those at earlier gestational ages. More studies should be conducted on pregnant patients with COVID-19 in all trimesters to have a more accurate picture of how this virus affects pregnancy-related outcomes.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1016/j.jemermed.2020.04.003

Cites

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cited by

See all 671

Metadata

Authors
Eastin, C., & Eastin, T.
Venue
The Journal of Emergency Medicine
Publisher
Elsevier BV
Published
2020-04
Volume
58
Issue
4
Pages
710-711
ISSN
0736-4679 (ISSN-L)
OpenAlex
W3048467559
Cited by
671
References
0
FWCI
84.13
Type
journal article
Language
en
Open access
bronze

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Clinical characteristics and intrauterine vertical transmission potential of COVID-19 infection in nine pregnant women: a retrospective review of medical records. https://app.cochat.ai/papers/10.1016/j.jemermed.2020.04.003
The paper
Eastin, C., & Eastin, T. (2020). Clinical characteristics and intrauterine vertical transmission potential of COVID-19 infection in nine pregnant women: a retrospective review of medical records. The Journal of Emergency Medicine. https://doi.org/10.1016/j.jemermed.2020.04.003

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.