Evidence map›Paper›PMID 37565246›Full record

ArticleFrontiers in pediatrics2023

A multicentre study on the clinical characteristics of newborns infected with coronavirus disease 2019 during the omicron wave.

Yi-Heng Dai, Caihuan Li, Guilong Yuan, Wenhui Mo, Jun Chen, Runzhong Huang, Zhonghe Wan, Duohua Lin, Xiangming Zhong, Huanqiong Li and 2 more

Open access · goldAbstract read
In one paragraph

Article in Frontiers in pediatrics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.6field-weighted citation impact, top 30% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed, 2 citations in OpenAlex.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors at 4 institutions in 1 country.

Yi-Heng Dai *Department of Neonatal, Affiliated Foshan Maternity & Child Healthcare Hospital, Southern Medical University (Foshan Maternity &Child Healthcare Hospital), Foshan, China.
Caihuan Li *Department of Neonatal, Shunde Hospital of Southern Medical University, Foshan, China.
Guilong Yuan *Department of Neonatal, Nanhai Maternity & Child Healthcare Hospital of Foshan, Foshan, China.
Wenhui Mo *Department of Neonatal, Foshan Fosun Chancheng Hospital, Foshan, China.
Jun ChenDepartment of Neonatal, Affiliated Foshan Maternity & Child Healthcare Hospital, Southern Medical University (Foshan Maternity &Child Healthcare Hospital), Foshan, China.
Runzhong HuangDepartment of Neonatal, Shunde Women's and Children's Hospital of Guangdong Medical University, Foshan, China.
Zhonghe WanDepartment of Neonatal, The Sixth Affiliated Hospital of South China University of Technology, Foshan, China.
Duohua LinDepartment of Neonatal, Foshan Gaoming District People's Hospital, Foshan, China.
Xiangming ZhongDepartment of Neonatal, Sanshui Maternal and Child Health Hospital of Foshan City, Foshan, China.
Huanqiong LiDepartment of Neonatal, Sanshui District People's Hospital of Foshan, Foshan, China.
Ling LiuDepartment of Neonatal, The Third Affiliated Hospital of Guangdong Medical University, Foshan, China.
Jipeng ShiDepartment of Neonatal, Affiliated Foshan Maternity & Child Healthcare Hospital, Southern Medical University (Foshan Maternity &Child Healthcare Hospital), Foshan, China.
Foshan Maternity and Child Health Care Hospital · CNGuangdong Medical College · CNSouth China University of Technology · CNThe First People's Hospital of Shunde · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: To investigate the clinical characteristics and outcomes of newborns infected with coronavirus disease 2019 (COVID-19) during the Omicron wave. Methods: From December 1, 2022, to January 4, 2023, clinical data were collected from neonates with COVID-19 who were admitted to 10 hospitals in Foshan City, China. Their epidemiological histories, clinical manifestations and outcomes were analysed. The neonates were divided into symptomatic and asymptomatic groups. The Results: A total of 286 children were diagnosed, including 166 males, 120 females, 273 full-term infants and 13 premature infants. They were 5.5 (0-30) days old on average when they were admitted to the hospital. These children had contact with patients who tested positive for COVID-19 and were infected through horizontal transmission. This study included 33 asymptomatic and 253 symptomatic patients, among whom 143 were diagnosed with upper respiratory tract infections and 110 were diagnosed with pneumonia. There were no severe or critical patients. Fever (220 patients) was the most common clinical manifestation, with a duration of 1.1 (1-6) days. The next most common clinical manifestations were cough with nasal congestion or runny nose (4 patients), cough (34 patients), poor appetite (7 patients), shortness of breath (15 patients), and poor general status (1 patient). There were no significant abnormalities in routine blood tests among the neonates infected with COVID-19 except for mononucleosis. However, compared with the asymptomatic group, in the symptomatic group, the leukocyte and neutrophil granulocyte counts were significantly decreased, and the monocyte count was significantly increased. C-reactive protein (CRP) levels were significantly increased (≥10 mg/L) in 9 patients. Myocardial enzyme, liver function, kidney function and other tests showed no obvious abnormalities. Conclusions: In this study, neonates infected with the Omicron variant were asymptomatic or had mild disease. Symptomatic patients had lower leucocyte and neutrophil levels than asymptomatic patients.

Indexed as

clinical featurescoronavirus disease 2019neonatesomicron waveroutine blood tests

Identifiers

PMID37565246
PMCPMC10411454
OpenAlexW4384500318

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.