Evidence map›Paper›PMID 39170602›Full record

ArticleFrontiers in pediatrics2024

Exploring the prevalence and chest CT predictors of Long COVID in children: a comprehensive study from Shanghai and Linyi.

Yong Yin, Guijun Yang, Na Wang, Mei Zeng, Hejun Jiang, Shuhua Yuan, Jinhong Wu, Jing Zhang, Juan Cui, Guifang Zhou and 8 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Frontiers in pediatrics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
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

2 citing papers in PubMed.

  1. Article
  2. Review
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

18 authors.

Yong Yin *Department of Respiratory Medicine, Linyi Maternal and Child Health Care Hospital, Linyi Branch of Shanghai Children's Medical Center, Shanghai Jiao Tong University School of Medicine, Linyi, Shandong, China.
Guijun Yang *Department of Respiratory Medicine, Shanghai Children's Medical Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Na Wang *Department of Respiratory Medicine, Linyi Maternal and Child Health Care Hospital, Linyi Branch of Shanghai Children's Medical Center, Shanghai Jiao Tong University School of Medicine, Linyi, Shandong, China.
Mei ZengDepartment of Respiratory Medicine, Shanghai Children's Medical Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Hejun JiangDepartment of Respiratory Medicine, Shanghai Children's Medical Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Shuhua YuanDepartment of Respiratory Medicine, Shanghai Children's Medical Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Jinhong WuDepartment of Respiratory Medicine, Shanghai Children's Medical Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Jing ZhangDepartment of Respiratory Medicine, Shanghai Children's Medical Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Juan CuiDepartment of Respiratory Medicine, Linyi Maternal and Child Health Care Hospital, Linyi Branch of Shanghai Children's Medical Center, Shanghai Jiao Tong University School of Medicine, Linyi, Shandong, China.
Guifang ZhouDepartment of Respiratory Medicine, Linyi Maternal and Child Health Care Hospital, Linyi Branch of Shanghai Children's Medical Center, Shanghai Jiao Tong University School of Medicine, Linyi, Shandong, China.
Xin YangDepartment of Respiratory Medicine, Linyi Maternal and Child Health Care Hospital, Linyi Branch of Shanghai Children's Medical Center, Shanghai Jiao Tong University School of Medicine, Linyi, Shandong, China.
Yunqin ZhangDepartment of Respiratory Medicine, Linyi Maternal and Child Health Care Hospital, Linyi Branch of Shanghai Children's Medical Center, Shanghai Jiao Tong University School of Medicine, Linyi, Shandong, China.
Zhichao SunDepartment of Respiratory Medicine, Linyi Maternal and Child Health Care Hospital, Linyi Branch of Shanghai Children's Medical Center, Shanghai Jiao Tong University School of Medicine, Linyi, Shandong, China.
Jiajun YuanPediatric AI Clinical Application and Research Center, Shanghai Children's Medical Center, Shanghai, China.
Jilei LinDepartment of Respiratory Medicine, Shanghai Children's Medical Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Jiande ChenDepartment of Respiratory Medicine, Shanghai Children's Medical Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Mingyu TangDepartment of Respiratory Medicine, Shanghai Children's Medical Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Jing ChenDepartment of Respiratory Medicine, Linyi Maternal and Child Health Care Hospital, Linyi Branch of Shanghai Children's Medical Center, Shanghai Jiao Tong University School of Medicine, Linyi, Shandong, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: COVID-19 constitutes a pandemic of significant detriment to human health. This study aimed to investigate the prevalence of Long COVID following SARS-CoV-2 infection, analyze the potential predictors of chest CT for the development of Long COVID in children. Methods: A cohort of children who visited the respiratory outpatient clinics at Shanghai Children's Medical Center or Linyi Maternal and Child Health Care Hospital from December 2022 to February 2023 and underwent chest CT scans within 1 week was followed up. Data on clinical characteristics, Long COVID symptoms, and chest CT manifestations were collected and analyzed. Multivariate logistic regression models and decision tree models were employed to identify factors associated with Long COVID. Results: A total of 416 children were included in the study. Among 277 children who completed the follow-up, the prevalence of Long COVID was 23.1%. Chronic cough, fatigue, brain fog, and post-exertional malaise were the most commonly reported symptoms. In the decision tree model for Long COVID, the presence of increased vascular markings, the absence of normal CT findings, and younger age were identified as predictors associated with a higher likelihood of developing Long COVID in children. However, no significant correlation was found between chest CT abnormality and the occurrence of Long COVID. Discussion: Long COVID in children presents a complex challenge with a significant prevalence rate of 23.1%. Chest CT scans of children post-SARS-CoV-2 infection, identified as abnormal with increased vascular markings, indicate a higher risk of developing Long COVID.

Indexed as

childrenCT abnormalitieslong COVIDpredictive factorsrespiratory tract infections

Identifiers

PMID39170602
PMCPMC11335557

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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.