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

Yong Yin; Yong Yin; Yong Yin; Yong Yin; Yong Yin; Yong Yin; Guijun Yang; Na Wang; Mei Zeng; Hejun Jiang; Shuhua Yuan; Jinhong Wu; Jing Zhang; Juan Cui; Guifang Zhou; Xin Yang; Yunqin Zhang; Zhichao Sun; Jiajun Yuan; Jiajun Yuan; Jiajun Yuan; Jilei Lin; Jilei Lin; Jilei Lin; Jilei Lin; Jiande Chen; Mingyu Tang; Jing Chen

doi:10.3389/fped.2024.1420196

Frontiers in Pediatrics (Aug 2024)

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

Yong Yin,
Yong Yin,
Yong Yin,
Yong Yin,
Yong Yin,
Yong Yin,
Guijun Yang,
Na Wang,
Mei Zeng,
Hejun Jiang,
Shuhua Yuan,
Jinhong Wu,
Jing Zhang,
Juan Cui,
Guifang Zhou,
Xin Yang,
Yunqin Zhang,
Zhichao Sun,
Jiajun Yuan,
Jiajun Yuan,
Jiajun Yuan,
Jilei Lin,
Jilei Lin,
Jilei Lin,
Jilei Lin,
Jiande Chen,
Mingyu Tang,
Jing Chen

Affiliations

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
Yong Yin: Department of Respiratory Medicine, Shanghai Children’s Medical Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
Yong Yin: Shanghai Children’s Medical Center Pediatric Medical Complex (Pudong), Shanghai, China
Yong Yin: Pediatric AI Clinical Application and Research Center, Shanghai Children’s Medical Center, Shanghai, China
Yong Yin: Shanghai Engineering Research Center of Intelligence Pediatrics (SERCIP), Shanghai, China
Yong Yin: Child Health Advocacy Institute, China Hospital Development Institute, Shanghai Jiao Tong University, Shanghai, 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 Zeng: Department of Respiratory Medicine, Shanghai Children’s Medical Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
Hejun Jiang: Department of Respiratory Medicine, Shanghai Children’s Medical Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
Shuhua Yuan: Department of Respiratory Medicine, Shanghai Children’s Medical Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
Jinhong Wu: Department of Respiratory Medicine, Shanghai Children’s Medical Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
Jing Zhang: Department of Respiratory Medicine, Shanghai Children’s Medical Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
Juan Cui: 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
Guifang Zhou: 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
Xin Yang: 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
Yunqin Zhang: 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
Zhichao Sun: 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
Jiajun Yuan: Pediatric AI Clinical Application and Research Center, Shanghai Children’s Medical Center, Shanghai, China
Jiajun Yuan: Shanghai Engineering Research Center of Intelligence Pediatrics (SERCIP), Shanghai, China
Jiajun Yuan: Medical Department of Shanghai Children’s Medical Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
Jilei Lin: Department of Respiratory Medicine, Shanghai Children’s Medical Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
Jilei Lin: Pediatric AI Clinical Application and Research Center, Shanghai Children’s Medical Center, Shanghai, China
Jilei Lin: Shanghai Engineering Research Center of Intelligence Pediatrics (SERCIP), Shanghai, China
Jilei Lin: Child Health Advocacy Institute, China Hospital Development Institute, Shanghai Jiao Tong University, Shanghai, China
Jiande Chen: Department of Respiratory Medicine, Shanghai Children’s Medical Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
Mingyu Tang: Department of Respiratory Medicine, Shanghai Children’s Medical Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
Jing Chen: 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

DOI: https://doi.org/10.3389/fped.2024.1420196
Journal volume & issue: Vol. 12

Abstract

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IntroductionCOVID-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.MethodsA 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.ResultsA 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.DiscussionLong 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.

Published in Frontiers in Pediatrics

ISSN: 2296-2360 (Online)
Publisher: Frontiers Media S.A.
Country of publisher: Switzerland
LCC subjects: Medicine: Pediatrics
Website: http://journal.frontiersin.org/journal/pediatrics

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