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

• Main Authors: Yong Yin (Author), Guijun Yang (Author), Na Wang (Author), Mei Zeng (Author), Hejun Jiang (Author), Shuhua Yuan (Author), Jinhong Wu (Author), Jing Zhang (Author), Juan Cui (Author), Guifang Zhou (Author), Xin Yang (Author), Yunqin Zhang (Author), Zhichao Sun (Author), Jiajun Yuan (Author), Jilei Lin (Author), Jiande Chen (Author), Mingyu Tang (Author), Jing Chen (Author)
• Format: Book
• Published: Frontiers Media S.A., 2024-08-01T00:00:00Z.
• Subjects: article
• Online Access: Connect to this object online.
• Notes: 2296-2360; 10.3389/fped.2024.1420196
• Keywords: long COVID; respiratory tract infections; children; CT abnormalities; predictive factors; Pediatrics; RJ1-570
• Source: Frontiers in Pediatrics, Vol 12 (2024)

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.