Yin Yong, Yang Guijun, Wang Na, Zeng Mei, Jiang Hejun, Yuan Shuhua, Wu Jinhong, Zhang Jing, Cui Juan, Zhou Guifang, Yang Xin, Zhang Yunqin, Sun Zhichao, Yuan Jiajun, Lin Jilei, Chen Jiande, Tang Mingyu, Chen Jing
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.
Department of Respiratory Medicine, Shanghai Children's Medical Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Front Pediatr. 2024 Aug 7;12:1420196. doi: 10.3389/fped.2024.1420196. eCollection 2024.
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.
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.
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.
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.
新冠病毒病是一场对人类健康造成重大损害的大流行病。本研究旨在调查新冠病毒2感染后长新冠的患病率,分析儿童长新冠发生的胸部CT潜在预测因素。
对2022年12月至2023年2月期间到上海儿童医学中心或临沂市妇幼保健院呼吸门诊就诊且在1周内接受胸部CT扫描的儿童队列进行随访。收集并分析临床特征、长新冠症状和胸部CT表现的数据。采用多因素逻辑回归模型和决策树模型来识别与长新冠相关的因素。
本研究共纳入416名儿童。在277名完成随访的儿童中,长新冠的患病率为23.1%。慢性咳嗽、疲劳、脑雾和运动后不适是最常报告的症状。在长新冠的决策树模型中,血管纹理增多、CT表现无正常以及年龄较小被确定为与儿童发生长新冠可能性较高相关的预测因素。然而,胸部CT异常与长新冠的发生之间未发现显著相关性。
儿童长新冠是一个复杂的挑战,患病率高达23.1%。新冠病毒2感染后儿童的胸部CT扫描显示血管纹理增多异常,提示发生长新冠的风险较高。