Department of Pediatrics, University of Colorado School of Medicine and Children's Hospital Colorado, 13123 E 16th Ave Box 090, Aurora, CO, 80045, USA.
Department of Biostatistics, Epidemiology and Informatics, The Perelman School of Medicine, University of Pennsylvania, 423 Guardian Dr, Blockley Hall 602, Philadelphia, PA, 19104, USA.
Sci Rep. 2023 Nov 28;13(1):21005. doi: 10.1038/s41598-023-47655-y.
Multi-system inflammatory syndrome in children (MIS-C) is a severe post-acute sequela of SARS-CoV-2 infection in children, and there is a critical need to unfold its highly heterogeneous disease patterns. Our objective was to characterize the illness spectrum of MIS-C for improved recognition and management. We conducted a retrospective cohort study using data from March 1, 2020-September 30, 2022, in 8 pediatric medical centers from PEDSnet. We included 1139 children hospitalized with MIS-C and used their demographics, symptoms, conditions, laboratory values, and medications for analyses. We applied heterogeneity-adaptive latent class analyses and identified three latent classes. We further characterized the sociodemographic and clinical characteristics of the latent classes and evaluated their temporal patterns. Class 1 (47.9%) represented children with the most severe presentation, with more admission to the ICU, higher inflammatory markers, hypotension/shock/dehydration, cardiac involvement, acute kidney injury and respiratory involvement. Class 2 (23.3%) represented a moderate presentation, with 4-6 organ systems involved, and some overlapping features with acute COVID-19. Class 3 (28.8%) represented a mild presentation. Our results indicated that MIS-C has a spectrum of clinical severity ranging from mild to severe and the proportion of severe or critical MIS-C decreased over time.
儿童多系统炎症综合征 (MIS-C) 是儿童 SARS-CoV-2 感染后的严重急性后遗症，因此迫切需要阐明其高度异质的疾病模式。我们的目标是描述 MIS-C 的疾病谱，以提高识别和管理能力。我们使用 PEDSnet 中的 8 个儿科医疗中心在 2020 年 3 月 1 日至 2022 年 9 月 30 日期间的数据进行了一项回顾性队列研究。我们纳入了 1139 名因 MIS-C 住院的儿童，并对他们的人口统计学、症状、疾病、实验室值和药物进行了分析。我们应用了异质性自适应潜在类别分析，并确定了三个潜在类别。我们进一步描述了潜在类别的社会人口统计学和临床特征，并评估了它们的时间模式。第 1 类（47.9%）代表病情最严重的患儿，他们更需要入住 ICU，炎症标志物更高，伴有低血压/休克/脱水、心脏受累、急性肾损伤和呼吸受累。第 2 类（23.3%）代表中度表现，涉及 4-6 个器官系统，与急性 COVID-19 有一些重叠特征。第 3 类（28.8%）代表轻度表现。我们的结果表明，MIS-C 的临床严重程度呈谱性分布，从轻到重，严重或危急 MIS-C 的比例随时间逐渐降低。
