key: cord-0989431-c8i7dabb authors: Zhao, Yan; Yin, Lijuan; Patel, Jenil; Tang, Lei; Huang, Ying title: The inflammatory markers of multisystem inflammatory syndrome in children (MIS‐C) and adolescents associated with COVID‐19: A meta‐analysis date: 2021-04-01 journal: J Med Virol DOI: 10.1002/jmv.26951 sha: f993249834233e9c966662771901da7023d45032 doc_id: 989431 cord_uid: c8i7dabb To conduct a systematic review and meta‐analysis to characterize inflammatory markers in comparisons of multisystem inflammatory syndrome in children (MIS‐C) versus severe/non‐severe COVID‐19, severe MIS‐C versus non‐severe MIS‐C, and among age groups of MIS‐C. Nine databases were searched for studies on inflammatory markers of MIS‐C. After quality checks, data were pooled using a fixed or random effects model. Inflammatory markers included white blood cell count (WBC) or leukocytes, absolute lymphocyte count (ALC), absolute neutrophil count (ANC), platelet count (PLT), C‐reactive protein (CRP), procalcitonin (PCT), ferritin, D‐dimer, lactate dehydrogenase (LDH), fibrinogen, and erythrocyte sedimentation rate (ESR) for comparisons by severity and age. Twenty‐one studies with 1735 participants yielded 787 MIS‐C patients. Compared to non‐severe COVID‐19 patients, MIS‐C patients had lower ALC and higher ANC, CRP, and D‐dimer levels. Compared to severe COVID‐19 patients, MIS‐C patients had lower LDH and PLT counts and higher ESR levels. Severe MIS‐C patients had higher levels of WBC, ANC, CRP, D‐dimer, and ferritin than non‐severe MIS‐C patients. For MIS‐C, younger children (0–5 years) had lower CRP and ferritin levels than middle‐aged/older children/adolescents. Measurement of inflammatory markers might assist clinicians in accurate evaluation and diagnosis of MIS‐C and the associated disorders. The 2019 novel coronavirus disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has spread rapidly all over the world. During the earlier phase of the pandemic, children were thought to be "immune" or largely spared from the comorbidities and mortality associated with COVID-19. 1 However, recent studies have reported severe or even critical complications to have developed among children with COVID-19. 2, 3 In particular, an unusual syndrome of fever and hyperinflammatory process has emerged in pediatric populations with COVID-19. 4 The syndrome has been described as Pediatric Inflammatory Multisystem Syndrome temporally associated with SARS-CoV-2 (PIMS-TS) or pediatric multisystem inflammatory syndrome (PMIS) by the Royal College of Pediatrics and Child Health (RCPCH) 5 Syndrome in Children (MIS-C) by the World Health Organization (WHO) 6 and Centers for Disease Control and Prevention (CDC). 7 The preliminary case definitions were proposed, with MIS-C specifically characterized as a hyperinflammatory syndrome with multiorgan involvement and some clinical features that also overlap with Kawasaki disease (KD). 8 The term MIS-C is used throughout this meta-analysis. Several studies have reported laboratory features of MIS-C that are related to the known hyperinflammatory syndrome, however, these were limited by smaller sample sizes or descriptive studies to derive conclusions with strong external validity. [9] [10] [11] [12] Moreover, as per our knowledge, there are no meta-analyses in the literature that have compared the inflammatory markers of MIS-C among several known conditions to be associated with it, including COVID- 19 . In this study, we performed a meta-analysis to elucidate the inflammatory markers between MIS-C and known associated conditions including COVID-19, along with an internal comparison of MIS-C based on its severity and age. We conducted the research according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, and registered our review on the International Prospective Register of Systematic Reviews database (PROSPERO) on September 28, 2020; PROSPERO ID (CRD42020211402). We reported baseline characteristics and outcomes as available from the selected studies, which included author information, country, the age range of study participants, time period of the study, number of included patients, and diagnostic information were extracted. The different kinds of inflammatory markers were extracted as our target data. We used the Newcastle-Ottawa Scale (NOS) 13 to perform a quality assessment on all observational studies (case-control and cohort). Based on the scoring system of the NOS scale, we checked for selection (4 points), comparability (2 points), and outcome/exposure (3 points) for each study. A score of 1-3, 4-6, and 7-9 points indicated low, moderate, and high quality, respectively. Two investigators (Yan Zhao and Lijuan Yin) individually performed data extraction and quality assessment for each study. Discrepancies were resolved by a consensus that included a third investigator (Ying Huang). We calculated weighted mean deviations (WMD), standard mean differences (SMD), and corresponding 95% confidence intervals (95% CIs) from data within the included studies. Furthermore, we performed Q test ZHAO ET AL. | 4359 to assess overall heterogeneity, and I 2 test for quantitative assessment to assess the degree of heterogeneity. For studies with p < .1 or I 2 > 50%, indicative of non-negligible heterogeneity, a REM was generated to combine the numerical values. In contrast, for studies with no significant heterogeneity, a FEM was adopted. I 2 values of 25%, 50%, and 75%, respectively, represented low, moderate, and high heterogeneity, respectively. For studies with I 2 > 50%, sensitivity analysis and subgroup analysis were performed to probe the source of heterogeneity. For studies with I 2 > 75%, indicative of large heterogeneity, we did not use the combined result as they were rendered inconclusive. If the results of the two models (REM and FEM) were generally consistent, the combined result was considered reliable. In contrast, if the results were inconsistent, the combined results were considered unreliable. For analyses of over 10 studies, Begg's test and Egger's test were used to assess publication bias. STATA (StataCorp) 14 was used to perform all the statistical analyses. The initial literature search yielded 2972 articles from all the databases. A final total of 21 studies were included after screening based on the inclusion criteria ( Figure 1 ). All of the studies had a total of 1735 participants which included 787 MIS-C patients. Except for three studies, 22, 29, 31 the rest of the studies had fewer than 100 enrolled participants. Twelve studies [15] [16] [17] [18] [19] [20] [21] [22] 30, 31, 33, 34 compared MIS-C and COVID-19 along with subgroup analysis of MIS-C and severe/ non-severe COVID-19; seven studies [23] [24] [25] [26] [27] 32, 35 compared severe and non-severe MIS-C, while two studies 28,29 compared MIS-C across different age groups (0-4/0-5 years representing the young age of infants or preschoolers, 5-12/6-12 years representing the middle age of school-age and 13-20 years representing adolescents/young adults of puberty or postpuberty). All study features and characteristics are presented in Table 1 . In the quality assessment of study design for the selected studies, three studies 16, 18, 33 were deemed of moderate quality, with scores of 6, and the remaining 18 studies were deemed of high quality, with scores above 7 (eTable in the Supplement). (Table 2) 3. The results from sensitivity analysis were fairly similar and verified the stability of our analytical models. In addition, results from both the were consistent, which indicated reliability in interpreting the combined results. As the number of included studies in each comparison group was less than 10, we did not assess for publication bias. The recent COVID-19 pandemic poses a huge challenge to global public health. With the associated comorbidities being rapidly discovered, MIS-C has rapidly emerged as a threat to pediatric populations diagnosed with COVID-19. 1 New studies have confirmed the presence of hyperinflammatory syndrome in patients with MIS-C. [2] [3] [4] In this study, we conducted a meta-analysis to identify the inflammatory markers of MIS-C for evidence-based monitoring of disease progression. We found that inflammatory markers, including Hence the results should be interpreted with caution. Second, the selected studies were mainly non-randomized controlled studies. Third, the majority of the studies were limited by smaller sample sizes. Some studies enrolled relatively fewer subjects, and smaller sizes may reduce statistical power and influence the heterogeneity. Fourth, the number of included studies in each comparison was less than 10, which did not allow us to detect publication bias. Finally, we were unable to investigate the underlying mechanisms of inflammatory markers in MIS-C, as we did not have relevant information to do the same. 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The data that support the findings of this study are openly available in figshare at https://figshare.com/s/f67383194d4617d88916, reference numbers .