Skip to main content
NCBI home page
UKPMC Funders Author Manuscripts logoLink to UKPMC Funders Author Manuscripts
. Author manuscript; available in PMC: 2025 Jan 23.
Published in final edited form as: Microbiol Immunol. 2025 Jan 15;69(3):174–181. doi: 10.1111/1348-0421.13198

Diagnostic Markers of Severe COVID-19 and Community-Acquired Pneumonia in Children From Southern India

Tina Damodar 1,✉, Lonika Lodha 1, Sourabh Suran 1, Namratha Prabhu 1, Maria Jose 1, Uddhav Kinhal 2, GV Basavaraja 3, Vykuntaraju K Gowda 2, Reeta S Mani 1,✉
PMCID: PMC7617320  EMSID: EMS202694  PMID: 39812381

Abstract

COVID-19 severely impacts children in India, with many developing severe pneumonia or multisystem inflammatory syndrome (MIS-C). Concurrently, non-COVID-19 respiratory viruses causing community-acquired pneumonia (CAP) have resurged. These conditions present similarly, challenging accurate diagnosis. This study aims to compare inflammatory markers and clinical parameters in children with severe COVID-19 pneumonia, non-COVID-19 CAP, and COVID-associated MIS-C. We assessed 12 mediators in serum from 14 children with severe COVID-19 pneumonia, 16 with severe non-COVID-19 CAP, and 9 with MIS-C. Clinical characteristics and routine laboratory findings at admission were recorded. Children with MIS-C had significantly higher levels of IL-1RA, IL-8, and TNF compared with those with severe COVID-19 pneumonia; and higher levels of CCL2, HGF, M-CSF, and IL-8 compared with severe non-COVID-19 CAP. GROα levels tended to be higher in severe COVID-19 pneumonia. Clinical presentations were similar, but MIS-C patients had distinct laboratory findings, including lower platelet counts and albumin levels, and higher creatinine and liver enzyme levels. MIS-C exhibited a unique inflammatory profile. IL-8 emerged as a potential biomarker for MIS-C, while increased GROα levels in severe COVID-19 pneumonia merit further exploration. Combining inflammatory markers with routine laboratory parameters may improve the diagnosis and differentiation of these conditions, enhancing patient management.

Keywords: COVID-19, cytokines, immune markers, MIS-C associated with COVID-19, pneumonia

Abbreviations

AES

acute encephalitis syndrome

CAP

community-acquired pneumonia

HSV

herpes simplex virus

JEV

Japanese encephalitis virus

MIS-C

multisystem inflammatory syndrome in children

RSV

respiratory syncytial virus

SARS

severe acute respiratory syndrome

VZV

varicella zoster virus

WHO IMCI

World Health Organization-Integrated Management of Childhood Illness

1. Introduction

The COVID-19 pandemic has had a significant impact on India, with more than 44.4 million confirmed cases and 0.53 million fatalities recorded to date [1]. While studies from high-income nations suggest that children generally experience milder COVID-19 illness compared with adults, concerning findings have surfaced in India, indicating that approximately 65% of children with COVID-19 develop severe illness, including severe acute pneumonia and COVID-associated multisystem inflammatory syndrome (MIS-C), with mortality rates ranging from 13% in severe COVID-19 pneumonia to 19% in MIS-C [2].

It is also observed that, as the COVID-19 pandemic recedes, there has been a resurgence of non-COVID-19 respiratory viruses causing community-acquired pneumonia (CAP) in children, often with an altered seasonal pattern. This resurgence is likely due to the relaxation of COVID-19 prevention measures and the increased vulnerability of the population to other respiratory pathogens [3]. The clinical presentation of severe COVID-19 pneumonia, MIS-C, and severe non-COVID-19 CAP in children can be nonspecific and overlapping, with a wide array of constitutional, gastrointestinal, and respiratory manifestations [2, 4–7]. This similarity in presentation makes accurate clinical diagnosis challenging.

Prompt identification of the underlying condition is crucial for initiating timely and targeted treatment, leading to positive outcomes. However, current diagnostic methods have limitations. Diagnosis based on the presence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2 anti-nucleocapsid antibodies alone is unreliable, as positive results may imply prior exposure or asymptomatic infection rather than active disease. Similarly, pathogen-based polymerase chain reaction (PCR) tests are limited by high cost, limited availability, and delays in presentation and sampling, which are typical in developing countries, leading to unreliable PCR test results [8].

Global literature highlights the role of cytokines and chemokines, such as interleukin-6 (IL-6), IL-8, tumor necrosis factor (TNF), and interferon-gamma (IFN-γ), in severe COVID-19 and severe non-COVID-19 CAP, suggesting their potential use as biomarkers of these conditions [9]. Severe COVID-19 is characterized by a dysregulated immune response unrelated to viral burden, involving inappropriate inflammasome activation, pyroptosis, and cytokine storm, resulting in a self-perpetuating cycle of tissue damage. In MIS-C, a type II interferon response is predominant, with an immunopathophysiology similar to that of toxic shock syndrome, although not yet clearly delineated [10]. Cytokine storm is also known to occur in other severe viral pneumonias, such as those caused by respiratory syncytial virus (RSV) or influenza virus [11]. However, there is a paucity of data on inflammatory marker profiles in these conditions from the Indian pediatric population.

Given the distinct pathophysiologies but similar clinical presentations of severe COVID-19 pneumonia, severe non-COVID-19 pneumonia, and MIS-C associated with COVID-19, there is a pressing need for reliable biomarkers to aid in their diagnosis and management. The primary objective of this study is to investigate and compare the profiles of serum inflammatory markers among children diagnosed with these conditions. This will provide further insights into their pathophysiological mechanisms and potentially improve diagnostic accuracy, leading to the timely initiation of appropriate treatment and better patient outcomes. Additionally, the study aims to examine any differences in clinical and routine laboratory parameters between these groups.

2. Materials and Methods

The study analyzed data from three distinct groups of children, that is, “Severe COVID-19 pneumonia,” “Severe non-COVID-19 CAP,” and “COVID-associated MIS-C,” enrolled from the Indira Gandhi Institute of Child Health, a tertiary care pediatric hospital in Bangalore. All laboratory testing was performed in the Department of Neurovirology, National Institute of Mental Health and Neurosciences (NIMHANS), Bangalore. For this study, a subset of patients with sufficient samples for cytokine/ chemokine profiling were included.

Children with severe COVID-19 pneumonia and severe non-COVID-19 CAP were enrolled as a part of the same study from September 2019 to October 2021. These children were under 5 years of age and met the WHO IMCI (World Health Organization-Integrated Management of Childhood Illness) case definition of severe pneumonia, encompassing children presenting with cough and/or difficulty in breathing, accompanied by rapid breathing, with or without chest wall indrawing. Additionally, it involved the presence of danger signs indicative of severe disease, such as inability to drink, persistent vomiting, convulsions, lethargy or unconsciousness, stridor in a calm child, or severe malnutrition, which warranted hospitalization. Children with a duration of illness exceeding 7 days, those who had received antibiotics/antivirals for more than 72 h at presentation, or those with a history of hospitalization within the preceding 30 days were excluded from the study.

Children with COVID-19-associated MIS-C were enrolled through another study between March 2020 and December 2022. Eligible participants were children under 18 years of age who met the 2020 CDC MIS-C and acute encephalitis syndrome (AES) case definitions [8]. Briefly, this included children presenting with fever and altered mental status (such as altered behavior/personality, irritability, lethargy, drowsiness, altered speech), along with laboratory evidence of inflammation, clinically severe illness requiring hospitalization, multisystem organ involvement (involving more than two systems), and evidence of current or recent SARS-CoV-2 infection by RT-PCR, serology, or antigen test; or exposure to a suspected or confirmed COVID-19 case within 4 weeks before symptom onset, and absence of an alternative diagnosis.

Quantitative determination of anti-nucleocapsid antibodies was performed in all serum samples using the Elecsys Anti-SARS-CoV-2 N electrochemiluminescence immunoassay (Roche Diagnostics International Ltd). A cutoff index ≥ 1.0, as recommended by the manufacturer, indicated a reactive/positive result for anti-SARSCoV-2 antibodies. For SARS-CoV-2 RNA detection, RNA extraction utilized the QIAamp Viral RNA Mini Kit, and real-time PCR was conducted using the NIV-ICMR Single Tube Four Target Assay Kit [12].

Patient data were collected through medical records, clinical examinations, and laboratory tests. The sample size for each group was determined based on the availability of sufficient samples for cytokine/chemokine profiling, ensuring that the analyzed samples were representative of the respective populations.

Ethical approval for all studies was obtained from the institutional ethics and review boards of both institutions. The study team, trained in obtaining consent from parents/guardians and assent from older children, adhered to approved procedures and forms throughout the recruitment process.

2.1. Microbiological Tests

Blood samples were collected in plain tubes from all children included in the study. Additionally, throat and nasopharyngeal swabs were collected in viral transport medium (VTM) from children with severe COVID-19 pneumonia and severe non-COVID-19 CAP. Cerebrospinal fluid, wherever available, was collected from children with MIS-C. All samples were sent to the Department of Neurovirology at NIMHANS for extensive testing of infectious causes of pneumonia and AES, as appropriate.

For children in the MIS-C group, samples underwent extensive testing to rule out infectious causes of AES, utilizing a previously outlined laboratory algorithm [13]. Briefly, initial assays included serological tests for JEV, dengue, chikungunya, Leptospira sp, and scrub typhus. Subsequent tests involved real-time PCR for bacterial pathogens, herpes simplex virus (HSV) 1 and 2, enterovirus, varicella-zoster virus (VZV), mumps virus, and parechovirus.

For children with pneumonia, samples were subjected to COVID-sure multiplex real-time RT-PCR kit (Trivitron, Cat# 30201284) and multiplex PCR for respiratory infections using Fast Track Diagnostics (FTD) Respiratory pathogens 21 assay (Siemens Healthineers, Cat# 10921702). The multiplex PCR included targets for influenza A & B virus, human rhinovirus, human CoV 229E, NL63, HKU1, and OC43, human parainfluenza viruses, human metapneumovirus, human bocavirus, Mycoplasma pneumoniae, RSV, human parechovirus, enterovirus, and human adenovirus.

Serum samples from all three groups were further stored at −80°C for subsequent cytokine/chemokine profiling, with a focus on minimizing freeze−thaw cycles.

2.2. Cytokine and Chemokine Profiling

Serum cytokines and chemokines were measured using a Bio-Plex Pro Human Cytokine Screening Panel (Bio-Rad). The panel assessed 17 human cytokines and chemokines, divided into two subpanels:

Panel 1: IL-1RA, IL-12(p40), CCL11 (Eotaxin), GM-CSF, CCL2 (MCP-1), GROα (CXCL1), HGF, and M-CSF.

Panel 2: IL-1β, IL-2, IL-6, IL-10, IFN-γ, TNF, IL-8, IL-17A, and IL-1α.

The assay procedure involved incubating samples and standards with antibody-conjugated beads, followed by the addition of biotinylated detection antibodies and streptavidin−phycoerythrin. The plate was then read using a Bio-Plex MAGPIX multiplex reader (Bio-Rad), and the data were analyzed using Bio-Plex Manager Software version 6.0. To avoid bias due to undetectable levels or missing data, only mediators detected in more than 80% of the samples were included in the subsequent analyses.

2.3. Clinical Characteristic and Routine Laboratory Findings

Clinical characteristics and routine hematological and bio-chemical findings at admission were noted for all patients included in the study.

2.4. Statistical Analysis

Statistical analyses and data visualization were performed using R version 3.6.3 (The R Project for Statistical Computing) and Prism 8 version 10.1.0 (GraphPad Software). Descriptive statistics for categorical variables were presented as frequencies and percentages, while continuous variables were summarized using median and interquartile range (IQR) after assessing normality through visual inspection of histograms. Categorical data were compared using the χ2 or Fisher’s exact test, depending on sample size. Continuous skewed variables among the etiological groups were compared using the Mann−Whitney U test. A p-value < 0.05 was considered statistically significant. Exploratory correlations between inflammatory mediator levels were examined using Spearman’s correlation test. Heatmaps were generated from the correlation matrices to visually represent the mediators and highlight those with a strong positive (dark red) or a strong negative (dark blue) correlation, as described previously [8].

3. Results

The baseline characteristics of the three patient groups are summarized in Table 1. Although the recruitment criteria for MIS-C did not specifically include respiratory features, cough and/or breathing difficulty were present in six (66.6%) of the nine children with MIS-C. Within the severe non-COVID-19 CAP group, the etiologies found were rhinovirus (n = 6), RSV (n = 6), influenza A H1N1 (n = 3), and bocavirus (n = 1). The following mediators were not identified in > 80% of samples and were excluded from analysis: IL-12p40, GM-CSF, IL-2, IL-1α, and IL-1β.

Table 1. Baseline characteristics of study participants.

Parameter Severe COVID-19
pneumonia (n = 14, 36%)		 Severe non-COVID-19
CAP (n = 16, 41%)		 MIS-C
(n = 9, 24%)
Median (IQR1−IQR3) age 6 (3−17) months 7 (4.8−13.2) months 3.0 (1.6−7.0) years
Male:female ratio 1.8:1 1:1 2:1
Median duration of illness before presentation to the hospital 3.0 (2.0−4.0) days 3.0 (2.0−5.0) days 6.0 (4.0−7.0) days
Open in a new tab

3.1. MIS-C Versus Severe COVID-19 Pneumonia

There were no significant differences in the clinical features of MIS-C and severe COVID-19 pneumonia (Supporting MIS-C Information S1: Table 1). Median levels of all mediators, except for serum GROα, were higher in patients with MIS-C. Compared with severe COVID-19 pneumonia, serum levels of IL-1RA, IL-8, and TNF were significantly higher in patients with MIS-C (Figure 1). Additionally, serum levels of CCL11, HGF, and M-CSF were higher in the MIS-C group at a p-value close to 0.05 (0.059, 0.059, 0.051; respectively). Heat-map (Figure 2) revealed distinct patterns among different etiologies.

Figure 1. Graphical representation of cytokines/chemokines significantly associated with etiologies.

Figure 1

Open in a new tab

(a−c) Serum concentrations of mediators significantly different between MIS-C and severe COVID-19 pneumonia. (d−g) Serum concentrations of mediators significantly different between MIS-C and Severe non-COVID-19 CAP.

Figure 2. Heatmaps of correlations between different mediators in serum of etiological groups.

Figure 2

Open in a new tab

Heatmap reveals distinct patterns of inflammatory mediators in the etiological group.

At admission, the median values of the absolute neutrophil count, alanine transaminase, and creatinine were significantly higher, while median values of platelets, albumin, and potassium were significantly lower in children with MIS-C (Supporting Information S1: Table 2). Transaminitis (AST/ALT > 80 IU/L) was noted in six (66.7%) patients with MIS-C compared with three (21.4%) patients with severe COVID-19 pneumonia (p = 0.077).

3.2. Severe COVID-19 Pneumonia Versus Severe non-COVID-19 CAP

Children with severe COVID-19 pneumonia and severe non-COVID-19 CAP were below 5 years of age, and there was no significant age difference between the two groups. Both groups presented with respiratory findings; however, cough was a presenting feature in all children with severe non-COVID-19 CAP, compared with nine (64%) children with severe COVID-19 pneumonia (p = 0.014). Similarly, abnormal respiratory sounds were present in 14 (87.5%) children with severe non-COVID-19 CAP compared with five (36%) children with severe COVID-19 pneumonia (p = 0.007). The duration of hospitalization was significantly higher in children with severe COVID-19 pneumonia (median [IQR1−IQR3]: 13.0 [9.0−17.8] days) compared with children with severe non-COVID-19 CAP (Median [IQR1−IQR3]: 7.0 [5.8−8.2] days) (p = 0.009) (Supporting Information S1: Table 3).

Except for blood total leukocyte count, which was significantly higher in children with severe non-COVID-19 CAP, there were no other statistically significant differences in inflammatory mediators and routine blood investigations between the two groups (Supporting Information S1: Table 4).

3.3. MIS-C (With Respiratory Features) Versus Severe Non-COVID-19 CAP

No statistically significant differences were observed in clinical findings between children with severe non-COVID-19 CAP and children with MIS-C who had respiratory findings (Supporting Information S1: Table 5). The duration of hospitalization was significantly higher in children with MIS-C (Median [IQR1−IQR3]: 17.0 [17.0−25.2] days) compared with severe non-COVID-19 CAP (Median [IQR1−IQR3]: 7.0 [5.8−8.2] days) (p = 0.002).

Serum levels of CCL2, HGF, M-CSF, and IL-8 were significantly higher in children with MIS-C (with respiratory features) compared with severe non-COVID-19 CAP (Figures 1 and 2). Serum albumin and platelet counts were significantly lower, while creatinine and liver enzymes were significantly higher in MIS-C (with respiratory features). Transaminitis was noted in five (83.3%) children with MIS-C compared with one (6.2%) child with severe non-COVID-19 CAP (Supporting Information S1: Table 6).

4. Discussion

This study identified distinct inflammatory mediator profiles in children with severe COVID-19 pneumonia, severe non-COVID-19 CAP, and MIS-C. Our findings also highlight the importance of immune response markers in differentiating between these three conditions, as clinical symptoms alone are insufficient for accurate diagnosis.

MIS-C patients in our study had a higher median age (3 years) compared with severe COVID-19, which may be partially explained by the different age limits during recruitment. However, it is important to note that MIS-C can also occur in very young children, as recently reported from lower- and middle-income countries (LMICs) [14, 15]. This finding has implications for understanding the epidemiology of MIS-C and emphasizes the need for vigilance in diagnosing and managing this condition in young children.

Our study also confirms that children with MIS-C are at higher risk of prolonged hospitalization compared to those with other serious viral respiratory infections [2, 16]. We found that low platelet count significantly differentiated MIS-C from severe COVID-19 pneumonia, consistent with previous reports [4]. Additionally, derangement in liver enzymes, urea, creatinine, albumin, and potassium levels was significantly associated with MIS-C, reflecting the multisystem nature of the syndrome [17–21]. These laboratory findings may be related to the underlying pathophysiological mechanisms of MIS-C, such as endothelial dysfunction and hyperinflammation.

Notably, our study identified several inflammatory markers that could potentially differentiate MIS-C from severe COVID-19 pneumonia and severe non-COVID-19 CAP. Median levels of serum GROα, a known marker of severity of SARS-CoV-2, were higher in patients with severe COVID-19 pneumonia compared with the other two groups, although not significantly. This finding suggests that the underlying mechanism of neutrophil hyper-activation may differ between severe COVID-19 and other groups [22].

IL-8, significantly elevated in MIS-C in our study, is reported to differentiate MIS-C from Kawasaki Disease [23] and serves as a marker of severity in influenza infections in children [24]. Additionally, IL-8 has been associated with severity in adult influenza [25] and COVID-19 [26], and has been shown to be significantly higher in COVID-19 compared to influenza A (H1N1) [27]. Our is the first study to report its role in differentiating both COVID-19 and non-COVID-19 viral infections from MIS-C in children. However, further evaluation with a larger sample size is required to fully understand its significance in the pediatric population. However, further evaluation with a larger sample size is necessary to establish its utility as a biomarker for MIS-C.

IL-1RA, an anti-inflammatory marker, and TNF, a proinflammatory marker, were both found to be significantly higher in MIS-C compared with severe COVID-19. These findings support the previously stated hypothesis that MIS-C entails a dysregulated immune response with both hypo- and hyper-inflammatory characteristics. It has also been hypothesized that this balance is influenced by genetic variations. These findings have important clinical implications related to the treatment of MIS-C, as both markers have been shown to normalize in response to treatment. The occurrence of such a dysregulated immune response also highlights the importance of cautious immunomodulatory therapy to prevent iatrogenic harm in these patients [28–34].

In the current study, HGF, M-CSF, and CCL11 levels were higher in the MIS-C group than in the severe COVID-19 pneumonia group, and this difference was approaching significance. Furthermore, M-CSF and HGF were significantly higher in MIS-C compared with severe non-COVID-19 CAP. HGF, in particular, has been previously associated with severe COVID-19 [18–20] but not with MIS-C [11]. Our study demonstrates that elevated HGF may potentially distinguish MIS-C from severe COVID-19 as well as from severe non-COVID-19 CAP. Moreover, elevated HGF, combined with significantly low platelet counts, are indicative of a more severe endothelial dysfunction and pro-thrombotic state in MIS-C compared to severe COVID-19 [21].

M-CSF has been reported to differentiate between MIS-C and other non-COVID-19 febrile illnesses [35], and our study reiterates the finding of elevated M-CSF levels in MIS-C compared with febrile controls. While M-CSF is reported to be a marker of severity in adult patients with influenza [25], COVID-19 [26, 27], and adenovirus respiratory infection [36], its significance in pediatric severe respiratory infections remains unknown. One of the biological functions of M-CSF is stimulating the release of CCL2 [37]. Accordingly, we also found that serum levels of CCL2, associated with enhanced macrophage infiltration and hyperinflammatory endothelial dysfunction [38], were significantly higher in children with MIS-C compared to severe non-COVID-19 CAP. Although there is no precedence of such a comparison in existing literature, increased levels of CCL2 in nasal wash have been seen in influenza and RSV infections [39], while raised serum CCL2 has been associated with acute COVID-19 infections [31], MIS-C [31, 38, 40], and mortality in influenza H7N9 infection [41]. Furthermore, CCL2 is a potential therapeutic target for both severe COVID-19 and MIS-C [38].

CCL11, a neuroinflammatory marker associated with “brain fog” in long COVID, was elevated in MIS-C patients compared with COVID-19 patients in our study. This finding is likely due to the inclusion of children with MIS-C as part of a study focusing on AES [8]. CCL11 has been previously linked to cardiac manifestations and male gender in MIS-C patients [11, 31, 42, 43].

This study contributes to the expanding body of evidence highlighting the importance of inflammatory markers as diagnostic and prognostic tools for both inflammatory [44, 45] and infectious diseases [46, 47], especially in pediatric patients. Interest in this field surged during the COVID-19 pandemic as research clarified the roles of cytokines and chemokines in SARS-CoV-2 infection and in MIS-C [48, 49].

Our study has limitations, including a small sample size in each category and the lack of samples from healthy controls. Additionally, potential confounding factors such as age, gender, and collection of samples at different stages of the disease process might have influenced the levels of inflammatory markers. By grouping viral causes of CAP into a single group (i.e., severe non-COVID-19 CAP), potential differences among specific viral etiologies may have been overlooked. Therefore, the role of these markers in pediatric severe respiratory infections and MIS-C warrants further investigation.

5. Conclusions

In summary, the findings of this study suggest that MIS-C is associated with distinct inflammatory markers such as IL-1RA, IL-8, TNF, M-CSF, CCL2, and HGF, which may serve as potential biomarkers. Elevated GROα levels in severe COVID-19 pneumonia merit further exploration. The findings support the integration of inflammatory markers with routine laboratory parameters and molecular assays to improve diagnosis and differentiation of severe COVID-19 pneumonia, severe non-COVID-19 pneumonia, and MIS-C, ultimately improving patient management and outcomes. Further research with larger populations is necessary to validate these biomarkers’ clinical utility.

Supplementary Material

Additional supporting information can be found online in the Supporting Information section.

Supporting information

Acknowledgments

This work was supported by DBT/Wellcome Trust India Alliance Fellowship IA/CPHE/18/1/503960 awarded to Dr. Tina Damodar and a grant from the Indian Council of Medical Research (ICMR) (Project ID: 2021−3668) to Dr. Reeta S. Mani. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Funding

This work was supported by DBT/Wellcome Trust India Alliance Fellowship IA/CPHE/18/1/503960 awarded to Dr. Tina Damodar and a grant from the Indian Council of Medical Research (ICMR) (Project ID: 2021−3668) to Dr. Reeta S. Mani.

Footnotes

Author Contributions

All authors contributed to the study’s conception and design. Material preparation, data collection, and analysis were performed by Tina Damodar, Lonika Lodha, Sourabh Suran, Namratha Prabhu, Maria Jose, and Uddhav Kinhal. The first draft of the manuscript was written by Tina Damodar and Lonika Lodha and reviewed by Reeta S Mani. All authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.

Ethics Statement

Ethical approval for all studies was obtained from the institutional ethics and review boards of IGICH and the coordinating center, the National Institute of Mental Health and Neurosciences (NIMHANS). The study team, trained in obtaining consent from parents/guardians and assent from older children, adhered to approved procedures and forms throughout the recruitment process.

Conflicts of Interest

The authors declare no conflicts of interest.

Data Availability Statement

The datasets generated during and/or analyzed during the current study are available from the corresponding author upon reasonable request.

References

  • 1.COVID-19 Dashboard, Home, MoHFW, Government of India. https://covid19dashboard.mohfw.gov.in/
  • 2.Gupta V, Singh A, Ganju S, et al. Severity and Mortality Associated With COVID-19 Among Children Hospitalised in Tertiary Care Centres in India: A Cohort Study. Lancet Regional Health - Southeast Asia. 2023;13:100203. doi: 10.1016/j.lansea.2023.100203. http://www.thelancet.com/article/S277236822300063X/fulltext . [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 3.Chow EJ, Uyeki TM, Chu HY. The Effects of the COVID-19 Pandemic on Community Respiratory Virus Activity. Nature Reviews Microbiology. 2023;21:195–210. doi: 10.1038/s41579-022-00807-9. https://www.nature.com/articles/s41579-022-00807-9 . [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 4.Feldstein LR, Tenforde MW, Friedman KG, et al. Characteristics and Outcomes of US Children and Adolescents With Multisystem Inflammatory Syndrome in Children (MIS-C) Compared With Severe Acute COVID-19. Journal of the American Medical Association. 2021;325:1074–1087. doi: 10.1001/jama.2021.2091. https://jamanetwork.com/journals/jama/fullarticle/2777026 . [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 5.Coronavirus Disease (COVID-19) Similarities and Differences Between COVID-19 and Influenza. World Health Organization Newsroom; https://www.who.int/news-room/questions-and-answers/item/coronavirus-disease-covid-19-similarities-and-differences-with-influenza . [Google Scholar]
  • 6.Losier A, Gupta G, Caldararo M, Dela Cruz CS. The Impact of Coronavirus Disease 2019 on Viral, Bacterial, and Fungal Respiratory Infections. Clinics in Chest Medicine. 2023;44:407–423. doi: 10.1016/j.ccm.2022.11.018. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 7.Farida H, Triasih R, Lokida D, et al. Epidemiologic, Clinical, and Serum Markers May Improve Discrimination Between Bacterial and Viral Etiologies of Childhood Pneumonia. Frontiers in Medicine. 2023;10:1140100. doi: 10.3389/fmed.2023.1140100. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 8.Damodar T, Dunai C, Prabhu N, et al. Diagnostic Markers of Acute Encephalitis Syndrome and COVID-Associated Multisystem Inflammatory Syndrome in Children From Southern India. Journal of Medical Virology. 2024;96:e29666. doi: 10.1002/jmv.29666. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 9.Luciani LL, Miller LM, Zhai B, et al. Blood Inflammatory Biomarkers Differentiate Inpatient and Outpatient Coronavirus Disease 2019 From Influenza. Open Forum Infectious Diseases. 2023;10:ofad095. doi: 10.1093/ofid/ofad095. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 10.Sun YK, Wang C, Lin PQ, et al. Severe Pediatric COVID-19: A Review From the Clinical and Immunopathophysiological Perspectives. World Journal of Pediatrics. 2024;20:307–324. doi: 10.1007/s12519-023-00790-y. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 11.Pacheco-Hernández LM, Ramírez-Noyola JA, Gómez-García IA, Ignacio-Cortés S, Zúñiga J, Choreño-Parra JA. Comparing the Cytokine Storms of COVID-19 and Pandemic Influenza. Journal of Interferon & Cytokine Research. 2022;42:369–392. doi: 10.1089/jir.2022.0029. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 12.Ravindra A, Mishra B, Rath S, et al. Comparability of the Sensitivity of Different Real Time PCR Kits Used in the Detection of SARS CoV-2. Indian Journal of Medical Microbiology. 2021;39:S74 [Google Scholar]
  • 13.Damodar T, Singh B, Prabhu N, et al. Association of Scrub Typhus in Children With Acute Encephalitis Syndrome and Meningoencephalitis, Southern India. Emerging Infectious Diseases. 2023;29:711–722. doi: 10.3201/eid2904.221157. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 14.Mohsin SS, Abbas Q, Chowdhary D, et al. Multisystem Inflammatory Syndrome (MIS-C) in Pakistani Children: A Description of the Phenotypes and Comparison With Historical Cohorts of Children With Kawasaki Disease and Myocarditis. PLoS One. 2021;16:e0253625. doi: 10.1371/journal.pone.0253625. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 15.Chinniah K, Bhimma R, Naidoo KL, et al. Multisystem Inflammatory Syndrome in Children Associated With SARS-CoV-2 Infection in KwaZulu-Natal, South Africa. Pediatric Infectious Disease Journal. 2023;42:e9–e14. doi: 10.1097/INF.0000000000003759. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 16.Shein SL, Carroll CL, Remy KE, et al. Epidemiology and Outcomes of SARS-CoV-2 Infection or Multisystem Inflammatory Syndrome in Children vs Influenza Among Critically Ill Children. JAMA Network Open. 2022;5:e2217217. doi: 10.1001/jamanetworkopen.2022.17217. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 17.Trifonova I, Ngoc K, Nikolova M, et al. Patterns of Cytokine and Chemokine Expression in Peripheral Blood of Patients With COVID-19 Associated With Disease Severity. International Journal of Immunopathology and Pharmacology. 2023;37:1–12. doi: 10.1177/03946320231163681. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 18.Wolszczak-Biedrzycka B, Dorf J, Wojewódzka-Żelezniakowicz M, et al. Changes in Chemokine and Growth Factor Levels May Be Useful Biomarkers for Monitoring Disease Severity in COVID-19 Patients; A Pilot Study. Frontiers in Immunology. 2023;14:1320362. doi: 10.3389/fimmu.2023.1320362. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 19.Ravindran R, O’Connor E, Gupta A, et al. Lipid Mediators and Cytokines/Chemokines Display Differential Profiles in Severe Versus Mild/Moderate COVID-19 Patients. International Journal of Molecular Sciences. 2023;24:13054. doi: 10.3390/ijms241713054. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 20.Gorgojo-Galindo Ó, Martín-Fernández M, Peñarrubia-Ponce MJ, et al. Predictive Modeling of Poor Outcome in Severe COVID-19: A Single-Center Observational Study Based on Clinical, Cytokine and Laboratory Profiles. Journal of Clinical Medicine. 2021;10:5431. doi: 10.3390/jcm10225431. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 21.Zaira B, Yulianti T, Levita J. Correlation Between Hepatocyte Growth Factor (HGF) With D-Dimer and Interleukin-6 As Prognostic Markers of Coagulation and Inflammation in Long COVID-19 Survivors. Current Issues in Molecular Biology. 2023;45:5725–5740. doi: 10.3390/cimb45070361. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 22.Boribong BP, LaSalle TJ, Bartsch YC, et al. Neutrophil Profiles of Pediatric COVID-19 and Multisystem Inflammatory Syndrome in Children. Cell Reports Medicine. 2022;3:100848. doi: 10.1016/j.xcrm.2022.100848. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 23.Fabi M, Filice E, Biagi C, et al. Multisystem Inflammatory Syndrome Following SARS-CoV-2 Infection in Children: One Year After the Onset of the Pandemic in a High-Incidence Area. Viruses. 2021;13:2022. doi: 10.3390/v13102022. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 24.Takano T, Tajiri H, Kashiwagi Y, Kimura S, Kawashima H. Cytokine and Chemokine Response in Children With the 2009 Pandemic Influenza A (H1N1) Virus Infection. European Journal of Clinical Microbiology & Infectious Diseases: Official Publication of the European Society of Clinical Microbiology. 2011;30:117–120. doi: 10.1007/s10096-010-1041-9. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 25.Zhang J, Wang J, Gong Y, Gu Y, Xiang Q, Tang LL. Interleukin-6 and Granulocyte Colony-Stimulating Factor as Predictors of the Prognosis of Influenza-Associated Pneumonia. BMC Infectious Diseases. 2022;22:343. doi: 10.1186/s12879-022-07321-6. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 26.Monserrat J, Gómez-Lahoz A, Ortega M, et al. Role of Innate and Adaptive Cytokines in the Survival of COVID-19 Patients. International Journal of Molecular Sciences. 2022;23:10344. doi: 10.3390/ijms231810344. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 27.Guo J, Wang S, Xia H, et al. Cytokine Signature Associated With Disease Severity in COVID-19. Frontiers in Immunology. 2021;12:681516. doi: 10.3389/fimmu.2021.681516. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 28.Gelzo M, Castaldo A, Giannattasio A, et al. MIS-C: A COVID-19-As sociated Condition Between Hypoimmunity and Hyperimmunity. Frontiers in Immunology. 2022;13:985433. doi: 10.3389/fimmu.2022.985433. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 29.Moreews M, Le Gouge K, Khaldi-Plassart S, et al. Polyclonal Expansion of TCR Vβ 21.3+ CD4+ and CD8+ T Cells Is a Hallmark of Multisystem Inflammatory Syndrome in Children. Science Immunology. 2021;6:eabh1516. doi: 10.1126/sciimmunol.abh1516. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 30.Syrimi E, Fennell E, Richter A, et al. The Immune Landscape of SARS-CoV-2-Associated Multisystem Inflammatory Syndrome in Children (MIS-C) From Acute Disease to Recovery. iScience. 2021;24:103215. doi: 10.1016/j.isci.2021.103215. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 31.Peart Akindele N, Kouo T, Karaba AH, et al. Distinct Cytokine and Chemokine Dysregulation in Hospitalized Children With Acute Coronavirus Disease 2019 and Multisystem Inflammatory Syndrome With Similar Levels of Nasopharyngeal Severe Acute Respiratory Syndrome Coronavirus 2 Shedding. Journal of Infectious Diseases. 2021;224:606–615. doi: 10.1093/infdis/jiab285. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 32.Talarico LB, Toledano A, Contrini MM, et al. Distinct Immune Phenotypes and Cytokine Profiles in Children with Differing Severity of COVID-19. Pediatric Infectious Disease Journal. 2022;41:919–926. doi: 10.1097/INF.0000000000003669. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 33.Rodríguez-Rubio M, Menéndez-Suso JJ, Cámara-Hijón C, et al. Cytokine Profile in Children With Severe Multisystem Inflammatory Syndrome Related to the Coronavirus Disease 2019. Journal of Pediatric Intensive Care. 2022;11:259–264. doi: 10.1055/s-0041-1724101. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 34.Diorio C, Henrickson SE, Vella LA, et al. Multisystem Inflammatory Syndrome in Children and COVID-19 Are Distinct Presentations of SARS-COV-2. Journal of Clinical Investigation. 2020;130:5967–5975. doi: 10.1172/JCI140970. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 35.Huang JJ, Gaines SB, Amezcua ML, et al. Upregulation of Type 1 Conventional Dendritic Cells Implicates Antigen Cross-Presentation in Multisystem Inflammatory Syndrome. Journal of Allergy and Clinical Immunology. 2022;149:912–922. doi: 10.1016/j.jaci.2021.10.015. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 36.Li J, Wei J, Xu Z, et al. Cytokine/Chemokine Expression Is Closely Associated Disease Severity of Human Adenovirus Infections in Immunocompetent Adults and Predicts Disease Progression. Frontiers in Immunology. 2021;12:1. doi: 10.3389/fimmu.2021.691879. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 37.Ushach I, Zlotnik A. Biological Role of Granulocyte Macrophage Colony-Stimulating Factor (GM-CSF) and Macrophage Colony-Stimulating Factor (M-CSF) on Cells of the Myeloid Lineage. Journal of Leukocyte Biology. 2016;100:481–489. doi: 10.1189/jlb.3RU0316-144R. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 38.Gelzo M, Giannattasio A, Maglione M, et al. Biomarkers of Endothelial Damage in Distinct Phases of Multisystem Inflammatory Syndrome in Children. Metabolites. 2022;12:680. doi: 10.3390/metabo12080680. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 39.Gill MA, Long K, Kwon T, et al. Differential Recruitment of Dendritic Cells and Monocytes to Respiratory Mucosal Sites in Children With Influenza Virus or Respiratory Syncytial Virus Infection. Journal of Infectious Diseases. 2008;198:1667–1676. doi: 10.1086/593018. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 40.Caldarale F, Giacomelli M, Garrafa E, et al. Plasmacytoid Dendritic Cells Depletion and Elevation of IFN-γ Dependent Chemokines CXCL9 and CXCL10 in Children With Multisystem Inflammatory Syndrome. Frontiers in Immunology. 2021;12:654587. doi: 10.3389/fimmu.2021.654587. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 41.Guo J, Huang F, Liu J, et al. The Serum Profile of Hypercyto-kinemia Factors Identified in H7N9-Infected Patients Can Predict Fatal Outcomes. Scientific Reports. 2015;5:10942. doi: 10.1038/srep10942. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 42.Kumar NP, Venkataraman A, Nancy A, et al. Immune Profiles in Multisystem Inflammatory Syndrome in Children With Cardiovascular Abnormalities. Viruses. 2023;15:2162. doi: 10.3390/v15112162. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 43.Rajamanickam A, Kumar NP, Venkataraman A, et al. Sex-Specific Differences in Systemic Immune Responses in Mis-C Children. Scientific Reports. 2024;14:1720. doi: 10.1038/s41598-024-52116-1. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 44.Yang J, Li Y, Luo H, et al. Elevated Serum Levels of the NLRP3 Inflammasome Are Associated With the Severity of Anti-NMDAR Encephalitis in Children. Clinica Chimica Acta. 2023;551:117587. doi: 10.1016/j.cca.2023.117587. [DOI] [PubMed] [Google Scholar]
  • 45.Diamantino Soares AC, Araújo Passos LS, Sable C, et al. Circulating Cytokines Predict Severity of Rheumatic Heart Disease. International Journal of Cardiology. 2019;289:107–109. doi: 10.1016/j.ijcard.2019.04.063. [DOI] [PubMed] [Google Scholar]
  • 46.Hao M, Wang X, Du J, et al. Cytokine Levels Are Associated With the Severity of Varicella Infections. Journal of Infection in Developing Countries. 2015;9:190–196. doi: 10.3855/jidc.5255. [DOI] [PubMed] [Google Scholar]
  • 47.Yang M, Meng F, Gao M, Cheng G, Wang X. Cytokine Signatures Associate With Disease Severity in Children With Mycoplasma Pneumoniae Pneumonia. Scientific Reports. 2019;9:17853. doi: 10.1038/s41598-019-54313-9. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 48.Vanetti C, Lampasona V, Stracuzzi M, et al. The Immunological Profile of SARS-CoV-2 Infection in Children Is Linked to Clinical Severity and Age. International Journal of Molecular Sciences. 2023;24:6779. doi: 10.3390/ijms24076779. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 49.Calcaterra V, Loretelli C, Biganzoli D, et al. Long-Term Cytokine Profile in Multisystem Inflammatory Disease Among Children. Cytokine. 2024;183:156744. doi: 10.1016/j.cyto.2024.156744. [DOI] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supporting information
EMS202694-supplement-Supporting_information.docx (49.7KB, docx)

Data Availability Statement

The datasets generated during and/or analyzed during the current study are available from the corresponding author upon reasonable request.

RESOURCES