Diagnostic Utility of Creatine Kinase and IL-10 in Early Discrimination Between Pediatric Influenza A (H1N1) and Adenovirus Infections

Diagnostic Utility of Creatine Kinase and IL-10 in Early Discrimination Between Pediatric Influenza A (H1N1) and Adenovirus Infections | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Diagnostic Utility of Creatine Kinase and IL-10 in Early Discrimination Between Pediatric Influenza A (H1N1) and Adenovirus Infections Jiahao Wang, Xun Zhu, Deru Lei, Yibing Zheng, Suzhen Pan, Xianming He, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8548499/v1 This work is licensed under a CC BY 4.0 License Status: Under Revision Version 1 posted 5 You are reading this latest preprint version Abstract Background Differentiating influenza, A (H1N1) from adenovirus infection in children remains challenging during concurrent outbreaks due to overlapping clinical features. Rapid, reliable biomarkers are needed to guide early management. Methods We retrospectively reviewed clinical and laboratory data from 307 children with laboratory-confirmed influenza A (H1N1) and 118 with adenovirus infection admitted to the Second Affiliated Hospital of Wenzhou Medical University between May and September 2024. Demographics and serum levels of creatine kinase (CK), lactate dehydrogenase (LDH), aspartate aminotransferase (AST), interleukin-8 (IL-8), and interleukin-10 (IL-10) were compared. Univariate and multivariate logistic regression models were used to assess discriminative performance. Diagnostic accuracy was evaluated using area under the receiver operating characteristic curve (AUC), with optimal cut-offs determined by Youden’s index. Results Children with H1N1 were older than those with adenovirus infection (5.67 ± 3.45 vs. 3.82 ± 1.94 years; P < 0.05); sex distribution did not differ significantly. Among single markers, IL-10 showed the highest AUC for identifying H1N1 (0.922; 95% CI: 0.870–0.974), followed by CK (0.915; 0.869–0.961) and LDH (0.880; 0.818–0.942). A combined model of CK and IL-10 yielded an AUC of 0.965 (95% CI: 0.938–0.993), with sensitivity of 90.0% and specificity of 94.1%, outperforming any individual marker. Conclusions The combination of serum CK and IL-10 demonstrates high diagnostic accuracy for early differentiation of influenza A (H1N1) from adenovirus infection in children. This dual-marker approach may support timely clinical decision-making and pathogen-directed management in acute respiratory illness. Influenza A (H1N1) Adenovirus infection Creatine kinase Interleukin-10 Early diagnosis Figures Figure 1 Figure 2 Figure 3 1. Background Influenza A (H1N1) is a highly transmissible acute respiratory infection that spreads rapidly and continues to pose a significant global public health burden( 2 ). Children are especially susceptible owing to incomplete respiratory development and relative immune immaturity( 3 ). Adenovirus, meanwhile, ranks among the most common viral causes of community-acquired pneumonia (CAP) in this age group and carries a high risk of severe outcomes( 1 ). Untreated or delayed diagnosis can lead to progressive pneumonia and long-term sequelae—including bronchiectasis, pulmonary fibrosis, and atelectasis—jeopardizing both short- and long-term health( 4 ). Timely differentiation between these two infections is clinically crucial. Early pathogen identification allows for targeted antiviral use, which can shorten illness duration and reduce complications( 4 ). Yet during overlapping seasonal peaks, H1N1 and adenovirus present with strikingly similar signs and symptoms. Young children often cannot articulate their complaints clearly, further complicating clinical judgment( 5 ).PCR remains the diagnostic gold standard for both viruses, but its practical utility in early triage is limited. Turnaround times are often too long for acute decision-making, results depend heavily on sampling quality, and false negatives remain a concern( 6 ). Efforts have therefore turned to serum biomarkers as potential aids for rapid discrimination. Traditional markers like white blood cell count and C-reactive protein (CRP) help distinguish bacterial from viral etiologies but lack specificity between different viruses. Although elevated CRP has been linked to bacterial co-infection in H1N1 cases, evidence is inconsistent( 7 ). Procalcitonin (PCT) typically stays low in pure viral infections but rises in bacterial, fungal, or parasitic disease; some studies suggest it may help rule out bacterial superinfection in influenza( 8 ). However, most data come from adult or critically ill populations—robust pediatric evidence is still lacking. To address this gap, we retrospectively analyzed data from 307 children with confirmed H1N1 infection and 118 with adenovirus infection diagnosed during the same outbreak period in 2024. Focusing on cardiac enzymes and cytokines, we specifically evaluated the diagnostic performance of creatine kinase (CK) and interleukin-10 (IL-10) in distinguishing these two entities. Our goal was to identify readily measurable, early-phase biomarkers that could support more precise and timely clinical decisions in pediatric practice. 2. Materials and Methods 2.1 Study Population This retrospective study included 307 children diagnosed with H1N1 and 118 with adenovirus infection at the Second Affiliated Hospital of Wenzhou Medical University between May and September 2024. All cases were confirmed through multiplex PCR testing of respiratory secretions. The study was approved by the Ethics Committee of the hospital, adhering to the principles outlined in the Declaration of Helsinki, and informed consent was obtained from all guardians. 2.2 Inclusion and Exclusion Criteria Diagnostic Criteria: H1N1: Confirmed according to the Expert Consensus on Diagnosis and Treatment of Influenza in Children (2015 Edition) by the Pediatric Respiratory Group of the Chinese Medical Association. Adenovirus: Diagnosed based on criteria set forth in the Expert Consensus on Integrated Traditional Chinese and Western Medicine Diagnosis and Treatment of Viral Pneumonia in Children (2019 Edition). Inclusion Criteria:1) Age between 1 month and 14 years.2) Complete clinical and laboratory data available.3) First visit without prior antiviral or corticosteroid treatment. Exclusion Criteria:1) Co-infection with bacteria, mycoplasma, or fungi.2) History of severe chronic heart, liver, or kidney disease or immunodeficiency.3) Previous history of muscle diseases or hemolytic disorders. 2.3 Methods 2.3.1 Laboratory Testing Venous blood samples were collected within 24 hours of admission. CK, LDH, and AST levels were measured using a Beckman AU5830 biochemical analyzer. Cytokine levels (IL-8, IL-10) were detected via flow cytometry (FACS Canto, provided by Jiangxi Saige Biotechnology Co., Ltd.). All blood tests were performed within 48 hours of fever onset. Control samples were collected from healthy children during outpatient visits or health check-ups. 2.3.2 Detection of H1N1 and Adenovirus Nasopharyngeal swabs or sputum samples were collected upon admission. H1N1 diagnosis was confirmed using real-time fluorescent PCR (ABI7500 Real-Time PCR System, reagents from Jiangsu Success Bio-Tech Co., Ltd.). Adenovirus detection utilized RT-PCR coupled with capillary electrophoresis (Eastwin ETC811 Gene Amplifier and 3500Dx Genetic Analyzer, reagents from Ningbo HealthGene Technologies Co., Ltd.). 2.4 Statistical Analysis Data were analyzed using SPSS 21.0 software. Continuous variables were tested for normality and presented as mean ± standard deviation (mean ± SD). One-way ANOVA was used for comparisons among multiple groups, with LSD test for homogeneous variances and Dunnett's T3 for heterogeneous variances. Univariate logistic regression assessed the diagnostic performance of each biomarker (CK, AST, LDH, IL-8, IL-10). Multivariate logistic regression models were constructed using forward stepwise selection with P < 0.10. Model performance was evaluated by calculating the area under the receiver operating characteristic curve (AUC), and Hanley and McNeil methods compared AUC values. Optimal ROC cut-off points were determined using Youden’s index (sensitivity + specificity − 1). Statistical significance was set at P < 0.05 (ns: not significant; * P < 0.05; ** P < 0.01; *** P < 0.001; **** P < 0.0001). 3. Results 3.1 Clinical and Laboratory Characteristics of the Study Population A total of 427 children were included: 310 with H1N1 and 117 with adenovirus infection. Baseline and laboratory characteristics are summarized in Table 1 . Children with H1N1 were significantly older than those with adenovirus infection (5.66 ± 3.44 vs. 3.83 ± 1.95 years; t = 6.88, P < 0.001). Inflammatory markers differed markedly between groups. CRP and white blood cell count (WBC) were both higher in the adenovirus group (P < 0.001 for both). Differential leukocyte counts showed a higher neutrophil percentage in H1N1 cases (P < 0.001), whereas lymphocyte and monocyte percentages were elevated in adenovirus infection (P 0.05 for all). Table 1 Comparison of clinical features between influenza A group and adenovirus group Variables Total (n = 427) H1N1 (n = 310) Adenovirus (n = 117) Statistic P Age, Mean ± SD 5.16 ± 3.21 5.66 ± 3.44 3.83 ± 1.95 t = 6.88 < .001 Sex, n(%) χ²=0.01 0.929 0 181 (42.39) 131 (42.26) 50 (42.74) 1 246 (57.61) 179 (57.74) 67 (57.26) CRP, Mean ± SD 17.02 ± 21.91 10.97 ± 14.60 33.01 ± 28.95 t=-7.49 < .001 PCT, Mean ± SD 0.65 ± 1.29 0.73 ± 1.67 0.57 ± 0.74 t = 0.63 0.527 WBC, Mean ± SD 8.30 ± 3.64 7.68 ± 3.22 10.02 ± 4.17 t=-5.26 < .001 Neutrophils, Mean ± SD 0.66 ± 0.18 0.68 ± 0.17 0.61 ± 0.19 t = 3.74 < .001 Lymphocyte, Mean ± SD 0.24 ± 0.16 0.22 ± 0.16 0.28 ± 0.16 t=-3.73 < .001 Monocyte, Mean ± SD 0.09 ± 0.03 0.09 ± 0.03 0.10 ± 0.03 t=-2.21 0.028 Uric acid, Mean ± SD 262.35 ± 76.36 265.61 ± 82.58 258.63 ± 69.04 t = 0.54 0.593 t: t-test, χ²: Chi-square test ;SD: standard deviation 3.2 Comparison of Serum Inflammatory Cytokines and Tissue Injury Markers Among Groups Serum levels of inflammatory cytokines and tissue injury markers differed significantly across healthy controls, children with H1N1, and those with adenovirus infection (Fig. 1 ). Compared with healthy controls, the H1N1 group showed markedly higher levels of CK, aspartate aminotransferase (AST), and LDH) (P < 0.0001 for all). Levels of interleukin-8 (IL-8) and interleukin-10 (IL-10) were also significantly elevated in the H1N1 group versus controls (P < 0.0001 for both).When directly compared with the adenovirus group, children with H1N1 exhibited significantly higher concentrations of IL-8, IL-10, CK, AST, and LDH (P < 0.001 for all comparisons). 3.3 Independent Predictive Value of CK and IL-10 in H1N1 Versus Adenovirus Infection Univariate logistic regression analysis in children with H1N1 identified LDH, CK, AST, IL-8, and IL-10 as significantly associated with the outcome. Specifically, CK (OR = 1.07, 95% CI: 1.05–1.09) and IL-10 (OR = 2.15, 95% CI: 1.65–2.82) showed the strongest associations. After multivariate adjustment, CK (OR = 1.13, 95% CI: 1.01–1.27, P = 0.037) and IL-10 (OR = 5.31, 95% CI: 1.19–23.78, P = 0.029) remained independent predictors (Fig. 2 A).In children with adenovirus infection, univariate analysis also revealed significant associations between LDH, CK, AST, IL-8, and IL-10 and the outcome. Among these, LDH (OR = 1.14, 95% CI: 1.07–1.22) and IL-10 (OR = 1.41, 95% CI: 1.10–1.81) were most strongly linked to increased risk. Multivariate analysis confirmed that LDH (OR = 1.19, 95% CI: 1.07–1.32, P = 0.001) and IL-10 (OR = 2.91, 95% CI: 1.05–8.04, P = 0.039) remained statistically significant, whereas CK and other markers lost significance after adjustment (Fig. 2 B).Comparing the two groups, CK and IL-10 demonstrated stronger predictive power in distinguishing H1N1 from adenovirus infection. Both CK and IL-10 were independent predictors in H1N1 cases, with IL-10 showing the highest effect size. In contrast, CK did not retain independent significance in adenovirus infections. Therefore, the combination of CK and IL-10 offers a valuable tool for early differentiation between these two conditions, aiding rapid clinical diagnosis and targeted management. 3.4 Diagnostic Performance of Serum Biomarkers for Differentiating H1N1 from Adenovirus Infection Receiver operating characteristic (ROC) curve analysis was performed to assess the diagnostic accuracy of serum biomarkers in distinguishing H1N1 from adenovirus infection (Table 2 ). In children with H1N1, both CK and interleukin-10 (IL-10) demonstrated high discriminative ability. CK yielded an area under the curve (AUC) of 0.915 (95% CI: 0.869–0.961), with an optimal cutoff of 137.0 U/L. The combination of CK and IL-10 further improved performance, achieving an AUC of 0.965 (95% CI: 0.938–0.993) (Fig. 3 A). In contrast, among children with adenovirus infection, CK and IL-10 showed markedly lower diagnostic accuracy. LDH emerged as the strongest single predictor in this group, with an AUC of 0.962 (95% CI: 0.925–0.999) (Fig. 3 B). Table 2 ROC analysis results of children with H1N1 and adenovirus infection Influenza A (H1N1) Adenovirus infection Variable AUC (95%CI) Cutoff Level Sensitivity Specificiy AUC (95%CI) Cutoff Level Sensitivity Specificiy CK 0.915(0.869–0.961) 137.0 0.862 0.840 0.679(0.560–0.791) 104.5 0.833 0.600 LDH 0.880(0.818–0.942) 250.5 0.750 1.000 0.962(0.925–0.999) 250.0 0.894 1.000 IL-10 0.922(0.870–0.974) 5.27 0.912 0.900 0.712(0.609–0.815) 4.2 0.600 0.800 CK༆IL-10 0.965(0.938–0.993) - 0.900 0.941 0.722(0.619–0.825) - 0.833 0.627 4. Discussion Our study demonstrates that the combination of CK and IL-10 offers superior diagnostic performance for distinguishing H1N1 from adenovirus infection, with an AUC of 0.965, sensitivity of 90.0%, and specificity of 94.1%. This finding provides clinicians with a rapid and reliable serological strategy during the critical early window before pathogen-specific results are available. Early and accurate differentiation of respiratory viral infections in children remains a significant challenge in clinical practic( 9 )e. Previous studies have largely focused on inflammatory markers such as CRP and PCT to differentiate bacterial from viral infections, but few have explored biomarkers specific to differentiating viral pathogens( 5 , 10 ). Our observation that CK levels are significantly higher in H1N1-infected children compared to those with adenovirus infection is novel and warrants further investigation. Influenza viruses, particularly H1N1, can bind to sialic acid receptors widely expressed in muscle tissues, potentially leading to direct viral invasion and myopathy. Additionally, the "cytokine storm" associated with severe H1N1 infections may exacerbate muscle damage through immune-mediated mechanisms. In contrast, adenoviruses primarily infect respiratory epithelial cells, causing less direct damage to muscle tissue( 11 , 12 ). This differential tropism likely underpins the observed differences in CK levels between the two groups( 13 ). IL-10, a key anti-inflammatory cytokine, showed markedly elevated levels in children with H1N1 compared to those with adenovirus infection. Existing literature indicates that IL-10 levels correlate positively with disease severity in severe H1N1 cases( 14 ). We hypothesize that the excessive inflammatory response triggered by H1N1 infection prompts a compensatory anti-inflammatory response, resulting in increased IL-10 secretion. While adenovirus infections also induce inflammation, characterized by elevated CRP and white blood cell counts, their immune response profiles appear to be dominated by other cytokines( 7 , 15 , 16 ). Notably, multivariate logistic regression analysis revealed that IL-10 had an odds ratio (OR) of 5.31 (95% CI: 1.19–23.78) in the H1N1 group, suggesting it not only serves as a marker of inflammation but may also play a crucial role in disease progression and modulation. In addition to CK and IL-10, our study found that LDH exhibited excellent diagnostic performance in adenovirus infection (AUC = 0.962). This is consistent with adenovirus's propensity to cause widespread epithelial cell damage, leading to LDH release. The E3-11.6K protein of adenovirus mediates host cell lysis, resulting in the release of intracellular LDH. In contrast, H1N1 virus primarily exits via budding, causing less direct cellular damage( 17 ).Compared to traditional pathogen-specific tests such as PCR, the CK-IL-10 combination offers several advantages: rapid turnaround time (within 2 hours), lower cost (approximately one-third of PCR testing), and reduced susceptibility to sample collection errors, thereby minimizing false-negative results. These features make it particularly suitable for use in primary care settings and during influenza outbreaks. This study has several limitations. First, as a single-center retrospective analysis, selection bias cannot be ruled out. Second, we did not include other common respiratory viruses (e.g., respiratory syncytial virus, parainfluenza virus) as controls, limiting the generalizability of our findings. Third, we did not explore the correlation between biomarker levels and disease severity or prognosis, nor did we assess their predictive value for complications. Lastly, external validation was not performed, so the generalizability of our results requires further confirmation. Future research should focus on multicenter prospective studies to validate the diagnostic efficacy of the CK-IL-10 model across different age groups and seasons. Integrating this model with clinical symptom scoring systems could enhance its utility. Additionally, exploring the molecular mechanisms underlying CK and IL-10 elevation in H1N1 infection could provide insights for targeted interventions. Advances in proteomics and metabolomics may further refine diagnostic accuracy by incorporating multiple biomarkers. In conclusion, the combination of CK and IL-10 provides a rapid and reliable diagnostic tool for early differentiation of H1N1 from adenovirus infection in children. This discovery not only enhances our understanding of the immunopathological mechanisms underlying different viral respiratory infections but also offers valuable clinical guidance for precise diagnosis and personalized treatment. During seasons when influenza and adenovirus co-circulate, this diagnostic model could serve as a critical adjunct for early intervention, ultimately improving patient outcomes. 5. Conclusion The combination of serum creatine kinase and interleukin-10 demonstrates high diagnostic accuracy for early differentiation of H1N1 from adenovirus infection in children, offering a practical tool to support timely clinical decision-making. Declarations Funding information: This research was funded by The Second Affiliated Hospital of Wenzhou Medical University (grant number: Y20210100). Author contributions: All authors have contributed to this manuscript and have agreed to its submission to the journal. Jiahao Wang and Xun Zhu attended the patient. Jiahao Wang and Xun Zhu wrote the manuscript. Deru Lei prepared figures and Tables. Yibing Zheng, Suzhen Pan, Weiyan Jiang analyzed data. Weiyan Jiang and Jiao Shao reviewed the manuscript. All authors read and approved the final manuscript. Consent to publication ： Not applicable. Conflict of interest: Authors state no conflict of interest. Data availability statement: All materials are owned by the authors and/or no permissions are required. If you need more details, please contact Jiao Shao (E-mail: [email protected] ). Ethics approval and consent to participate ： The research related to human use complied with all relevant national regulations and institutional policies in accordance with the tenets of the Helsinki Declaration and was approved by the authors’ institutional review board or equivalent committee(Ethics approval number: 2021-K-116-01). Acknowledgments: We thank the Second Affiliated Hospital of Wenzhou Medical University for providing the experimental place used in this study. References Al-Romaihi HE, Smatti MK, Al-Khatib HA, Coyle PV, Ganesan N, Nadeem S, et al. Molecular epidemiology of influenza, RSV, and other respiratory infections among children in Qatar: A six years report (2012–2017). Int J Infect Dis. 2020;95:133–41. Bi Y, Yang J, Wang L, Ran L, Gao GF. Ecology and evolution of avian influenza viruses. Curr Biol. 2024;34(15):R716–21. Jimenez-Juarez RN, Moreno-Espinosa S, Reyes-Lopez A, Parra-Ortega I, Laris-Gonzalez A, De la Rosa-Zamboni D et al. Impact of Influenza on Children in a Referral Hospital in Mexico City: Clinical Burden and Predictors of Mechanical Ventilation. Viruses. 2025;17(6). Dotan M, Zion E, Bilavsky E, Nahum E, Ben-Zvi H, Zalcman J, et al. Adenovirus can be a serious, life-threatening disease, even in previously healthy children. Acta Paediatr. 2022;111(3):614–9. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8548499","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":579428091,"identity":"78fb0ce1-9040-47c2-b517-23aa2db22ff7","order_by":0,"name":"Jiahao Wang","email":"","orcid":"","institution":"Wenzhou Medical University Second Affiliated Hospital","correspondingAuthor":false,"prefix":"","firstName":"Jiahao","middleName":"","lastName":"Wang","suffix":""},{"id":579428092,"identity":"201d3aeb-8944-4e9e-931d-e9077df2a444","order_by":1,"name":"Xun Zhu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA8UlEQVRIiWNgGAWjYBACPgbmBoYHYCbzAeMfFRJy8oS0sDEwNjAkQJgJxQxnLIwNG4jXwqPwmbGtIpHhACEt7AcbPyTUHE7czsDDuLlwnkQCYwPzw0c38GnhSWyWSDiWlrizgfew8cxtEnnsDGzGxjl4HZbYIJHAZpO44QBfmgHvNolixgYeNmm8WvgfNv9I+CcB1MJj/oN3jkRiwwFCWiQS24AIZAuPgTFvA1FaHrZZJPalGW84wJZgOOOYhLFhMwG/8PMnH77x4dth2Q0HmA8YfKipk5Nnb374GJ8WBJB/AGUwE6V8FIyCUTAKRgE+AABnSUu2WzEVTwAAAABJRU5ErkJggg==","orcid":"https://orcid.org/0009-0002-8427-2435","institution":"Wenzhou Medical University Second Affiliated Hospital","correspondingAuthor":true,"prefix":"","firstName":"Xun","middleName":"","lastName":"Zhu","suffix":""},{"id":579428093,"identity":"d47a4015-4561-43ca-a21c-424c121b38c6","order_by":2,"name":"Deru Lei","email":"","orcid":"","institution":"Wenzhou Medical University Second Affiliated Hospital","correspondingAuthor":false,"prefix":"","firstName":"Deru","middleName":"","lastName":"Lei","suffix":""},{"id":579428097,"identity":"e8220a5f-55f4-4fc1-88ed-e0cb41799c6c","order_by":3,"name":"Yibing Zheng","email":"","orcid":"","institution":"Wenzhou Medical University Second Affiliated Hospital","correspondingAuthor":false,"prefix":"","firstName":"Yibing","middleName":"","lastName":"Zheng","suffix":""},{"id":579428098,"identity":"ba15aa57-e44b-49cc-8877-f9db8399f7ae","order_by":4,"name":"Suzhen Pan","email":"","orcid":"","institution":"Wenzhou Medical University Second Affiliated Hospital","correspondingAuthor":false,"prefix":"","firstName":"Suzhen","middleName":"","lastName":"Pan","suffix":""},{"id":579428102,"identity":"b394c96e-a0a9-48ed-8015-842e44b91b0f","order_by":5,"name":"Xianming He","email":"","orcid":"","institution":"Wenzhou Medical University Second Affiliated Hospital","correspondingAuthor":false,"prefix":"","firstName":"Xianming","middleName":"","lastName":"He","suffix":""},{"id":579428105,"identity":"71091876-f4d5-46c4-8859-66edd8f2507b","order_by":6,"name":"Lei Shu","email":"","orcid":"","institution":"Wenzhou Medical University Second Affiliated Hospital","correspondingAuthor":false,"prefix":"","firstName":"Lei","middleName":"","lastName":"Shu","suffix":""},{"id":579428106,"identity":"0239dc12-02f6-4a7d-b303-b1d5c9f8b017","order_by":7,"name":"Weiyan Jiang","email":"","orcid":"","institution":"Wenzhou Medical University Second Affiliated Hospital","correspondingAuthor":false,"prefix":"","firstName":"Weiyan","middleName":"","lastName":"Jiang","suffix":""},{"id":579428107,"identity":"e60ae05c-d1bd-406f-ad5b-62b178f697da","order_by":8,"name":"Jiao Shao","email":"","orcid":"https://orcid.org/0009-0003-2333-2286","institution":"Wenzhou Medical University Second Affiliated Hospital","correspondingAuthor":false,"prefix":"","firstName":"Jiao","middleName":"","lastName":"Shao","suffix":""}],"badges":[],"createdAt":"2026-01-08 08:02:17","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8548499/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8548499/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":101435732,"identity":"005da16e-86b7-47f5-b2e5-285f0fb0cbc3","added_by":"auto","created_at":"2026-01-29 16:16:43","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":40676,"visible":true,"origin":"","legend":"\u003cp\u003eComparison of serological indicators among the influenza A group, adenovirus group, and healthy control group. (A) CK levels; (B) AST levels; (C) LDH levels; (D) IL-8 levels; (E) IIL-10 levels. *P \u0026lt; 0.05, **P \u0026lt; 0.01, ***P \u0026lt; 0.001, ****P \u0026lt; 0.0001.\u003c/p\u003e","description":"","filename":"Onlinefloatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-8548499/v1/10a592e59cf9b46c48fb2fb8.png"},{"id":101435734,"identity":"76454dde-18b1-406d-8f75-216241a25639","added_by":"auto","created_at":"2026-01-29 16:16:43","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":33842,"visible":true,"origin":"","legend":"\u003cp\u003e(A) Forest plots of univariate and multivariate logistic regression for children with H1N1. (B) Forest plots of univariate and multivariate logistic regression for children with adenovirus infection. The horizontal axis represents the odds ratio (OR, logarithmic scale), with dots indicating OR values and horizontal lines representing 95% confidence intervals (CI). Blue dots/lines indicate univariate analysis, while red dots/lines indicate multivariate analysis.\u003c/p\u003e","description":"","filename":"Onlinefloatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-8548499/v1/84b4a6f5cee2069e33fa28d5.png"},{"id":101435735,"identity":"d7e412cb-864d-47e2-aac5-42f3958e5307","added_by":"auto","created_at":"2026-01-29 16:16:43","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":36034,"visible":true,"origin":"","legend":"\u003cp\u003e(A) ROC curve analysis of serum indices in children with H1N1. (B) ROC curve analysis of serum indices in children with adenovirus infection.\u003c/p\u003e","description":"","filename":"Onlinefloatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-8548499/v1/61456b2cdbc818c5258f757b.png"},{"id":101880931,"identity":"6b238860-466d-44f2-bf18-6c0070b97632","added_by":"auto","created_at":"2026-02-04 15:08:03","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":897848,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8548499/v1/461548e8-05d1-4773-b7bc-111031ff1a62.pdf"}],"financialInterests":"","formattedTitle":"Diagnostic Utility of Creatine Kinase and IL-10 in Early Discrimination Between Pediatric Influenza A (H1N1) and Adenovirus Infections","fulltext":[{"header":"1. Background","content":"\u003cp\u003eInfluenza A (H1N1) is a highly transmissible acute respiratory infection that spreads rapidly and continues to pose a significant global public health burden(\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). Children are especially susceptible owing to incomplete respiratory development and relative immune immaturity(\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). Adenovirus, meanwhile, ranks among the most common viral causes of community-acquired pneumonia (CAP) in this age group and carries a high risk of severe outcomes(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). Untreated or delayed diagnosis can lead to progressive pneumonia and long-term sequelae\u0026mdash;including bronchiectasis, pulmonary fibrosis, and atelectasis\u0026mdash;jeopardizing both short- and long-term health(\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eTimely differentiation between these two infections is clinically crucial. Early pathogen identification allows for targeted antiviral use, which can shorten illness duration and reduce complications(\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). Yet during overlapping seasonal peaks, H1N1 and adenovirus present with strikingly similar signs and symptoms. Young children often cannot articulate their complaints clearly, further complicating clinical judgment(\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e).PCR remains the diagnostic gold standard for both viruses, but its practical utility in early triage is limited. Turnaround times are often too long for acute decision-making, results depend heavily on sampling quality, and false negatives remain a concern(\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eEfforts have therefore turned to serum biomarkers as potential aids for rapid discrimination. Traditional markers like white blood cell count and C-reactive protein (CRP) help distinguish bacterial from viral etiologies but lack specificity between different viruses. Although elevated CRP has been linked to bacterial co-infection in H1N1 cases, evidence is inconsistent(\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). Procalcitonin (PCT) typically stays low in pure viral infections but rises in bacterial, fungal, or parasitic disease; some studies suggest it may help rule out bacterial superinfection in influenza(\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). However, most data come from adult or critically ill populations\u0026mdash;robust pediatric evidence is still lacking.\u003c/p\u003e \u003cp\u003eTo address this gap, we retrospectively analyzed data from 307 children with confirmed H1N1 infection and 118 with adenovirus infection diagnosed during the same outbreak period in 2024. Focusing on cardiac enzymes and cytokines, we specifically evaluated the diagnostic performance of creatine kinase (CK) and interleukin-10 (IL-10) in distinguishing these two entities. Our goal was to identify readily measurable, early-phase biomarkers that could support more precise and timely clinical decisions in pediatric practice.\u003c/p\u003e"},{"header":"2. Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Study Population\u003c/h2\u003e \u003cp\u003eThis retrospective study included 307 children diagnosed with H1N1 and 118 with adenovirus infection at the Second Affiliated Hospital of Wenzhou Medical University between May and September 2024. All cases were confirmed through multiplex PCR testing of respiratory secretions. The study was approved by the Ethics Committee of the hospital, adhering to the principles outlined in the Declaration of Helsinki, and informed consent was obtained from all guardians.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Inclusion and Exclusion Criteria\u003c/h2\u003e \u003cp\u003eDiagnostic Criteria:\u003c/p\u003e \u003cp\u003eH1N1: Confirmed according to the Expert Consensus on Diagnosis and Treatment of Influenza in Children (2015 Edition) by the Pediatric Respiratory Group of the Chinese Medical Association. Adenovirus: Diagnosed based on criteria set forth in the Expert Consensus on Integrated Traditional Chinese and Western Medicine Diagnosis and Treatment of Viral Pneumonia in Children (2019 Edition).\u003c/p\u003e \u003cp\u003eInclusion Criteria:1) Age between 1 month and 14 years.2) Complete clinical and laboratory data available.3) First visit without prior antiviral or corticosteroid treatment.\u003c/p\u003e \u003cp\u003eExclusion Criteria:1) Co-infection with bacteria, mycoplasma, or fungi.2) History of severe chronic heart, liver, or kidney disease or immunodeficiency.3) Previous history of muscle diseases or hemolytic disorders.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Methods\u003c/h2\u003e \u003cdiv id=\"Sec6\" class=\"Section3\"\u003e \u003ch2\u003e2.3.1 Laboratory Testing\u003c/h2\u003e \u003cp\u003eVenous blood samples were collected within 24 hours of admission. CK, LDH, and AST levels were measured using a Beckman AU5830 biochemical analyzer. Cytokine levels (IL-8, IL-10) were detected via flow cytometry (FACS Canto, provided by Jiangxi Saige Biotechnology Co., Ltd.). All blood tests were performed within 48 hours of fever onset. Control samples were collected from healthy children during outpatient visits or health check-ups.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section3\"\u003e \u003ch2\u003e2.3.2 Detection of H1N1 and Adenovirus\u003c/h2\u003e \u003cp\u003eNasopharyngeal swabs or sputum samples were collected upon admission. H1N1 diagnosis was confirmed using real-time fluorescent PCR (ABI7500 Real-Time PCR System, reagents from Jiangsu Success Bio-Tech Co., Ltd.). Adenovirus detection utilized RT-PCR coupled with capillary electrophoresis (Eastwin ETC811 Gene Amplifier and 3500Dx Genetic Analyzer, reagents from Ningbo HealthGene Technologies Co., Ltd.).\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e2.4 Statistical Analysis\u003c/h2\u003e \u003cp\u003eData were analyzed using SPSS 21.0 software. Continuous variables were tested for normality and presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD). One-way ANOVA was used for comparisons among multiple groups, with LSD test for homogeneous variances and Dunnett's T3 for heterogeneous variances. Univariate logistic regression assessed the diagnostic performance of each biomarker (CK, AST, LDH, IL-8, IL-10). Multivariate logistic regression models were constructed using forward stepwise selection with P\u0026thinsp;\u0026lt;\u0026thinsp;0.10. Model performance was evaluated by calculating the area under the receiver operating characteristic curve (AUC), and Hanley and McNeil methods compared AUC values. Optimal ROC cut-off points were determined using Youden\u0026rsquo;s index (sensitivity\u0026thinsp;+\u0026thinsp;specificity \u0026minus;\u0026thinsp;1). Statistical significance was set at P\u0026thinsp;\u0026lt;\u0026thinsp;0.05 (ns: not significant; * P\u0026thinsp;\u0026lt;\u0026thinsp;0.05; ** P\u0026thinsp;\u0026lt;\u0026thinsp;0.01; *** P\u0026thinsp;\u0026lt;\u0026thinsp;0.001; **** P\u0026thinsp;\u0026lt;\u0026thinsp;0.0001).\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Clinical and Laboratory Characteristics of the Study Population\u003c/h2\u003e \u003cp\u003eA total of 427 children were included: 310 with H1N1 and 117 with adenovirus infection. Baseline and laboratory characteristics are summarized in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Children with H1N1 were significantly older than those with adenovirus infection (5.66\u0026thinsp;\u0026plusmn;\u0026thinsp;3.44 vs. 3.83\u0026thinsp;\u0026plusmn;\u0026thinsp;1.95 years; t\u0026thinsp;=\u0026thinsp;6.88, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Inflammatory markers differed markedly between groups. CRP and white blood cell count (WBC) were both higher in the adenovirus group (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001 for both). Differential leukocyte counts showed a higher neutrophil percentage in H1N1 cases (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), whereas lymphocyte and monocyte percentages were elevated in adenovirus infection (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001 and P\u0026thinsp;=\u0026thinsp;0.028, respectively). No significant differences were observed between groups in sex distribution, serum uric acid, or PCT levels (P\u0026thinsp;\u0026gt;\u0026thinsp;0.05 for all).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparison of clinical features between influenza A group and adenovirus group\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal (n\u0026thinsp;=\u0026thinsp;427)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eH1N1\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;310)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAdenovirus\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;117)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eStatistic\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge, Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.16\u0026thinsp;\u0026plusmn;\u0026thinsp;3.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.66\u0026thinsp;\u0026plusmn;\u0026thinsp;3.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.83\u0026thinsp;\u0026plusmn;\u0026thinsp;1.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003et\u0026thinsp;=\u0026thinsp;6.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex, n(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eχ\u0026sup2;=0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.929\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e181 (42.39)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e131 (42.26)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e50 (42.74)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e246 (57.61)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e179 (57.74)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e67 (57.26)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCRP, Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17.02\u0026thinsp;\u0026plusmn;\u0026thinsp;21.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10.97\u0026thinsp;\u0026plusmn;\u0026thinsp;14.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e33.01\u0026thinsp;\u0026plusmn;\u0026thinsp;28.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003et=-7.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePCT, Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.65\u0026thinsp;\u0026plusmn;\u0026thinsp;1.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.73\u0026thinsp;\u0026plusmn;\u0026thinsp;1.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.57\u0026thinsp;\u0026plusmn;\u0026thinsp;0.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003et\u0026thinsp;=\u0026thinsp;0.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.527\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWBC, Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.30\u0026thinsp;\u0026plusmn;\u0026thinsp;3.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.68\u0026thinsp;\u0026plusmn;\u0026thinsp;3.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10.02\u0026thinsp;\u0026plusmn;\u0026thinsp;4.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003et=-5.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNeutrophils, Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.66\u0026thinsp;\u0026plusmn;\u0026thinsp;0.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.68\u0026thinsp;\u0026plusmn;\u0026thinsp;0.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.61\u0026thinsp;\u0026plusmn;\u0026thinsp;0.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003et\u0026thinsp;=\u0026thinsp;3.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLymphocyte, Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.24\u0026thinsp;\u0026plusmn;\u0026thinsp;0.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.22\u0026thinsp;\u0026plusmn;\u0026thinsp;0.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.28\u0026thinsp;\u0026plusmn;\u0026thinsp;0.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003et=-3.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMonocyte, Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.09\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.09\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.10\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003et=-2.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.028\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUric acid, Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e262.35\u0026thinsp;\u0026plusmn;\u0026thinsp;76.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e265.61\u0026thinsp;\u0026plusmn;\u0026thinsp;82.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e258.63\u0026thinsp;\u0026plusmn;\u0026thinsp;69.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003et\u0026thinsp;=\u0026thinsp;0.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.593\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003et: t-test, χ\u0026sup2;: Chi-square test ;SD: standard deviation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Comparison of Serum Inflammatory Cytokines and Tissue Injury Markers Among Groups\u003c/h2\u003e \u003cp\u003eSerum levels of inflammatory cytokines and tissue injury markers differed significantly across healthy controls, children with H1N1, and those with adenovirus infection (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Compared with healthy controls, the H1N1 group showed markedly higher levels of CK, aspartate aminotransferase (AST), and LDH) (P\u0026thinsp;\u0026lt;\u0026thinsp;0.0001 for all). Levels of interleukin-8 (IL-8) and interleukin-10 (IL-10) were also significantly elevated in the H1N1 group versus controls (P\u0026thinsp;\u0026lt;\u0026thinsp;0.0001 for both).When directly compared with the adenovirus group, children with H1N1 exhibited significantly higher concentrations of IL-8, IL-10, CK, AST, and LDH (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001 for all comparisons).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e3.3 Independent Predictive Value of CK and IL-10 in H1N1 Versus Adenovirus Infection\u003c/h2\u003e \u003cp\u003eUnivariate logistic regression analysis in children with H1N1 identified LDH, CK, AST, IL-8, and IL-10 as significantly associated with the outcome. Specifically, CK (OR\u0026thinsp;=\u0026thinsp;1.07, 95% CI: 1.05\u0026ndash;1.09) and IL-10 (OR\u0026thinsp;=\u0026thinsp;2.15, 95% CI: 1.65\u0026ndash;2.82) showed the strongest associations. After multivariate adjustment, CK (OR\u0026thinsp;=\u0026thinsp;1.13, 95% CI: 1.01\u0026ndash;1.27, P\u0026thinsp;=\u0026thinsp;0.037) and IL-10 (OR\u0026thinsp;=\u0026thinsp;5.31, 95% CI: 1.19\u0026ndash;23.78, P\u0026thinsp;=\u0026thinsp;0.029) remained independent predictors (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA).In children with adenovirus infection, univariate analysis also revealed significant associations between LDH, CK, AST, IL-8, and IL-10 and the outcome. Among these, LDH (OR\u0026thinsp;=\u0026thinsp;1.14, 95% CI: 1.07\u0026ndash;1.22) and IL-10 (OR\u0026thinsp;=\u0026thinsp;1.41, 95% CI: 1.10\u0026ndash;1.81) were most strongly linked to increased risk. Multivariate analysis confirmed that LDH (OR\u0026thinsp;=\u0026thinsp;1.19, 95% CI: 1.07\u0026ndash;1.32, P\u0026thinsp;=\u0026thinsp;0.001) and IL-10 (OR\u0026thinsp;=\u0026thinsp;2.91, 95% CI: 1.05\u0026ndash;8.04, P\u0026thinsp;=\u0026thinsp;0.039) remained statistically significant, whereas CK and other markers lost significance after adjustment (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB).Comparing the two groups, CK and IL-10 demonstrated stronger predictive power in distinguishing H1N1 from adenovirus infection. Both CK and IL-10 were independent predictors in H1N1 cases, with IL-10 showing the highest effect size. In contrast, CK did not retain independent significance in adenovirus infections. Therefore, the combination of CK and IL-10 offers a valuable tool for early differentiation between these two conditions, aiding rapid clinical diagnosis and targeted management.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e3.4 Diagnostic Performance of Serum Biomarkers for Differentiating H1N1 from Adenovirus Infection\u003c/h2\u003e \u003cp\u003eReceiver operating characteristic (ROC) curve analysis was performed to assess the diagnostic accuracy of serum biomarkers in distinguishing H1N1 from adenovirus infection (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). In children with H1N1, both CK and interleukin-10 (IL-10) demonstrated high discriminative ability. CK yielded an area under the curve (AUC) of 0.915 (95% CI: 0.869\u0026ndash;0.961), with an optimal cutoff of 137.0 U/L. The combination of CK and IL-10 further improved performance, achieving an AUC of 0.965 (95% CI: 0.938\u0026ndash;0.993) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA). In contrast, among children with adenovirus infection, CK and IL-10 showed markedly lower diagnostic accuracy. LDH emerged as the strongest single predictor in this group, with an AUC of 0.962 (95% CI: 0.925\u0026ndash;0.999) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eROC analysis results of children with H1N1 and adenovirus infection\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e \u003cp\u003eInfluenza A (H1N1)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c9\" namest=\"c6\"\u003e \u003cp\u003eAdenovirus infection\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAUC (95%CI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCutoff Level\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSensitivity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSpecificiy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eAUC (95%CI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eCutoff Level\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eSensitivity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eSpecificiy\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCK\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.915(0.869\u0026ndash;0.961)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e137.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.862\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.840\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.679(0.560\u0026ndash;0.791)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e104.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.833\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.600\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLDH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.880(0.818\u0026ndash;0.942)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e250.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.750\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.962(0.925\u0026ndash;0.999)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e250.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.894\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIL-10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.922(0.870\u0026ndash;0.974)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.912\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.900\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.712(0.609\u0026ndash;0.815)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.600\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.800\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCK༆IL-10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.965(0.938\u0026ndash;0.993)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.900\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.941\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.722(0.619\u0026ndash;0.825)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.833\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.627\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eOur study demonstrates that the combination of CK and IL-10 offers superior diagnostic performance for distinguishing H1N1 from adenovirus infection, with an AUC of 0.965, sensitivity of 90.0%, and specificity of 94.1%. This finding provides clinicians with a rapid and reliable serological strategy during the critical early window before pathogen-specific results are available. Early and accurate differentiation of respiratory viral infections in children remains a significant challenge in clinical practic(\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e)e. Previous studies have largely focused on inflammatory markers such as CRP and PCT to differentiate bacterial from viral infections, but few have explored biomarkers specific to differentiating viral pathogens(\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). Our observation that CK levels are significantly higher in H1N1-infected children compared to those with adenovirus infection is novel and warrants further investigation.\u003c/p\u003e \u003cp\u003eInfluenza viruses, particularly H1N1, can bind to sialic acid receptors widely expressed in muscle tissues, potentially leading to direct viral invasion and myopathy. Additionally, the \"cytokine storm\" associated with severe H1N1 infections may exacerbate muscle damage through immune-mediated mechanisms. In contrast, adenoviruses primarily infect respiratory epithelial cells, causing less direct damage to muscle tissue(\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). This differential tropism likely underpins the observed differences in CK levels between the two groups(\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIL-10, a key anti-inflammatory cytokine, showed markedly elevated levels in children with H1N1 compared to those with adenovirus infection. Existing literature indicates that IL-10 levels correlate positively with disease severity in severe H1N1 cases(\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). We hypothesize that the excessive inflammatory response triggered by H1N1 infection prompts a compensatory anti-inflammatory response, resulting in increased IL-10 secretion. While adenovirus infections also induce inflammation, characterized by elevated CRP and white blood cell counts, their immune response profiles appear to be dominated by other cytokines(\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). Notably, multivariate logistic regression analysis revealed that IL-10 had an odds ratio (OR) of 5.31 (95% CI: 1.19\u0026ndash;23.78) in the H1N1 group, suggesting it not only serves as a marker of inflammation but may also play a crucial role in disease progression and modulation.\u003c/p\u003e \u003cp\u003eIn addition to CK and IL-10, our study found that LDH exhibited excellent diagnostic performance in adenovirus infection (AUC\u0026thinsp;=\u0026thinsp;0.962). This is consistent with adenovirus's propensity to cause widespread epithelial cell damage, leading to LDH release. The E3-11.6K protein of adenovirus mediates host cell lysis, resulting in the release of intracellular LDH. In contrast, H1N1 virus primarily exits via budding, causing less direct cellular damage(\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e).Compared to traditional pathogen-specific tests such as PCR, the CK-IL-10 combination offers several advantages: rapid turnaround time (within 2 hours), lower cost (approximately one-third of PCR testing), and reduced susceptibility to sample collection errors, thereby minimizing false-negative results. These features make it particularly suitable for use in primary care settings and during influenza outbreaks.\u003c/p\u003e \u003cp\u003eThis study has several limitations. First, as a single-center retrospective analysis, selection bias cannot be ruled out. Second, we did not include other common respiratory viruses (e.g., respiratory syncytial virus, parainfluenza virus) as controls, limiting the generalizability of our findings. Third, we did not explore the correlation between biomarker levels and disease severity or prognosis, nor did we assess their predictive value for complications. Lastly, external validation was not performed, so the generalizability of our results requires further confirmation. Future research should focus on multicenter prospective studies to validate the diagnostic efficacy of the CK-IL-10 model across different age groups and seasons. Integrating this model with clinical symptom scoring systems could enhance its utility. Additionally, exploring the molecular mechanisms underlying CK and IL-10 elevation in H1N1 infection could provide insights for targeted interventions. Advances in proteomics and metabolomics may further refine diagnostic accuracy by incorporating multiple biomarkers.\u003c/p\u003e \u003cp\u003eIn conclusion, the combination of CK and IL-10 provides a rapid and reliable diagnostic tool for early differentiation of H1N1 from adenovirus infection in children. This discovery not only enhances our understanding of the immunopathological mechanisms underlying different viral respiratory infections but also offers valuable clinical guidance for precise diagnosis and personalized treatment. During seasons when influenza and adenovirus co-circulate, this diagnostic model could serve as a critical adjunct for early intervention, ultimately improving patient outcomes.\u003c/p\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eThe combination of serum creatine kinase and interleukin-10 demonstrates high diagnostic accuracy for early differentiation of H1N1 from adenovirus infection in children, offering a practical tool to support timely clinical decision-making.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eFunding information:\u003c/strong\u003e This research was funded by\u0026nbsp;The Second Affiliated Hospital of Wenzhou Medical University\u0026nbsp;(grant number: Y20210100).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions:\u003c/strong\u003e All authors have contributed to this manuscript and have agreed to its submission to the journal.\u0026nbsp;Jiahao Wang and Xun Zhu\u0026nbsp;attended the patient.\u0026nbsp;Jiahao Wang\u0026nbsp;and\u0026nbsp;Xun Zhu\u0026nbsp;wrote the manuscript.\u0026nbsp;Deru Lei\u0026nbsp;prepared figures and Tables.\u0026nbsp;Yibing Zheng, Suzhen Pan, Weiyan Jiang\u0026nbsp;analyzed data.\u0026nbsp;Weiyan Jiang and Jiao Shao\u0026nbsp;reviewed the manuscript.\u0026nbsp;All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to publication\u003c/strong\u003e\u003cstrong\u003e：\u003c/strong\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interest:\u0026nbsp;\u003c/strong\u003eAuthors state no conflict of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability statement:\u003c/strong\u003e All materials are owned by the authors and/or no permissions are required. If you need more details, please contact\u0026nbsp;Jiao Shao\u0026nbsp;(E-mail:\u0026nbsp;[email protected]).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003cstrong\u003e：\u003c/strong\u003eThe research related to human use complied with all relevant national regulations and institutional policies in accordance with the tenets of the Helsinki Declaration and was approved by the authors\u0026rsquo;\u0026nbsp;institutional review board or equivalent committee(Ethics approval number: 2021-K-116-01).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments:\u0026nbsp;\u003c/strong\u003eWe thank the Second Affiliated Hospital of Wenzhou Medical University for providing the experimental place used in this study.\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAl-Romaihi HE, Smatti MK, Al-Khatib HA, Coyle PV, Ganesan N, Nadeem S, et al. Molecular epidemiology of influenza, RSV, and other respiratory infections among children in Qatar: A six years report (2012\u0026ndash;2017). Int J Infect Dis. 2020;95:133\u0026ndash;41.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBi Y, Yang J, Wang L, Ran L, Gao GF. Ecology and evolution of avian influenza viruses. Curr Biol. 2024;34(15):R716\u0026ndash;21.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJimenez-Juarez RN, Moreno-Espinosa S, Reyes-Lopez A, Parra-Ortega I, Laris-Gonzalez A, De la Rosa-Zamboni D et al. Impact of Influenza on Children in a Referral Hospital in Mexico City: Clinical Burden and Predictors of Mechanical Ventilation. Viruses. 2025;17(6).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDotan M, Zion E, Bilavsky E, Nahum E, Ben-Zvi H, Zalcman J, et al. Adenovirus can be a serious, life-threatening disease, even in previously healthy children. Acta Paediatr. 2022;111(3):614\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLiu M, Han Y, Sun J, Wei X, Zhao X, Wang B, et al. Comparison of the Epidemiological and Clinical Characteristics of Hospitalized Children With Pneumonia Caused by SARS-CoV-2, Influenza A, and Human Adenoviruses: A Case-Control Study. Clin Pediatr (Phila). 2022;61(2):150\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhang R, Wang H, Tian S, Deng J. Adenovirus viremia may predict adenovirus pneumonia severity in immunocompetent children. BMC Infect Dis. 2021;21(1):213.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAppenzeller C, Ammann RA, Duppenthaler A, Gorgievski-Hrisoho M, Aebi C. Serum C-reactive protein in children with adenovirus infection. Swiss Med Wkly. 2002;132(25\u0026ndash;26):345\u0026ndash;50.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eXu H, Chen W, Lai Q, Chen Y, Guo Y, Chen J et al. Clinical Characteristics of Adenovirus Pneumonia in Children. Pathogens. 2025;14(11).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSaville TJ, Colton H, Jarju S, Armitage EP, Drammeh S, Tazzyman S, et al. Microfluidic qPCR for detection of 21 common respiratory viruses in children with influenza-like illness. Sci Rep. 2024;14(1):28292.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHuang W, Niu W, Chen H, Jiang W, Fu Y, Li X, et al. Development of a nomogram for severe influenza in previously healthy children: a retrospective cohort study. J Int Med Res. 2023;51(2):3000605231153768.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eServidei S, Miranda AF, Gamboa ET. Infectivity of influenza B virus in cultured human muscle. Acta Neuropathol. 1987;73(1):67\u0026ndash;76.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSwaringen JC, Seiler JG 3rd, Bruce RW. Jr. Influenza A induced rhabdomyolysis resulting in extensive compartment syndrome. Clin Orthop Relat Res. 2000(375):243\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKoren MA, Arnold JC, Fairchok MP, Lalani T, Danaher PJ, Schofield CM, et al. Type-specific clinical characteristics of adenovirus-associated influenza-like illness at five US military medical centers, 2009\u0026ndash;2014. Influenza Other Respir Viruses. 2016;10(5):414\u0026ndash;20.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWest EE, Merle NS, Kaminski MM, Palacios G, Kumar D, Wang L, et al. Loss of CD4(+) T cell-intrinsic arginase 1 accelerates Th1 response kinetics and reduces lung pathology during influenza infection. Immunity. 2023;56(9):2036\u0026ndash;53. e12.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWang QY, Yuan L, Lin JY, Zhuo ZQ, Wang YM, Li SS, et al. Clinical characteristics of severe influenza virus-associated pneumonia complicated with bacterial infection in children: a retrospective analysis. BMC Infect Dis. 2023;23(1):545.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKulkarni U, Karsten CM, Kohler T, Hammerschmidt S, Bommert K, Tiburzy B, et al. IL-10 mediates plasmacytosis-associated immunodeficiency by inhibiting complement-mediated neutrophil migration. J Allergy Clin Immunol. 2016;137(5):1487\u0026ndash;e976.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLiu D, Wang C, Chen Y, Huang X, Wen Y, Duan S, et al. Protein Kinase C Epsilon Overexpression Protects the Heart Against Doxorubicin-Induced Cardiotoxicity Via Activating SIRT1. Cardiovasc Toxicol. 2025;25(6):915\u0026ndash;28.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"italian-journal-of-pediatrics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"itjp","sideBox":"Learn more about [Italian Journal of Pediatrics](http://ijponline.biomedcentral.com)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/ITJP/default.aspx","title":"Italian Journal of Pediatrics","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Influenza A (H1N1), Adenovirus infection, Creatine kinase, Interleukin-10, Early diagnosis","lastPublishedDoi":"10.21203/rs.3.rs-8548499/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8548499/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eDifferentiating influenza, A (H1N1) from adenovirus infection in children remains challenging during concurrent outbreaks due to overlapping clinical features. Rapid, reliable biomarkers are needed to guide early management.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003e We retrospectively reviewed clinical and laboratory data from 307 children with laboratory-confirmed influenza A (H1N1) and 118 with adenovirus infection admitted to the Second Affiliated Hospital of Wenzhou Medical University between May and September 2024. Demographics and serum levels of creatine kinase (CK), lactate dehydrogenase (LDH), aspartate aminotransferase (AST), interleukin-8 (IL-8), and interleukin-10 (IL-10) were compared. Univariate and multivariate logistic regression models were used to assess discriminative performance. Diagnostic accuracy was evaluated using area under the receiver operating characteristic curve (AUC), with optimal cut-offs determined by Youden\u0026rsquo;s index.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eChildren with H1N1 were older than those with adenovirus infection (5.67\u0026thinsp;\u0026plusmn;\u0026thinsp;3.45 vs. 3.82\u0026thinsp;\u0026plusmn;\u0026thinsp;1.94 years; P\u0026thinsp;\u0026lt;\u0026thinsp;0.05); sex distribution did not differ significantly. Among single markers, IL-10 showed the highest AUC for identifying H1N1 (0.922; 95% CI: 0.870\u0026ndash;0.974), followed by CK (0.915; 0.869\u0026ndash;0.961) and LDH (0.880; 0.818\u0026ndash;0.942). A combined model of CK and IL-10 yielded an AUC of 0.965 (95% CI: 0.938\u0026ndash;0.993), with sensitivity of 90.0% and specificity of 94.1%, outperforming any individual marker.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eThe combination of serum CK and IL-10 demonstrates high diagnostic accuracy for early differentiation of influenza A (H1N1) from adenovirus infection in children. This dual-marker approach may support timely clinical decision-making and pathogen-directed management in acute respiratory illness.\u003c/p\u003e","manuscriptTitle":"Diagnostic Utility of Creatine Kinase and IL-10 in Early Discrimination Between Pediatric Influenza A (H1N1) and Adenovirus Infections","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-01-29 16:16:38","doi":"10.21203/rs.3.rs-8548499/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"","date":"2026-01-23T14:59:33+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-01-23T14:42:15+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-01-23T04:45:22+00:00","index":"","fulltext":""},{"type":"submitted","content":"Italian Journal of Pediatrics","date":"2026-01-21T03:07:42+00:00","index":"","fulltext":""},{"type":"decision","content":"Major revision","date":"2026-01-15T00:05:04+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"italian-journal-of-pediatrics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"itjp","sideBox":"Learn more about [Italian Journal of Pediatrics](http://ijponline.biomedcentral.com)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/ITJP/default.aspx","title":"Italian Journal of Pediatrics","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"ff0fa8ab-cc0d-4864-a99e-e7f392280211","owner":[],"postedDate":"January 29th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"in-revision","subjectAreas":[],"tags":[],"updatedAt":"2026-03-02T13:47:32+00:00","versionOfRecord":[],"versionCreatedAt":"2026-01-29 16:16:38","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8548499","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8548499","identity":"rs-8548499","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}