Epidemiology, Bacterial Coinfection Risk Factors, and Inflammatory Markers in Children with RSV, AdV, and hMPV Pneumonia in Zunyi, China

Epidemiology, Bacterial Coinfection Risk Factors, and Inflammatory Markers in Children with RSV, AdV, and hMPV Pneumonia in Zunyi, China | 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 Epidemiology, Bacterial Coinfection Risk Factors, and Inflammatory Markers in Children with RSV, AdV, and hMPV Pneumonia in Zunyi, China Dewei Zhou, Kaiting Tang, Yu Zhao, Huan Yue, Jingjing Ma, He Zha This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8884580/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 18 You are reading this latest preprint version Abstract Background Community acquired pneumonia (CAP) is a major cause of illness and death in children under five worldwide. This study characterized the epidemiology of RSV/AdV/hMPV associated CAP in Zunyi children and identified bacterial co-infection risk factors, to provide a scientific basis for individualized pediatric CAP management in this region. Methods A retrospective analysis of clinical data from 2315 children with CAP admitted to Zunyi First People's Hospital (Third Affiliated Hospital of Zunyi Medical University) between January and December 2025 was performed. Univariate and multivariate logistic regression analyses identified risk factors for bacterial co-infection, and receiver operating characteristic (ROC) curve analysis evaluated the predictive value of inflammatory markers. Results A total of 2,315 children with CAP were enrolled. The RSV positivity rate (22.76%) was significantly higher than that for AdV (9.72%) and hMPV (9.84%, p <0.05). Single virus pneumonia (SVP) and viral and bacterial co-infected pneumonia (VBCP) were the main types for all three viruses. RSV infection peaked in autumn and winter, with the highest positivity in children under 1 year. AdV infection occurred year-round and was most common in children aged 1–5 years. hMPV infection was concentrated from January to April, predominantly in children aged 1–3 years. Children with RSV pneumonia were the youngest and had obvious wheezing. Children with AdV pneumonia had the highest rates of high fever, tonsillar enlargement, and sepsis, the shortest hospital stay, and significantly higher IL-6 and WBC levels. Multivariate logistic regression showed that elevated IL-6 was an independent risk factor for RSV-associated VBCP (OR=1.031, 95% CI: 1.011–1.052, P =0.002), AdV-associated VBCP (OR=1.035, 95% CI: 1.015–1.056, P =0.001), and hMPV-associated VBCP (OR=1.026, 95% CI: 1.006–1.046, P =0.009). For RSV-associated VBCP, WBC was an additional independent risk factor (OR=1.062, 95% CI: 1.005–1.122, P =0.032). No other indicators exhibited independent predictive value. ROC curve analysis demonstrated that combined inflammatory marker detection had predictive value for VBCP. Conclusions RSV, AdV, and hMPV cause different patterns of illness and inflammation in children with pneumonia in Zunyi. When these viruses co-occur with bacteria, the disease becomes more severe, and the risks vary by virus. High IL-6 levels are a shared, early warning sign of viral and bacterial co-infection for all three viruses. Respiratory Syncytial Virus Adenovirus Human Metapneumovirus Community Acquired Pneumonia Risk factors Figures Figure 1 Figure 2 Background Community-acquired pneumonia (CAP) is a leading cause of morbidity and mortality in children under 5 worldwide. Viruses are major etiological agents, and the pathogen profile is complex [ 1 , 2 ]. RSV, adenovirus, and hMPV are the most common viral pathogens of childhood CAP [ 3 ]. Clinically, these viruses induce primary pneumonia. They also cause respiratory mucosal damage and local immune dysfunction, predisposing children to secondary bacterial infections and viral-bacterial coinfection pneumonia (VBCP) [ 4 , 5 ]. VBCP exacerbates inflammation, leading to more severe illness, prolonged disease, and increased severity rates [ 6 – 8 ]. The epidemiology of respiratory pathogens varies by country and region, influenced by geographic location, humidity, and other factors [ 9 – 11 ]. Research often focuses on single-viral pneumonia (SVP) or nationwide analyses [ 3 , 12 , 13 ]. Few studies address VBCP or compare CAP caused by RSV, AdV, and hMPV. In southwest China, particularly Zunyi, the pathogen spectrum and disease burden of childhood respiratory infections may vary regionally due to unique geographic, climatic, and population density conditions. To date, basic data on the age distribution, seasonal epidemic patterns, as well as positivity rates of RSV-, AdV-, and hMPV-induced pneumonia in Zunyi’s children remain lacking. Furthermore, the risk factors for bacterial co-infection with these three viruses are not clearly defined, and targeted early identification indicators are scarce in clinical practice. Consequently, regional, multi-virus comparative studies specific to Zunyi are limited, failing to meet the real needs of local clinical diagnosis, treatment, and prevention. Although inflammatory markers have gained widespread attention for their diagnostic value in viral-bacterial co-infections, differences in their expression levels and comparative diagnostic potency across distinct viral infection contexts require additional confirmation. This study aims to systematically analyze the epidemiological characteristics of RSV-, AdV-, and hMPV-induced pneumonia in Zunyi, identify independent risk factors for bacterial co-infection, and compare differences in inflammatory marker expression between SVP and VBCP. The findings are intended to provide a scientific basis for precise prevention and control of pediatric viral pneumonia, early identification of bacterial co-infections, and personalized treatment in Zunyi. Materials and Methods 1. Materials A retrospective analysis of clinical data from 2315 children aged <5 years with CAP hospitalized in the Department of Pediatric Respiratory Medicine at Zunyi First People's Hospital (The Third Affiliated Hospital of Zunyi Medical University) from January to December 2025 was performed. The Ethics Review Committee has waived the requirement for informed consent because this is a retrospective analysis, all patient information was anonymized, and there were no additional interventions or risks to participants in this study. This study was conducted in full accordance with the Declaration of Helsinki. 2. Methods 2.1 Inclusion and Exclusion Criteria Inclusion criteria: ① Diagnosis of pneumonia per the 2023 pediatric guidelines, with pulmonary moist rales and radiological evidence; cases classified as severe or non-severe per guideline criteria. ② Complete clinical data available. ③Eligible participants were children aged between 29 days and 5 years at the time of hospital admission. ④Biological samples collected within 24 hours of admission for pathogen and inflammatory marker testing. Exclusion criteria: ① Presence of severe comorbidities or immunodeficiency. ② Diagnosis of pneumonia secondary to bronchopulmonary dysplasia, respiratory tract malformations, or foreign body aspiration. 2.2 Grouping Patients were grouped via two approaches: 1. Based on throat swab etiological test results at admission: ① SVP group: Detection of only one target virus (RSV, AdV, or hMPV) without concurrent bacteria or other pathogens; ② VBCP group: Detection of one aforementioned target virus plus one or more bacterial pathogens. 2. Based on disease severity, children were divided into severe and non‑severe groups. Severe pneumonia was defined as meeting any of the following criteria: poor general condition, impaired consciousness, hypoxemia, hyperpyrexia or persistent fever >5 days, dehydration or refusal to eat, or chest X‑ray/CT findings consistent with severe pneumonia. 2.3 Etiological Detection Total nucleic acids were extracted from samples using a Sansure Biotech nucleic acid extraction kit (magnetic bead-based). Multiplex nucleic acid detection kits from the same manufacturer were used to detect 8 respiratory pathogens (AdV, RSV, hMPV, parainfluenza virus types 1/2/3, influenza A/B viruses) and Mycoplasma pneumoniae. All assays were performed on an Applied Biosystems Q5 real‑time fluorescent quantitative PCR system, strictly following the manufacturer’s instructions. Bacterial culture was performed using sputum samples. 2.4 Inflammation Marker Detection Serum concentrations of cytokines (IL-2, IL-4, IL-6, IL-10, IL-17A, TNF-α, IFN-γ) were measured using a BD FcapArray3 flow cytometer. White blood cell (WBC) count and high-sensitivity C-reactive protein (hs-CRP) levels were detected with a Sysmex automated hematology analyzer and specific protein analyzer, respectively. Statistical analysis Categorical data were presented as the number of cases and corresponding percentages. Comparisons among categorical variables were performed using the chi-square test or Fisher’s exact test, as appropriate. Normally distributed continuous variables are reported as mean ± standard deviation, and differences between groups were assessed using independent t-tests and Kruskal-Wallis H Test. For continuous variables with non-normal distributions, data were expressed as median (1st quartile, 3rd quartile) [M (P25, P75)], and the Mann-Whitney U test was used to compare the groups. Variables that demonstrated statistical significance ( P <0.05) in the univariate analysis of mortality risk factors were subsequently included in a multivariate logistic regression model to evaluate the multifactorial associations with VBCP. All statistical analyses were performed using SPSS version 26.0 (SPSS, Inc., Chicago, IL, USA). Statistical significance was set at a two-tailed p-value of less than 0.05. Receiver operating characteristic (ROC) analysis was employed to measure the diagnostic values of inflammatory markers. This analysis informed some indices to measure the predictive value including area under the ROC curve, sensitivity and specificity. Results Epidemiological characteristics Among 2315 children with CAP, the RSV positivity rate (22.76%) was significantly higher than that for AdV (9.72%) and hMPV (9.84%) ( p < 0.05, Fig. 1 a). SVP and VBCP were the predominant infection patterns for all three pathogens (Fig. 1 b). The three most common bacteria in the VBCP groups were Haemophilus influenzae , Streptococcus pneumoniae , and Moraxella catarrhalis (Fig. 1 c). The severe case rate was significantly higher in the Respiratory syncytial virus and bacterial co-infected pneumonia (RSV-VBCP, 51.75%) and Human metapneumovirus and bacterial co-infected pneumonia hMPV-VBCP (39.02%) groups than in the single Respiratory syncytial virus pneumonia (RSV-SVP, 41.79%) and single Human metapneumovirus pneumonia (hMPV-SVP ,26.00%) groups, respectively ( p < 0.05, Fig. 1 d). The monthly and age distributions of the three pathogens differed. RSV positivity peaked twice in autumn and winter, with a minor peak in spring. AdV stayed stable year-round, without a low-incidence period. hMPV positivity was highest from January to April, dropping in May (Fig. 1 e). RSV positivity declined with age, peaking in children under 1 year. AdV infection was most common in children aged 1–5, while hMPV positivity was highest in those aged 1–3 ( p < 0.05, Fig. 1 f). Comparison of clinical symptoms and inflammatory markers among three types of SVP and VBCP A comparative analysis of clinical symptoms and inflammatory markers across the three SVP types revealed distinct profiles. Specifically, children in the RSV-SVP group were the youngest and most likely to present with wheezing. In contrast, patients in the single Adenovirus pneumonia pneumonia (AdV-SVP) group were the oldest and had the shortest hospital stay compared with those in the RSV-SVP and hMPV-SVP groups. Furthermore, high fever and tonsillar enlargement were most common in the AdV-SVP group, which also had the highest sepsis rate. Additionally, this group exhibited significantly higher IL-6 levels and WBC counts than the RSV-SVP and hMPV-SVP groups ( p < 0.05, Table 1 ). A comparative analysis of clinical symptoms and inflammatory markers across the three VBCP types showed that the RSV-VBCP group had the youngest patients and the highest wheezing rate. In contrast, the Adenovirus and bacterial co-infected pneumonia (AdV-VBCP) group exhibited the shortest hospital stay, the most frequent high fever and tonsillar enlargement, and the highest sepsis incidence. Furthermore, the AdV-VBCP group also had the highest IL-6 levels, which were significantly higher than those in the RSV-SVP and hMPV-SVP groups, although it had the lowest WBC and hs-CRP levels ( p < 0.05, Table 2 ). Table 1 A Comparison of Clinical Symptoms and Inflammatory Markers in Three Types of SVP RSV-SVP(n = 201) AdV-SVP(n = 95) hMPV-SVP(n = 100) χ 2 /H p Demographics and Hospitalization Status Male n(%) 126(62.69%) 56(58.95%) 52(52%) 3.156 0.206 Age (months) 9 (4,12) 36(12,60) 24(10,48) 103.087 a < 0.001, b < 0.001, c = 0.003* LOS (days) 6 (5,7) 5(5,6) 6(5,7) 18.947 a < 0.001, b = 0.109, c = 0.028* Pre-admission course (days) 4 (3,6) 3(2,7) 4(3,5) 4.538 0.075 Clinical symptoms Fever n(%) 75(37.31%) 69(72.63%) 57(57.00%) 41.088 a < 0.001, b < 0.001, c = 0.029* Cough n(%) 200(99.50%) 87(92.05%) 97(97.00%) 13.781 a < 0.001, b = 0.074, c < 0.001* Wheezing n(%) 77(38.31%) 11(11.58%) 20(20.00%) 26.805 a < 0.001, b < 0.001, c = 0.187* Enlarged tonsils n(%) 44(21.89%) 73(76.84%) 50(50.00%) 83.240 a < 0.001, b < 0.001, c < 0.001* Severe rates n(%) 84(41.79%) 46(48.42%) 26(26.00%) 11.240 a = 0.0283, b = 0.007, c = 0.001* Complications Myocardial damage 68(33.83%) 11(11.58%) 21(21.00%) 18.204 a < 0.001, b = 0.022, c = 0.076* Sepsis 9(4.48%) 46(48.42%) 15(15.00%) 84.919 a < 0.001, b = 0.001, c < 0.001* Inflammatory markers IL-2 1.09(0.91,1.28) 0.99 (0.77,1.26) 1.12(1.01,1.34) 11.241 0.871 IL-4 0.9(0.79,0.97) 0.86 (0.80,0.93) 0.91(0.8,0.98) 4.732 0.094 IL-6 5.32(2.79,11.08) 15.28 (8.71,29.93) 6.62(3.64,15.54) 44.019 a < 0.001, b = 0.169, c = 0.002* IL-10 6.3(2.71,15.13) 5.55 (3.22,9.52) 8.81(5.64,17.29) 14.42 a = 0.963, b = 0.014, c = 0.320* IL-17A 1.31(0.8,1.8) 0.88 (0.76,1.67) 1.29(0.78,1.73) 1.689 0.430 TNF-α 0.89(0.76,1.01) 0.91 (0.76,1.09) 0.9(0.76,1.1) 0.546 0.761 IFN-γ 3.28(1.52,6.81) 4.66 (1.89,11.22) 4.95(2.34,9.65) 12.266 a = 0.035, b = 0.178, c = 0.61 WBC 8.4(6.4,11.2) 10.40 (7.15,12.4) 7.8(5.8,10.35) 21.704 a = 0.004, b = 0.222, c < 0.001 hs-CRP 0.5(0.5,3.04) 1.89 (0.5,7.39) 2.29(0.5,7.99) 44.666 a < 0.001, b = 0.013, c = 0.018 Notes: a RSV group vs AdV group, b RSV group vs hMPV group, c AdV group vs hMPV group, *Significant statistical difference ( P < 0.05). Table 2 A Comparison of Clinical Symptoms and Inflammatory Markers in Three Types of VBCP RSV-VBCP(n = 199) AdV-VBCP(n = 60) hMPV-VBCP(n = 82) χ 2 /H p Demographics and Hospitalization Status Male n(%) 134(67.34%) 36(60.00%) 57(58.76%) 2.517 0.284 Age (months) 8 (3,12) 25 (12,48) 24(8,48) 60.504 a < 0.001, b < 0.001, c = 0.397* LOS (days) 7 (6,8) 5 (4,7) 6(5,7) 23.147 a < 0.001, b = 0.364, c = 0.017* Pre-admission course (days) 4 (3,6) 5 (2,7) 4.5(3,7) 5.217 0.074 Clinical symptoms Fever n(%) 66(33.17%) 40(66.67%) 41(42.27%) 23.181 a < 0.001, b = 0.008, c = 0.047* Cough n(%) 198(99.50%) 58(96.67%) 82(100%) 5.638 0.060 Wheezing n(%) 65(32.66%) 7(11.67%) 24(24.74%) 10.114 0.060 Enlarged tonsils n(%) 40(20.10%) 39(65.00%) 36(37.11%) 46.584 a < 0.001, b < 0.001, c = 0.009* Severe rates n(%) 103(51.75%) 26(43.33%) 32(39.02%) 4.219 0.121 Complications Myocardial damage 51(25.63%) 8(13.33%) 19(23.17%) 3.955 0.138 Sepsis 11(5.53%) 23(38.33%) 6(7.32%) 49.947 a < 0.001, b = 0.567, c < 0.001* Inflammatory markers IL-2 1.1(0.86,1.25) 1.14 (0.79,1.49) 1.14(1.03,1.47) 7.823 a = 0.351, b = 0.013, c = 0.139* IL-4 0.88(0.78,0.97) 0.9 (0.79,0.98) 0.91(0.84,1.07) 6.234 a = 0.607, b = 0.003, c = 0.034* IL-6 9.03(4.69,20.24) 29.68 (7.04,50.6) 12.89(6.14,25.69) 15.022 a < 0.001, b = 0.062, c = 0.069* IL-10 5.79(03.39,13.71) 9.01 (3.63,13.35) 9.18(3.82,16.48) 3.616 0.164 IL-17A 1.48(0.91,2.23) 1.33(1.01,1.64) 1.43(1.02,1.92) 3.4 0.183 TNF-α 0.93 (0.76,1.13) 1.04 (0.85,1.78) 0.98(0.76,1.14) 4.076 0.130 IFN-γ 2.89(1.69,6.39) 7.56 (1.78,19.82) 4.71(1.5,10.72) 14.201 a < 0.001, b = 0.049, c = 0.108* WBC 10(7.8,12.8) 8.5 (6.55,10.58) 9.15(7.1,11.53) 10.199 a = 0.121, b = 0.311, c = 0.016* hs-CRP 3.43(0.5,11.33) 0.5 (0.5,2.71) 3.54(0.5,9.12) 10.336 a = 0.003, b = 0.614, c = 0.003* Notes: a RSV group vs AdV group, b RSV group vs hMPV group, c AdV group vs hMPV group, *Significant statistical difference ( P < 0.05 ). Univariate analysis of RSV-VBCP, AdV-VBCP and hMPV-VBCP A total of 400 children with RSV pneumonia, 155 with AdV pneumonia, and 182 with hMPV pneumonia were included. Based on bacterial co-infection status, patients were divided into SVP and VBCP groups. Compared with the RSV-SVP group, the RSV-VBCP group exhibited a significantly increased length of hospital stay, a higher rate of severe disease, as well as higher levels of IL-6, IL-17A, WBC count, and hs-CRP ( P 0.05, Table 3 ). Compared with the AdV-SVP group, the AdV-VBCP group had a significantly longer prehospital duration and higher IL-6 levels (both P < 0.05), but significantly lower WBC count and hs-CRP levels ( P < 0.05). Other indicators showed no statistical significance (Table 4 ). Compared with the hMPV-SVP group, the hMPV-VBCP group demonstrated a significantly increased length of hospital stay, as well as elevated IL-6 levels and WBC count ( P < 0.05). No statistically significant differences were noted in other indicators (Table 5 ). Table 3 Univariate analysis of RSV-VBCP RSV-SVP(n = 201) RSV-VBCP (n = 199) χ2/U P Demographics and Hospitalization Status Male n(%) 126(62.69%) 134(67.34%) 0.950 0.330 Age (months) 9 (4,12) 8 (3,12) 0.02 0.984 LOS (days) 6 (5,7) 7 (6,8) 3.274 0.001* Pre-admission course (days) 4 (3,6) 4 (3,6) 0.824 0.410 Clinical symptoms Fever n(%) 75(37.31%) 66(33.17%) 0.881 0.348 Cough n(%) 200(99.50%) 198(99.45%) 0.001 0.994 Wheezing n(%) 77(38.31%) 65(32.66%) 1.392 0.238 Enlarged tonsils n(%) 44(21.89%) 40(20.10%) 0.193 0.660 Complications Myocardial damage 68(33.83%) 51(25.63%) 3.219 0.073 Sepsis 9(4.48%) 11(5.53%) 0.232 0.630 Inflammatory markers IL-2 1.09(0.91,1.28) 1.10(0.86,1.25) 0.019 0.985 IL-4 0.90(0.79,0.97) 0.88(0.78,0.97) 0.86 0.390 IL-6 5.32(2.79,11.08) 9.03(4.69,20.24) 5.5 < 0.001* IL-10 6.30(2.71,15.13) 5.79(3.39,13.71) 0.421 0.674 IL-17A 1.31(0.8,1.8) 1.48(0.91,2.23) 2.303 0.021* TNF-α 0.89(0.76,1.01) 0.93 (0.76,1.13) 0.912 0.362 IFN-γ 3.28(1.52,6.81) 2.89(1.69,6.39) 0.41 0.682 WBC 8.40(6.4,11.2) 10.00(7.8,12.8) 3.918 < 0.001* hs-CRP 0.50(0.5,3.04) 3.43(0.5,11.33) 5.928 < 0.001* *Significant statistical difference ( P < 0.05) Table 4 Univariate analysis of AdV-VBCP AdV-SVP(n = 95) AdV-VBCP (n = 60) χ 2 /U P Demographics and Hospitalization Status Male n(%) 56(58.95%) 36(60.00%) 0.017 0.897 Age (months) 36(12,60) 25 (12,48) 1.450 0.147 LOS (days) 5(5,6) 5 (4,7) 0.480 0.631 Pre-admission course (days) 3(2,7) 5 (2,7) 2.178 0.029* Clinical symptoms Fever n(%) 69(72.63%) 40(66.67%) 0.627 0.428 Cough n(%) 87(92.05%) 58(96.67%) 1.577 0.209 Wheezing n(%) 11(11.58%) 7(11.67%) 0.627 0.428 Enlarged tonsils n(%) 73(76.84%) 39(65.00%) 0.453 0.501 Complications Myocardial damage 11(11.58%) 8(13.33%) 0.105 0.746 Sepsis 46(48.42%) 23(38.33%) 1.515 0.218 Inflammatory markers IL-2 0.99 (0.77,1.26) 1.14 (0.79,1.49) 1.954 0.051 IL-4 0.86 (0.80,0.93) 0.90 (0.79,0.98) 1.326 0.185 IL-6 15.28 (8.71,29.93) 29.68 (7.04,50.6) 2.706 0.007* IL-10 5.55 (3.22,9.52) 9.01 (3.63,13.35) 1.899 0.058 IL-17A 0.88 (0.76,1.67) 1.33(1.01,1.64) 1.949 0.051 TNF-α 0.91 (0.76,1.09) 1.04 (0.85,1.78) 1.840 0.066 IFN-γ 4.66 (1.89,11.22) 7.56 (1.78,19.82) 1.315 0.188 WBC 10.40 (7.15,12.4) 8.5 (6.55,10.58) 2.320 0.020* hs-CRP 1.89 (0.5,7.6) 0.50 (0.5,2.71) 2.540 0.011* *Significant statistical difference ( P < 0.05) Table 5 Univariate analysis of hMPV-VBCP hMPV-SVP(n = 100) hMPV-VBCP(n = 82) χ 2 /U P Demographics and Hospitalization Status Male n(%) 65(65.00%) 57(69.51%) 0.415 0.519 Age (months) 24(10,48) 24(8,48) 0.141 0.888 LOS (days) 6(5,7) 6(5,7) 2.64 0.008 Pre-admission course (days) 4(3,5) 4.5(3,7) 1.632 0.103 Clinical symptoms Fever n(%) 57(57.00%) 41(50.00%) 0.888 0.346 Cough n(%) 97(97.00%) 82(100%) 2.501 0.114 Wheezing n(%) 20(20.00%) 24(29.27%) 2.111 0.146 Enlarged tonsils n(%) 50(50.00%) 36(43.90%) 0.672 0.412 Complications Myocardial damage 21(21.00%) 19(23.17%) 0.124 0.725 Sepsis 15(15.00%) 6(7.32%) 2.606 0.106 Inflammatory markers IL-2 1.12(1.01,1.34) 1.14(1.03,1.47) 1.113 0.266 IL-4 0.91(0.8,0.98) 0.91(0.84,1.07) 1.187 0.235 IL-6 6.62(3.64,15.54) 12.89(6.14,25.69) 3.502 < 0.001* IL-10 8.81(5.64,17.29) 9.18(3.82,16.48) 0.892 0.372 IL-17A 1.29(0.78,1.73) 1.43(1.02,1.92) 1.856 0.063 TNF-α 0.90(0.76,1.1) 0.98(0.76,1.14) 1.432 0.152 IFN-γ 4.95(2.34,9.65) 4.71(1.5,10.72) 0.475 0.635 WBC 7.8(5.8,10.35) 9.15(7.1,11.53) 2.65 0.008* hs-CRP 2.29(0.5,7.99) 3.54(0.5,9.12) 1.017 0.309 *Significant statistical difference ( P < 0.05) Multivariable logistic regression analysis of RSV-VBCP, AdV-VBCP and hMPV-VBCP To identify independent risk factors for viral-bacterial co-infection, variables with P < 0.1 in the univariate analysis were included in the multivariate logistic regression. Multivariate logistic regression analysis identified elevated IL-6 (OR = 1.031, 95% CI: 1.011–1.052, P = 0.002) and WBC (OR = 1.062, 95% CI: 1.005–1.122, P = 0.032) as independent risk factors for RSV-VBCP (Table 6 ). For AdV-VBCP, elevated IL-6 (OR = 1.035, 95% CI: 1.015–1.056, P = 0.001) was independent risk factor (Table 7 ). Elevated IL-6 (OR = 1.026, 95% CI: 1.006–1.046, P = 0.009) independently predicted hMPV-VBCP. No other indicators showed independent predictive value in any group (Table 8 ). Table 6 Multivariable logistic regression analysis of RSV-VBC Risk Factors β SE Wald OR 95% CI P IL6 0.031 0.01 9.484 1.031 (1.011,1.052) 0.002* Myocardial damage 0.329 0.232 2.009 1.389 (0.882,2.189) 0.156 IL17A 0.074 0.078 0.892 1.077 (0.924,1.255) 0.345 WBC 0.06 0.028 4.602 1.062 (1.005,1.122) 0.032* CRP 0.018 0.014 1.75 1.018 (0.991,1.046) 0.186 *Significant statistical difference ( P < 0.05) β: regression coefficient; SE: standard deviation; OR: odds ratio; CI: confidence interval Table 7 Multivariable logistic regression analysis of AdV-VBCP Risk Factors β SE Wald OR 95% CI P IL2 0.258 0.179 2.082 1.294 (0.912,1.837) 0.149 IL6 0.035 0.01 11.797 1.035 (1.015,1.056) 0.001* IL10 -0.001 0.007 0.041 0.999 (0.985,1.013) 0.839 IL17A 0.061 0.177 0.121 1.063 (0.752,1.504) 0.728 TNF 0.047 0.115 0.17 1.049 (0.837,1.314) 0.680 WBC -0.063 0.045 1.979 0.939 (0.859,1.025) 0.160 CRP -0.034 0.021 2.649 0.967 (0.928,1.007) 0.104 *Significant statistical difference ( P < 0.05) β: regression coefficient; SE: standard deviation; OR: odds ratio; CI: confidence interval Table 8 Multivariable logistic regression analysis of hMPV-VBCP Risk Factors β SE Wald OR 95% CI P IL6 0.026 0.01 6.831 1.026 (1.006,1.046) 0.009* IL17A 0.03 0.162 0.033 1.030 (0.749,1.416) 0.855 WBC 0.066 0.042 2.421 1.068 (0.983,1.160) 0.120 *Significant statistical difference ( P < 0.05) β: regression coefficient; SE: standard deviation; OR: odds ratio; CI: confidence interval Predictive value of inflammatory markers for VBCP ROC curve analysis was performed to assess the predictive value of inflammatory markers for VBCP. Inflammatory markers with significant differences in univariate analysis were used as test variables, with SVP and VBCP as the dependent variables. The results showed that the AUC values of IL-6, IL-17A, WBC, hs-CRP, and their combined panel for predicting RSV-VBCP were 0.659, 0.566, 0.613, 0.667, and 0.689, respectively (Table 9 , Fig. 2 a). For AdV-VBCP prediction, the AUC values of IL-2, IL-6, IL-10, TNF-α, WBC, CRP, and their combined panel were 0.593, 0.629, 0.591, 0.587, 0.616, 0.616, and 0.705, respectively (Table 10 , Fig. 2 b). The AUC values of IL-6, IL-17A, WBC, and their combined panel for predicting hMPV-VBCP were 0.651, 0.580, 0.614, and 0.681, respectively (Table 11 , Fig. 2 c). Table 9 Predictive value of inflammatory markers for VBCP Variables AUC 95CI Cut off Sensitivity Specificity P IL-6 0.659 (0.606, 0.712) 5.8 69.80% 55.20% < 0.001 CRP 0.667 (0.615, 0.719) 1.37 66.80% 63.20% < 0.001 WBC 0.613 (0.558, 0.668) 8.85 63.30% 57.20% < 0.001 IL-17A 0.566 (0.510, 0.623) 1.74 41.70% 73.60% < 0.001 Combination 0.689 (0.638, 0.741) / 67.80% 61.70% < 0.001 *Significant statistical difference ( P < 0.05) Table 10 Predictive value of inflammatory markers for AdV-VBCP Variables AUC 95CI Cut off Sensitivity Specificity P IL-2 0.593 (0.496, 0.689) 1.42 35.00% 89.50% < 0.001 IL-6 0.629 (0.528, 0.730) 40.57 40.00% 96.80% < 0.001 IL-10 0.591 (0.496, 0.686) 8.82 51.70% 72.60% < 0.001 CRP 0.616 (0.531, 0.702) 1.35 73.30% 52.60% < 0.001 WBC 0.611 (0.520, 0.701) 10.15 73.30% 53.70% < 0.001 TNF 0.587 (0.496, 0.679) 1.04 51.70% 67.40% < 0.001 Combination 0.705 (0.616, 0.794) / 41.70% 95.80% < 0.001 *Significant statistical difference ( P < 0.05) Table 11 Predictive value of inflammatory markers for hMPV-VBCP Variables AUC 95CI Cut off Sensitivity Specificity P IL-6 0.651 (0.571, 0.731) 5.86 76.80% 46.00% < 0.001 IL-17A 0.58 (0.497, 0.663) 1.34 59.80% 56.00% < 0.001 WBC 0.614 (0.532, 0.696) 8.15 64.60% 57.00% < 0.001 Combination 0.681 (0.604, 0.759) / 53.70% 77.00% < 0.001 *Significant statistical difference ( P < 0.05) Discussions This study systematically analyzed RSV, AdV, and hMPV infections in 2,315 children under 5 years with CAP in Zunyi, China. It is the first to reveal the epidemiological characteristics of these three viral pneumonias. The study examines the clinical impact of VBCP and differences in related inflammatory markers. It also explores independent risk factors for bacterial complications and assesses the predictive value of associated biomarkers. This study confirms RSV as the main viral cause of pediatric CAP in Zunyi, China. Its positivity rate (22.76%) is much higher than AdV (9.72%) and hMPV (9.84%), matching global pediatric CAP patterns [ 14 – 16 ]. Importantly, the three viruses have distinct seasonal and age distributions. RSV shows autumn-winter peaks and a minor spring peak, which differs from other Chinese regions [ 17 , 18 ], showing notable regional variations. Infection risk drops with age and mainly affects infants in their first year, consistent with global trends [ 19 ]. These findings underscore RSV’s threat to infants and the need for stronger local surveillance and protection during autumn and winter. In contrast, AdV infection occurs sporadically throughout the year, with little seasonal variation [ 20 , 21 ]. AdV is more common in children aged 1–5 years, with positivity rates consistent across domestic studies [ 22 – 24 ]. This confirms its role as a major pediatric CAP pathogen in Zunyi. The disease burden should not be overlooked. Because of AdV’s biological traits [ 25 , 26 ], its potential for ongoing transmission demands year-round clinical vigilance. Meanwhile, hMPV infection was highly concentrated from January to April. It had the highest positivity rate in children aged 1–3 years. This age distribution aligns with hMPV’s immunopathogenesis [ 27 , 28 ], but differs from that in other Chinese regions, such as Hebei, where peaks occur in summer and autumn [ 29 ]. Taken together, these characteristic distributions reflect inter-viral differences in environmental stability, transmission routes, and host immune responses. This provides a basis for targeted regional prevention and control strategies. Turning to clinical features, in the SVP group, RSV-infected children were the youngest and most prone to wheezing, consistent with global evidence that RSV is the primary pathogen of lower respiratory tract infections in infants. It's induced bronchial hyperreactivity and airway narrowing underpin the high wheezing incidence [ 30 – 33 ]. In contrast, AdV-infected children were the oldest, with significantly shorter hospital stays than the RSV and hMPV groups—potentially due to AdV’s predominance in preschoolers with relatively mature immune systems and more self-limiting disease courses. However, the AdV-SVP group also showed the highest incidence of fever and tonsillar enlargement, along with the highest sepsis risk, likely due to AdV’s direct epithelial lytic effect [ 34 ] and systemic inflammation [ 35 , 36 ]. Inflammatory marker data support this: AdV-SVP had significantly higher IL-6 and WBC levels than RSV-SVP and hMPV-SVP ( p < 0.05, Table 1 ). As a key pro-inflammatory cytokine, elevated IL-6 correlates with infection severity and systemic inflammatory responses [ 37 , 38 ]; AdV may induce substantial IL-6 release via mechanisms such as TLR pathway activation [ 39 , 40 ], thereby increasing fever and sepsis risk. Elevated WBC reflects the bone marrow’s rapid inflammatory response, further confirming AdV’s invasiveness. A similar pattern is observed in the VBCP group. RSV-VBCP infection mainly affected the youngest age group and was associated with a high incidence of wheezing, confirming that RSV retains its typical clinical features even in the presence of coinfection. On the other hand, the AdV-VBCP group had the shortest hospital stay, but showed the highest rates of high fever, tonsillar enlargement, and sepsis. These trends were similar to those noted in the AdV-SVP group, indicating that AdV infection tends to induce severe systemic symptoms, regardless of bacterial coinfection. Notably, inflammatory markers showed a complex pattern. The AdV-VBCP group exhibited the highest IL-6 levels, which were significantly higher than those in the RSV-SVP and hMPV-SVP groups. This may indicate that AdV plays a dominant role in the inflammatory response, even in the presence of bacterial coinfection. Elevated IL-6 is an early warning indicator and is positively correlated with sepsis risk. However, the AdV-VBCP group had the lowest WBC and hs-CRP levels, a paradoxical finding that warrants further investigation. On one hand, this may indicate an altered immune response during AdV-bacterial coinfection. For example, bacterial infection might inhibit WBC mobilization or accelerate apoptosis. On the other hand, low hs-CRP, an acute-phase protein, may be related to specific AdV strains or host immune regulation. For instance, AdV encodes proteins that interfere with host inflammatory pathways and partly suppress CRP synthesis [ 41 – 43 ]. Additionally, this discrepancy may reflect the influence of coinfecting bacterial types. Further subdivision of bacterial profiles is needed for verification. Building upon these findings, this study focused on identifying risk factors for VBCP. Multivariate logistic regression consistently identified elevated IL-6 levels as a common independent risk factor for bacterial coinfection in RSV-, AdV-, and hMPV-associated pneumonia. IL-6 is a core pro-inflammatory cytokine. Marked elevation of IL-6 reflects the severity of infectious stress, but it can also impair host bacterial clearance through immunosuppression [ 44 – 46 ]. This dual role creates a microenvironment favorable for secondary bacterial infection [ 38 , 47 , 48 ]. Thus, IL-6 is a key biomarker for predicting bacterial coinfection in pediatric pneumonia. Notably, distinct pathogens exhibit both similarities and differences in inflammatory marker changes during progression to VBCP. Specifically, compared with their respective SVP groups, RSV, AdV, and hMPV all showed significantly elevated IL-6 in coinfections. This finding confirms that IL-6 is a common risk factor. However, other systemic inflammatory indicators showed different trends. For instance, RSV coinfections were associated with concurrent increases in IL-6, IL-17A, WBC, and hs-CRP, consistent with typical inflammatory profiles in bacterial infections. These laboratory findings may support prompt consideration of bacterial coinfection in clinical practice. In contrast, AdV coinfections showed a marked increase in IL-6 but significant reductions in WBC and hs-CRP, underscoring that these laboratory profiles may lead to underrecognition of inflammation and warrant consideration of AdV's effects when interpreting results. This may relate to AdV-mediated inhibition of bone marrow hematopoiesis or hepatic synthetic function [ 41 , 43 , 49 ]. Ultimately, these findings highlight unique and potentially misleading laboratory results in AdV coinfections, warranting heightened clinical caution in interpretation. To further clarify clinical application, ROC curve analysis assessed the predictive value of inflammatory markers for VBCP. Single inflammatory markers showed limited predictive utility for VBCP, whereas combining IL-6 with other indicators improved predictive accuracy. This approach has potential clinical relevance and may provide auxiliary decision support for the rational use of antibiotics. Clinically, this study found important distinctions in patient management. AdV infection, whether in SVP or VBCP, was associated with high fever, a high sepsis incidence, and sustained IL-6 elevation. This suggests that, in the management of pediatric pneumonia in the Zunyi region, heightened vigilance for systemic complications is warranted in AdV-infected cases, with timely monitoring of IL-6 and other inflammatory markers to assess potential bacterial coinfection. In contrast, RSV infection management prioritizes wheezing control, whereas hMPV typically presents with relatively mild clinical manifestations. While differences in inflammatory markers may help distinguish SVP from VBCP, comprehensive clinical judgment is essential to avoid misinterpretation based on a single indicator. Despite these insights, this study has several limitations. First, as a single-center retrospective study, selection bias cannot be ruled out. Second, inflammatory markers were measured only at admission, precluding dynamic assessment of their temporal changes. Third, the dose-response relationship between viral load and bacterial coinfection risk was not evaluated, limiting understanding of how viral replication dynamics influence secondary infections. Future prospective multicenter studies will facilitate more precise risk assessment. Conclusion In summary, this study systematically characterized the distinct epidemiological features of RSV-, AdV-, and hMPV-associated pediatric pneumonia in the Zunyi region. Elevated IL-6 was confirmed as a common independent risk factor for VBCP across all three viral etiologies, with virus-specific risk factor profiles further identified. These findings provide evidence for targeted risk assessment and guide the development of personalized antibiotic management strategies for pediatric viral pneumonia in this region. Abbreviations RSV Respiratory syncytial virus AdV Adenovirus hMPV Human metapneumovirus MP Mycoplasma pneumoniae CAP Community Acquired Pneumonia VBCP viral and bacterial co-infected pneumonia SVP single virus pneumonia RSV-SVP single Respiratory syncytial virus pneumonia AdV-SVP single Adenovirus pneumonia pneumonia hMPV-SVP single Human metapneumovirus pneumonia RSV-VBCP Respiratory syncytial virus and bacterial co-infected pneumonia AdV- VBCP Adenovirus and bacterial co-infected pneumonia hMPV- VBCP Human metapneumovirus and bacterial co-infected pneumonia Declarations Ethics approval and consent to participate This study was approved by the Ethics Review Committee of the First People’s Hospital of Zunyi (Approval No. 2026-1-70). The Ethics Review Committee of the First People’s Hospital of Zunyi has waived the requirement for informed consent because this is a retrospective analysis, all patient information was anonymized, and there were no additional interventions or risks to participants in this study. This study was conducted in full accordance with the Declaration of Helsinki. Consent for publication Not applicable. Competing interests The authors declare no competing interests. Clinical trial number Not applicable. Author details 1 Department of Laboratory Medicine, the First People’s Hospital of Zunyi (the Third Affiliated Hospital of Zunyi Medical University), Zunyi, People’s Republic of China 2 The First Clinical College of Zunyi Medical University, Zunyi, Guizhou, China Funding This project was supported by the 2026 Guizhou Provincial Health Research Project (Clinical Research Category, NO. 2026GZWJKJXM0093). Author Contribution Conception and design: DWZ. Acquisition of data: DWZ, KTT, YZ, JJM and HY. Analysis and interpretation of data: DWZ and KTT. Drafting of the article: DWZ. Critical revision of the article: DWZ and HZ. Writing—review & editing: DWZ. Study supervision: DWZ. and HZ. All authors have read and agreed to the published version of the manuscript. Acknowledgements Not applicable. Data Availability The datasets used or analysed during this study available from the corresponding author on reasonable request. References Global. regional, and national incidence and mortality burden of non-COVID-19 lower respiratory infections and aetiologies, 1990–2021: a systematic analysis from the Global Burden of Disease Study 2021 [J]. Lancet Infect Dis. 2024;24(9):974–1002. Quantifying risks and interventions that have affected the burden. of lower respiratory infections among children younger than 5 years: an analysis for the Global Burden of Disease Study 2017 [J]. Lancet Infect Dis. 2020;20(1):60–79. 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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-8884580","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":597672174,"identity":"138c3c61-0451-40d9-a210-5638314509e4","order_by":0,"name":"Dewei Zhou","email":"","orcid":"","institution":"the First People’s Hospital of Zunyi (the Third Affiliated Hospital of Zunyi Medical University)","correspondingAuthor":false,"prefix":"","firstName":"Dewei","middleName":"","lastName":"Zhou","suffix":""},{"id":597672175,"identity":"ddcb2bb8-6618-4677-89a1-e8ab99df137a","order_by":1,"name":"Kaiting Tang","email":"","orcid":"","institution":"The First Clinical College of Zunyi Medical University","correspondingAuthor":false,"prefix":"","firstName":"Kaiting","middleName":"","lastName":"Tang","suffix":""},{"id":597672176,"identity":"badf054a-6d54-4f4c-8c0e-c89bcc68ff9e","order_by":2,"name":"Yu Zhao","email":"","orcid":"","institution":"the First People’s Hospital of Zunyi (the Third Affiliated Hospital of Zunyi Medical University)","correspondingAuthor":false,"prefix":"","firstName":"Yu","middleName":"","lastName":"Zhao","suffix":""},{"id":597672177,"identity":"79578b33-aa9d-4427-9594-17277c5c3a41","order_by":3,"name":"Huan Yue","email":"","orcid":"","institution":"the First People’s Hospital of Zunyi (the Third Affiliated Hospital of Zunyi Medical University)","correspondingAuthor":false,"prefix":"","firstName":"Huan","middleName":"","lastName":"Yue","suffix":""},{"id":597672178,"identity":"3b147378-66d5-44a8-b4a1-aa1e9682ee8b","order_by":4,"name":"Jingjing Ma","email":"","orcid":"","institution":"the First People’s Hospital of Zunyi (the Third Affiliated Hospital of Zunyi Medical University)","correspondingAuthor":false,"prefix":"","firstName":"Jingjing","middleName":"","lastName":"Ma","suffix":""},{"id":597672179,"identity":"9d2048a3-93bd-4096-bcd5-3abcaad24d34","order_by":5,"name":"He Zha","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAxUlEQVRIiWNgGAWjYDACCQY2BoYKGzl+ZuaDD0jQcibNWLKdLdmAeC2MLYcSDc7zmAkQpUN+dvOzBx8bDiQYH2YwY2CosYkmqIVxzjFzw5k77uSZHWZIe8BwLC23gZAWZokEM2neM8+KgVqOGzA2HCashU0i/Zv037bDiZubGdskiNLCI5FjJs0I1LKBmZmNOC0SEjllkj3AQJY4zMZskECMX+RnpG+T+AGKyv7zHx98qLEhrAUVJJCmfBSMglEwCkYBLgAA5pQ+kIRc010AAAAASUVORK5CYII=","orcid":"","institution":"the First People’s Hospital of Zunyi (the Third Affiliated Hospital of Zunyi Medical University)","correspondingAuthor":true,"prefix":"","firstName":"He","middleName":"","lastName":"Zha","suffix":""}],"badges":[],"createdAt":"2026-02-15 08:08:46","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8884580/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8884580/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":104171687,"identity":"d3ea5c84-acfd-4b2d-ae7c-2a2e8e8dd69c","added_by":"auto","created_at":"2026-03-08 14:55:12","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":44731,"visible":true,"origin":"","legend":"\u003cp\u003eEpidemiological characteristics of RSV, AdV, and hMPV. (a) Positive rates of RSV, AdV, and hMPV. (b) Infection patterns of RSV, AdV, and hMPV. (c) Pathogen composition of viral and bacterial co-infected pneumonia. (d) Comparison of severe ratesbetween SVI and VBCP. (e) Monthly distribution of RSV, AdV, and hMPV. (f) Age distribution of RSV, AdV, and hMPV.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-8884580/v1/196481e55c6e380eac465081.png"},{"id":104171665,"identity":"6c4dc7cf-076e-46f9-9470-cbc93e2e4f81","added_by":"auto","created_at":"2026-03-08 14:55:10","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":38385,"visible":true,"origin":"","legend":"\u003cp\u003eROC curves. (a) The roc curve of RSV-VBCP. (b) The roc curve of AdV-VBCP. (c) The roc curve of hMPV-VBCP.\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-8884580/v1/4a66797aab2e40b1fe8c341d.png"},{"id":104171711,"identity":"ec42f63d-0757-43a0-926e-72208ee3a47e","added_by":"auto","created_at":"2026-03-08 14:55:21","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1841655,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8884580/v1/6ceffce2-0791-4c91-ae9e-7304a9234483.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Epidemiology, Bacterial Coinfection Risk Factors, and Inflammatory Markers in Children with RSV, AdV, and hMPV Pneumonia in Zunyi, China","fulltext":[{"header":"Background","content":"\u003cp\u003eCommunity-acquired pneumonia (CAP) is a leading cause of morbidity and mortality in children under 5 worldwide. Viruses are major etiological agents, and the pathogen profile is complex [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. RSV, adenovirus, and hMPV are the most common viral pathogens of childhood CAP [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Clinically, these viruses induce primary pneumonia. They also cause respiratory mucosal damage and local immune dysfunction, predisposing children to secondary bacterial infections and viral-bacterial coinfection pneumonia (VBCP) [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. VBCP exacerbates inflammation, leading to more severe illness, prolonged disease, and increased severity rates [\u003cspan additionalcitationids=\"CR7\" citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. The epidemiology of respiratory pathogens varies by country and region, influenced by geographic location, humidity, and other factors [\u003cspan additionalcitationids=\"CR10\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Research often focuses on single-viral pneumonia (SVP) or nationwide analyses [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Few studies address VBCP or compare CAP caused by RSV, AdV, and hMPV.\u003c/p\u003e \u003cp\u003eIn southwest China, particularly Zunyi, the pathogen spectrum and disease burden of childhood respiratory infections may vary regionally due to unique geographic, climatic, and population density conditions. To date, basic data on the age distribution, seasonal epidemic patterns, as well as positivity rates of RSV-, AdV-, and hMPV-induced pneumonia in Zunyi\u0026rsquo;s children remain lacking. Furthermore, the risk factors for bacterial co-infection with these three viruses are not clearly defined, and targeted early identification indicators are scarce in clinical practice. Consequently, regional, multi-virus comparative studies specific to Zunyi are limited, failing to meet the real needs of local clinical diagnosis, treatment, and prevention. Although inflammatory markers have gained widespread attention for their diagnostic value in viral-bacterial co-infections, differences in their expression levels and comparative diagnostic potency across distinct viral infection contexts require additional confirmation.\u003c/p\u003e \u003cp\u003eThis study aims to systematically analyze the epidemiological characteristics of RSV-, AdV-, and hMPV-induced pneumonia in Zunyi, identify independent risk factors for bacterial co-infection, and compare differences in inflammatory marker expression between SVP and VBCP. The findings are intended to provide a scientific basis for precise prevention and control of pediatric viral pneumonia, early identification of bacterial co-infections, and personalized treatment in Zunyi.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cp\u003e\u003cstrong\u003e\u0026nbsp;1. Materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA retrospective analysis of clinical data from 2315 children aged \u0026lt;5 years with CAP hospitalized in the Department of Pediatric Respiratory Medicine at Zunyi First People\u0026apos;s Hospital (The Third Affiliated Hospital of Zunyi Medical University) from January to December 2025 was performed. The Ethics Review Committee has waived the requirement for informed consent because this is a retrospective analysis, all patient information was anonymized, and there were no additional interventions or risks to participants in this study. This study was conducted in full accordance with the Declaration of Helsinki.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2. Methods\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.1 Inclusion and Exclusion Criteria\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eInclusion criteria:\u0026nbsp;①\u0026nbsp;Diagnosis of pneumonia per the 2023 pediatric guidelines, with pulmonary moist rales and radiological evidence; cases classified as severe or non-severe per guideline criteria.\u0026nbsp;② Complete clinical data available.\u0026nbsp;③Eligible participants were children aged between 29 days and 5 years at the time of hospital admission.\u0026nbsp;④Biological samples collected within 24 hours of admission for pathogen and inflammatory marker testing.\u003c/p\u003e\n\u003cp\u003eExclusion criteria:\u0026nbsp;①\u0026nbsp;Presence of severe comorbidities or immunodeficiency.\u0026nbsp;②\u0026nbsp;Diagnosis of pneumonia secondary to bronchopulmonary dysplasia, respiratory tract malformations, or foreign body aspiration.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.2\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eGrouping\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePatients were grouped via two approaches:\u003c/p\u003e\n\u003cp\u003e1. Based on throat swab etiological test results at admission:\u0026nbsp;①\u0026nbsp;SVP group: Detection of only one target virus (RSV, AdV, or hMPV) without concurrent bacteria or other pathogens;\u0026nbsp;②\u0026nbsp;VBCP group: Detection of one aforementioned target virus plus one or more bacterial pathogens.\u003c/p\u003e\n\u003cp\u003e2. Based on disease severity, children were divided into severe and non‑severe groups. Severe pneumonia was defined as meeting any of the following criteria: poor general condition, impaired consciousness, hypoxemia, hyperpyrexia or persistent fever \u0026gt;5 days, dehydration or refusal to eat, or chest X‑ray/CT findings consistent with severe pneumonia.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.3 Etiological Detection\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTotal nucleic acids were extracted from samples using a Sansure Biotech nucleic acid extraction kit (magnetic bead-based). Multiplex nucleic acid detection kits from the same manufacturer were used to detect 8 respiratory pathogens (AdV, RSV, hMPV, parainfluenza virus types 1/2/3, influenza A/B viruses) and Mycoplasma pneumoniae. All assays were performed on an Applied Biosystems Q5 real‑time fluorescent quantitative PCR system, strictly following the manufacturer\u0026rsquo;s instructions. Bacterial culture was performed using sputum samples.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.4 Inflammation Marker Detection\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSerum concentrations of cytokines (IL-2, IL-4, IL-6, IL-10, IL-17A, TNF-\u0026alpha;, IFN-\u0026gamma;) were measured using a BD FcapArray3 flow cytometer. White blood cell (WBC) count and high-sensitivity C-reactive protein (hs-CRP) levels were detected with a Sysmex automated hematology analyzer and specific protein analyzer, respectively.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCategorical data were presented as the number of cases and corresponding percentages. Comparisons among categorical variables were performed using the\u0026nbsp;chi-square test or Fisher\u0026rsquo;s exact test, as appropriate. Normally distributed continuous variables are reported as mean \u0026plusmn; standard deviation, and differences between groups were assessed using independent t-tests and Kruskal-Wallis H Test. For continuous variables with non-normal distributions, data were expressed as median (1st quartile, 3rd quartile) [M (P25, P75)], and the Mann-Whitney U test was used to compare the groups. Variables that demonstrated statistical significance (\u003cem\u003eP\u003c/em\u003e\u0026lt;0.05) in the univariate analysis of mortality risk factors were subsequently included in a multivariate logistic regression model to evaluate the multifactorial associations with VBCP. All statistical analyses were performed using SPSS version 26.0 (SPSS, Inc., Chicago, IL, USA). Statistical significance was set at a two-tailed p-value of less than 0.05. Receiver operating characteristic (ROC) analysis was employed to measure the diagnostic values of inflammatory markers. This analysis informed some indices to measure the predictive value including area under the ROC curve, sensitivity and specificity.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eEpidemiological characteristics\u003c/h2\u003e \u003cp\u003eAmong 2315 children with CAP, the RSV positivity rate (22.76%) was significantly higher than that for AdV (9.72%) and hMPV (9.84%) (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05, Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea). SVP and VBCP were the predominant infection patterns for all three pathogens (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eb). The three most common bacteria in the VBCP groups were \u003cem\u003eHaemophilus influenzae\u003c/em\u003e, \u003cem\u003eStreptococcus pneumoniae\u003c/em\u003e, and \u003cem\u003eMoraxella catarrhalis\u003c/em\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ec). The severe case rate was significantly higher in the Respiratory syncytial virus and bacterial co-infected pneumonia (RSV-VBCP, 51.75%) and Human metapneumovirus and bacterial co-infected pneumonia hMPV-VBCP (39.02%) groups than in the single Respiratory syncytial virus pneumonia (RSV-SVP, 41.79%) and single Human metapneumovirus pneumonia (hMPV-SVP ,26.00%) groups, respectively (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05, Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ed). The monthly and age distributions of the three pathogens differed. RSV positivity peaked twice in autumn and winter, with a minor peak in spring. AdV stayed stable year-round, without a low-incidence period. hMPV positivity was highest from January to April, dropping in May (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ee). RSV positivity declined with age, peaking in children under 1 year. AdV infection was most common in children aged 1\u0026ndash;5, while hMPV positivity was highest in those aged 1\u0026ndash;3 (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05, Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ef).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eComparison of clinical symptoms and inflammatory markers among three types of SVP and VBCP\u003c/h3\u003e\n\u003cp\u003eA comparative analysis of clinical symptoms and inflammatory markers across the three SVP types revealed distinct profiles. Specifically, children in the RSV-SVP group were the youngest and most likely to present with wheezing. In contrast, patients in the single Adenovirus pneumonia pneumonia (AdV-SVP) group were the oldest and had the shortest hospital stay compared with those in the RSV-SVP and hMPV-SVP groups. Furthermore, high fever and tonsillar enlargement were most common in the AdV-SVP group, which also had the highest sepsis rate. Additionally, this group exhibited significantly higher IL-6 levels and WBC counts than the RSV-SVP and hMPV-SVP groups (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05, Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). A comparative analysis of clinical symptoms and inflammatory markers across the three VBCP types showed that the RSV-VBCP group had the youngest patients and the highest wheezing rate. In contrast, the Adenovirus and bacterial co-infected pneumonia (AdV-VBCP) group exhibited the shortest hospital stay, the most frequent high fever and tonsillar enlargement, and the highest sepsis incidence. Furthermore, the AdV-VBCP group also had the highest IL-6 levels, which were significantly higher than those in the RSV-SVP and hMPV-SVP groups, although it had the lowest WBC and hs-CRP levels (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05, Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\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\u003eA Comparison of Clinical Symptoms and Inflammatory Markers in Three Types of SVP\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\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=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRSV-SVP(n\u0026thinsp;=\u0026thinsp;201)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAdV-SVP(n\u0026thinsp;=\u0026thinsp;95)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ehMPV-SVP(n\u0026thinsp;=\u0026thinsp;100)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eχ\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u003cem\u003e/H\u003c/em\u003e\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 \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDemographics and Hospitalization Status\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale n(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e126(62.69%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e56(58.95%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e52(52%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3.156\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.206\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (months)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9 (4,12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e36(12,60)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e24(10,48)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e103.087\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ea\u0026thinsp;\u0026lt;\u0026thinsp;0.001, b\u0026thinsp;\u0026lt;\u0026thinsp;0.001, c\u0026thinsp;=\u0026thinsp;0.003*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLOS (days)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6 (5,7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5(5,6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6(5,7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e18.947\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ea\u0026thinsp;\u0026lt;\u0026thinsp;0.001, b\u0026thinsp;=\u0026thinsp;0.109, c\u0026thinsp;=\u0026thinsp;0.028*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePre-admission course (days)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4 (3,6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3(2,7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4(3,5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4.538\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.075\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eClinical symptoms\u003c/b\u003e\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\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFever n(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e75(37.31%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e69(72.63%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e57(57.00%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e41.088\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ea\u0026thinsp;\u0026lt;\u0026thinsp;0.001, b\u0026thinsp;\u0026lt;\u0026thinsp;0.001, c\u0026thinsp;=\u0026thinsp;0.029*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCough n(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e200(99.50%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e87(92.05%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e97(97.00%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e13.781\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ea\u0026thinsp;\u0026lt;\u0026thinsp;0.001, b\u0026thinsp;=\u0026thinsp;0.074, c\u0026thinsp;\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWheezing n(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e77(38.31%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11(11.58%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20(20.00%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e26.805\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ea\u0026thinsp;\u0026lt;\u0026thinsp;0.001, b\u0026thinsp;\u0026lt;\u0026thinsp;0.001, c\u0026thinsp;=\u0026thinsp;0.187*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEnlarged tonsils n(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e44(21.89%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e73(76.84%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e50(50.00%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e83.240\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ea\u0026thinsp;\u0026lt;\u0026thinsp;0.001, b\u0026thinsp;\u0026lt;\u0026thinsp;0.001, c\u0026thinsp;\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSevere rates n(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e84(41.79%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e46(48.42%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e26(26.00%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e11.240\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ea\u0026thinsp;=\u0026thinsp;0.0283, b\u0026thinsp;=\u0026thinsp;0.007, c\u0026thinsp;=\u0026thinsp;0.001*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eComplications\u003c/b\u003e\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\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMyocardial damage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e68(33.83%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11(11.58%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e21(21.00%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e18.204\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ea\u0026thinsp;\u0026lt;\u0026thinsp;0.001, b\u0026thinsp;=\u0026thinsp;0.022, c\u0026thinsp;=\u0026thinsp;0.076*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSepsis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9(4.48%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e46(48.42%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15(15.00%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e84.919\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ea\u0026thinsp;\u0026lt;\u0026thinsp;0.001, b\u0026thinsp;=\u0026thinsp;0.001, c\u0026thinsp;\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eInflammatory markers\u003c/b\u003e\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\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIL-2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.09(0.91,1.28)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.99 (0.77,1.26)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.12(1.01,1.34)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e11.241\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.871\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIL-4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.9(0.79,0.97)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.86 (0.80,0.93)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.91(0.8,0.98)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4.732\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.094\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIL-6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.32(2.79,11.08)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15.28 (8.71,29.93)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.62(3.64,15.54)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e44.019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ea\u0026thinsp;\u0026lt;\u0026thinsp;0.001, b\u0026thinsp;=\u0026thinsp;0.169, c\u0026thinsp;=\u0026thinsp;0.002*\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\u003e6.3(2.71,15.13)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.55 (3.22,9.52)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8.81(5.64,17.29)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e14.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ea\u0026thinsp;=\u0026thinsp;0.963, b\u0026thinsp;=\u0026thinsp;0.014, c\u0026thinsp;=\u0026thinsp;0.320*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIL-17A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.31(0.8,1.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.88 (0.76,1.67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.29(0.78,1.73)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.689\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.430\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTNF-α\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.89(0.76,1.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.91 (0.76,1.09)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.9(0.76,1.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.546\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.761\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIFN-γ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.28(1.52,6.81)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.66 (1.89,11.22)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.95(2.34,9.65)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e12.266\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ea\u0026thinsp;=\u0026thinsp;0.035, b\u0026thinsp;=\u0026thinsp;0.178, c\u0026thinsp;=\u0026thinsp;0.61\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWBC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.4(6.4,11.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10.40 (7.15,12.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.8(5.8,10.35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e21.704\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ea\u0026thinsp;=\u0026thinsp;0.004, b\u0026thinsp;=\u0026thinsp;0.222, c\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ehs-CRP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.5(0.5,3.04)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.89 (0.5,7.39)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.29(0.5,7.99)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e44.666\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ea\u0026thinsp;\u0026lt;\u0026thinsp;0.001, b\u0026thinsp;=\u0026thinsp;0.013, c\u0026thinsp;=\u0026thinsp;0.018\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eNotes: \u003csup\u003ea\u003c/sup\u003eRSV group vs AdV group, \u003csup\u003eb\u003c/sup\u003eRSV group vs hMPV group, \u003csup\u003ec\u003c/sup\u003eAdV group vs hMPV group, *Significant statistical difference (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \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\u003eA Comparison of Clinical Symptoms and Inflammatory Markers in Three Types of VBCP\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\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=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRSV-VBCP(n\u0026thinsp;=\u0026thinsp;199)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAdV-VBCP(n\u0026thinsp;=\u0026thinsp;60)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ehMPV-VBCP(n\u0026thinsp;=\u0026thinsp;82)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eχ\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u003cem\u003e/H\u003c/em\u003e\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 \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDemographics and Hospitalization Status\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale n(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e134(67.34%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e36(60.00%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e57(58.76%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.517\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.284\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (months)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8 (3,12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25 (12,48)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e24(8,48)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e60.504\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ea\u0026thinsp;\u0026lt;\u0026thinsp;0.001, b\u0026thinsp;\u0026lt;\u0026thinsp;0.001, c\u0026thinsp;=\u0026thinsp;0.397*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLOS (days)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7 (6,8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5 (4,7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6(5,7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e23.147\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ea\u0026thinsp;\u0026lt;\u0026thinsp;0.001, b\u0026thinsp;=\u0026thinsp;0.364, c\u0026thinsp;=\u0026thinsp;0.017*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePre-admission course (days)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4 (3,6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5 (2,7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.5(3,7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e5.217\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.074\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eClinical symptoms\u003c/b\u003e\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\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFever n(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e66(33.17%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e40(66.67%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e41(42.27%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e23.181\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ea\u0026thinsp;\u0026lt;\u0026thinsp;0.001, b\u0026thinsp;=\u0026thinsp;0.008, c\u0026thinsp;=\u0026thinsp;0.047*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCough n(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e198(99.50%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e58(96.67%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e82(100%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e5.638\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.060\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWheezing n(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e65(32.66%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7(11.67%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e24(24.74%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e10.114\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.060\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEnlarged tonsils n(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e40(20.10%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e39(65.00%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e36(37.11%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e46.584\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ea\u0026thinsp;\u0026lt;\u0026thinsp;0.001, b\u0026thinsp;\u0026lt;\u0026thinsp;0.001, c\u0026thinsp;=\u0026thinsp;0.009*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSevere rates n(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e103(51.75%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26(43.33%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e32(39.02%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4.219\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.121\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eComplications\u003c/b\u003e\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\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMyocardial damage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e51(25.63%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8(13.33%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19(23.17%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3.955\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.138\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSepsis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11(5.53%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23(38.33%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6(7.32%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e49.947\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ea\u0026thinsp;\u0026lt;\u0026thinsp;0.001, b\u0026thinsp;=\u0026thinsp;0.567, c\u0026thinsp;\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eInflammatory markers\u003c/b\u003e\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\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIL-2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.1(0.86,1.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.14 (0.79,1.49)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.14(1.03,1.47)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e7.823\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ea\u0026thinsp;=\u0026thinsp;0.351, b\u0026thinsp;=\u0026thinsp;0.013, c\u0026thinsp;=\u0026thinsp;0.139*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIL-4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.88(0.78,0.97)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.9 (0.79,0.98)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.91(0.84,1.07)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e6.234\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ea\u0026thinsp;=\u0026thinsp;0.607, b\u0026thinsp;=\u0026thinsp;0.003, c\u0026thinsp;=\u0026thinsp;0.034*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIL-6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9.03(4.69,20.24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29.68 (7.04,50.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12.89(6.14,25.69)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e15.022\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ea\u0026thinsp;\u0026lt;\u0026thinsp;0.001, b\u0026thinsp;=\u0026thinsp;0.062, c\u0026thinsp;=\u0026thinsp;0.069*\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\u003e5.79(03.39,13.71)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9.01 (3.63,13.35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.18(3.82,16.48)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3.616\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.164\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIL-17A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.48(0.91,2.23)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.33(1.01,1.64)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.43(1.02,1.92)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.183\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTNF-α\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.93 (0.76,1.13)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.04 (0.85,1.78)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.98(0.76,1.14)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4.076\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.130\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIFN-γ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.89(1.69,6.39)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.56 (1.78,19.82)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.71(1.5,10.72)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e14.201\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ea\u0026thinsp;\u0026lt;\u0026thinsp;0.001, b\u0026thinsp;=\u0026thinsp;0.049, c\u0026thinsp;=\u0026thinsp;0.108*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWBC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10(7.8,12.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.5 (6.55,10.58)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.15(7.1,11.53)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e10.199\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ea\u0026thinsp;=\u0026thinsp;0.121, b\u0026thinsp;=\u0026thinsp;0.311, c\u0026thinsp;=\u0026thinsp;0.016*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ehs-CRP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.43(0.5,11.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.5 (0.5,2.71)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.54(0.5,9.12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e10.336\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ea\u0026thinsp;=\u0026thinsp;0.003, b\u0026thinsp;=\u0026thinsp;0.614, c\u0026thinsp;=\u0026thinsp;0.003*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eNotes: \u003csup\u003ea\u003c/sup\u003eRSV group vs AdV group, \u003csup\u003eb\u003c/sup\u003eRSV group vs hMPV group, \u003csup\u003ec\u003c/sup\u003eAdV group vs hMPV group, *Significant statistical difference (\u003cem\u003eP\u0026thinsp;\u0026lt;\u0026thinsp;0.05\u003c/em\u003e).\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e\n\u003ch3\u003eUnivariate analysis of RSV-VBCP, AdV-VBCP and hMPV-VBCP\u003c/h3\u003e\n\u003cp\u003eA total of 400 children with RSV pneumonia, 155 with AdV pneumonia, and 182 with hMPV pneumonia were included. Based on bacterial co-infection status, patients were divided into SVP and VBCP groups.\u003c/p\u003e \u003cp\u003eCompared with the RSV-SVP group, the RSV-VBCP group exhibited a significantly increased length of hospital stay, a higher rate of severe disease, as well as higher levels of IL-6, IL-17A, WBC count, and hs-CRP (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). No statistically significant differences were observed in other indicators (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05, Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eCompared with the AdV-SVP group, the AdV-VBCP group had a significantly longer prehospital duration and higher IL-6 levels (both \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), but significantly lower WBC count and hs-CRP levels (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Other indicators showed no statistical significance (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eCompared with the hMPV-SVP group, the hMPV-VBCP group demonstrated a significantly increased length of hospital stay, as well as elevated IL-6 levels and WBC count (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). No statistically significant differences were noted in other indicators (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eUnivariate analysis of RSV-VBCP\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\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=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRSV-SVP(n\u0026thinsp;=\u0026thinsp;201)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRSV-VBCP (n\u0026thinsp;=\u0026thinsp;199)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eχ2/U\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDemographics and Hospitalization Status\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale n(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e126(62.69%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e134(67.34%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.950\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.330\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (months)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9 (4,12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8 (3,12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.984\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLOS (days)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6 (5,7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7 (6,8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.274\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.001*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePre-admission course (days)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4 (3,6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4 (3,6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.824\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.410\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eClinical symptoms\u003c/b\u003e\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\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFever n(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e75(37.31%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e66(33.17%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.881\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.348\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCough n(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e200(99.50%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e198(99.45%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.994\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWheezing n(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e77(38.31%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e65(32.66%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.392\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.238\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEnlarged tonsils n(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e44(21.89%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e40(20.10%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.193\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.660\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eComplications\u003c/b\u003e\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\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMyocardial damage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e68(33.83%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e51(25.63%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.219\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.073\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSepsis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9(4.48%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11(5.53%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.232\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.630\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eInflammatory markers\u003c/b\u003e\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\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIL-2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.09(0.91,1.28)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.10(0.86,1.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.985\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIL-4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.90(0.79,0.97)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.88(0.78,0.97)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.390\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIL-6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.32(2.79,11.08)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9.03(4.69,20.24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001*\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\u003e6.30(2.71,15.13)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.79(3.39,13.71)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.421\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.674\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIL-17A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.31(0.8,1.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.48(0.91,2.23)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.303\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.021*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTNF-α\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.89(0.76,1.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.93 (0.76,1.13)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.912\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.362\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIFN-γ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.28(1.52,6.81)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.89(1.69,6.39)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.682\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWBC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.40(6.4,11.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10.00(7.8,12.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.918\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ehs-CRP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.50(0.5,3.04)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.43(0.5,11.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5.928\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e*Significant statistical difference (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05)\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eUnivariate analysis of AdV-VBCP\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\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=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAdV-SVP(n\u0026thinsp;=\u0026thinsp;95)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAdV-VBCP (n\u0026thinsp;=\u0026thinsp;60)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eχ\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u003cem\u003e/U\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDemographics and Hospitalization Status\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale n(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e56(58.95%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e36(60.00%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.017\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.897\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (months)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e36(12,60)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25 (12,48)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.450\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.147\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLOS (days)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5(5,6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5 (4,7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.480\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.631\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePre-admission course (days)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3(2,7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5 (2,7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.178\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.029*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eClinical symptoms\u003c/b\u003e\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\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFever n(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e69(72.63%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e40(66.67%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.627\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.428\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCough n(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e87(92.05%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e58(96.67%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.577\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.209\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWheezing n(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11(11.58%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7(11.67%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.627\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.428\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEnlarged tonsils n(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e73(76.84%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e39(65.00%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.453\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.501\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eComplications\u003c/b\u003e\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\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMyocardial damage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11(11.58%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8(13.33%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.105\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.746\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSepsis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e46(48.42%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23(38.33%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.515\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.218\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eInflammatory markers\u003c/b\u003e\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\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIL-2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.99 (0.77,1.26)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.14 (0.79,1.49)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.954\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.051\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIL-4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.86 (0.80,0.93)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.90 (0.79,0.98)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.326\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.185\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIL-6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15.28 (8.71,29.93)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29.68 (7.04,50.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.706\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.007*\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\u003e5.55 (3.22,9.52)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9.01 (3.63,13.35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.899\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.058\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIL-17A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.88 (0.76,1.67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.33(1.01,1.64)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.949\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.051\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTNF-α\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.91 (0.76,1.09)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.04 (0.85,1.78)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.840\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.066\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIFN-γ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.66 (1.89,11.22)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.56 (1.78,19.82)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.315\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.188\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWBC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10.40 (7.15,12.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.5 (6.55,10.58)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.320\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.020*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ehs-CRP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.89 (0.5,7.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.50 (0.5,2.71)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.540\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.011*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e*Significant statistical difference (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05)\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eUnivariate analysis of hMPV-VBCP\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\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=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ehMPV-SVP(n\u0026thinsp;=\u0026thinsp;100)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ehMPV-VBCP(n\u0026thinsp;=\u0026thinsp;82)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eχ\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u003cem\u003e/U\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDemographics and Hospitalization Status\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale n(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e65(65.00%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e57(69.51%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.415\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.519\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (months)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e24(10,48)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24(8,48)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.141\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.888\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLOS (days)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6(5,7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6(5,7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.008\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePre-admission course (days)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4(3,5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.5(3,7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.632\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.103\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eClinical symptoms\u003c/b\u003e\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\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFever n(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e57(57.00%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e41(50.00%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.888\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.346\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCough n(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e97(97.00%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e82(100%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.501\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.114\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWheezing n(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20(20.00%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24(29.27%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.111\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.146\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEnlarged tonsils n(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e50(50.00%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e36(43.90%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.672\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.412\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eComplications\u003c/b\u003e\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\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMyocardial damage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21(21.00%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19(23.17%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.124\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.725\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSepsis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15(15.00%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6(7.32%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.606\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.106\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eInflammatory markers\u003c/b\u003e\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\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIL-2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.12(1.01,1.34)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.14(1.03,1.47)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.113\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.266\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIL-4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.91(0.8,0.98)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.91(0.84,1.07)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.187\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.235\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIL-6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.62(3.64,15.54)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12.89(6.14,25.69)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.502\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001*\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\u003e8.81(5.64,17.29)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9.18(3.82,16.48)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.892\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.372\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIL-17A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.29(0.78,1.73)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.43(1.02,1.92)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.856\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.063\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTNF-α\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.90(0.76,1.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.98(0.76,1.14)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.432\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.152\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIFN-γ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.95(2.34,9.65)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.71(1.5,10.72)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.475\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.635\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWBC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.8(5.8,10.35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9.15(7.1,11.53)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.008*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ehs-CRP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.29(0.5,7.99)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.54(0.5,9.12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.017\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.309\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e*Significant statistical difference (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05)\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eMultivariable logistic regression analysis of RSV-VBCP, AdV-VBCP and hMPV-VBCP\u003c/h2\u003e \u003cp\u003eTo identify independent risk factors for viral-bacterial co-infection, variables with \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.1 in the univariate analysis were included in the multivariate logistic regression.\u003c/p\u003e \u003cp\u003eMultivariate logistic regression analysis identified elevated IL-6 (OR\u0026thinsp;=\u0026thinsp;1.031, 95% CI: 1.011\u0026ndash;1.052, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.002) and WBC (OR\u0026thinsp;=\u0026thinsp;1.062, 95% CI: 1.005\u0026ndash;1.122, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.032) as independent risk factors for RSV-VBCP (Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e). For AdV-VBCP, elevated IL-6 (OR\u0026thinsp;=\u0026thinsp;1.035, 95% CI: 1.015\u0026ndash;1.056, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.001) was independent risk factor (Table\u0026nbsp;\u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e7\u003c/span\u003e). Elevated IL-6 (OR\u0026thinsp;=\u0026thinsp;1.026, 95% CI: 1.006\u0026ndash;1.046, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.009) independently predicted hMPV-VBCP. No other indicators showed independent predictive value in any group (Table\u0026nbsp;\u003cspan refid=\"Tab8\" class=\"InternalRef\"\u003e8\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMultivariable logistic regression analysis of RSV-VBC\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=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRisk Factors\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eβ\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSE\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eWald\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eOR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIL6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.031\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9.484\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.031\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e(1.011,1.052)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.002*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMyocardial damage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.329\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.232\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.009\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.389\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e(0.882,2.189)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.156\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIL17A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.074\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.078\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.892\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.077\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e(0.924,1.255)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.345\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWBC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.028\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4.602\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.062\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e(1.005,1.122)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.032*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCRP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.014\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e(0.991,1.046)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.186\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003e*Significant statistical difference (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05)\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eβ: regression coefficient; SE: standard deviation; OR: odds ratio; CI: confidence interval\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab7\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMultivariable logistic regression analysis of AdV-VBCP\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=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRisk Factors\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eβ\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSE\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eWald\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eOR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIL2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.258\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.179\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.082\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.294\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e(0.912,1.837)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.149\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIL6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.035\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e11.797\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.035\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e(1.015,1.056)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.001*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIL10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.007\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.041\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.999\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e(0.985,1.013)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.839\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIL17A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.061\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.177\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.121\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.063\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e(0.752,1.504)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.728\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTNF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.047\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.115\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.049\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e(0.837,1.314)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.680\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWBC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.063\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.045\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.979\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.939\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e(0.859,1.025)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.160\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCRP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.034\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.649\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.967\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e(0.928,1.007)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.104\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003e*Significant statistical difference (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05)\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eβ: regression coefficient; SE: standard deviation; OR: odds ratio; CI: confidence interval\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab8\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 8\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMultivariable logistic regression analysis of hMPV-VBCP\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=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRisk Factors\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eβ\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSE\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eWald\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eOR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIL6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.026\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6.831\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.026\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e(1.006,1.046)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.009*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIL17A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.162\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.033\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.030\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e(0.749,1.416)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.855\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWBC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.066\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.042\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.421\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.068\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e(0.983,1.160)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.120\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003e*Significant statistical difference (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05)\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eβ: regression coefficient; SE: standard deviation; OR: odds ratio; CI: confidence interval\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003ePredictive value of inflammatory markers for VBCP\u003c/h3\u003e\n\u003cp\u003eROC curve analysis was performed to assess the predictive value of inflammatory markers for VBCP. Inflammatory markers with significant differences in univariate analysis were used as test variables, with SVP and VBCP as the dependent variables. The results showed that the AUC values of IL-6, IL-17A, WBC, hs-CRP, and their combined panel for predicting RSV-VBCP were 0.659, 0.566, 0.613, 0.667, and 0.689, respectively (Table\u0026nbsp;\u003cspan refid=\"Tab9\" class=\"InternalRef\"\u003e9\u003c/span\u003e, Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea). For AdV-VBCP prediction, the AUC values of IL-2, IL-6, IL-10, TNF-α, WBC, CRP, and their combined panel were 0.593, 0.629, 0.591, 0.587, 0.616, 0.616, and 0.705, respectively (Table\u0026nbsp;\u003cspan refid=\"Tab10\" class=\"InternalRef\"\u003e10\u003c/span\u003e, Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eb). The AUC values of IL-6, IL-17A, WBC, and their combined panel for predicting hMPV-VBCP were 0.651, 0.580, 0.614, and 0.681, respectively (Table\u0026nbsp;\u003cspan refid=\"Tab11\" class=\"InternalRef\"\u003e11\u003c/span\u003e, Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ec).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab9\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 9\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePredictive value of inflammatory markers for VBCP\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=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" 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=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" 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\u003eAUC\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e95CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCut off\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSensitivity\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSpecificity\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIL-6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.659\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e(0.606, 0.712)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e69.80%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e55.20%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCRP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.667\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e(0.615, 0.719)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e66.80%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e63.20%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWBC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.613\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e(0.558, 0.668)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e63.30%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e57.20%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIL-17A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.566\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e(0.510, 0.623)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e41.70%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e73.60%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCombination\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.689\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e(0.638, 0.741)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e/\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e67.80%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e61.70%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003e*Significant statistical difference (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05)\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab10\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 10\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePredictive value of inflammatory markers for AdV-VBCP\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=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" 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=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" 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\u003eAUC\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e95CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCut off\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSensitivity\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSpecificity\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIL-2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.593\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e(0.496, 0.689)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e35.00%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e89.50%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIL-6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.629\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e(0.528, 0.730)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e40.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e40.00%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e96.80%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\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=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.591\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e(0.496, 0.686)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e51.70%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e72.60%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCRP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.616\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e(0.531, 0.702)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e73.30%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e52.60%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWBC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.611\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e(0.520, 0.701)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e73.30%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e53.70%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTNF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.587\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e(0.496, 0.679)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e51.70%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e67.40%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCombination\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.705\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e(0.616, 0.794)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e/\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e41.70%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e95.80%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003e*Significant statistical difference (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05)\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab11\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 11\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePredictive value of inflammatory markers for hMPV-VBCP\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=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" 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=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" 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\u003eAUC\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e95CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCut off\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSensitivity\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSpecificity\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIL-6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.651\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e(0.571, 0.731)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e76.80%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e46.00%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIL-17A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e(0.497, 0.663)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e59.80%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e56.00%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWBC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.614\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e(0.532, 0.696)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e64.60%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e57.00%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCombination\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.681\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e(0.604, 0.759)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e/\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e53.70%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e77.00%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003e*Significant statistical difference (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05)\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e"},{"header":"Discussions","content":"\u003cp\u003eThis study systematically analyzed RSV, AdV, and hMPV infections in 2,315 children under 5 years with CAP in Zunyi, China. It is the first to reveal the epidemiological characteristics of these three viral pneumonias. The study examines the clinical impact of VBCP and differences in related inflammatory markers. It also explores independent risk factors for bacterial complications and assesses the predictive value of associated biomarkers.\u003c/p\u003e \u003cp\u003eThis study confirms RSV as the main viral cause of pediatric CAP in Zunyi, China. Its positivity rate (22.76%) is much higher than AdV (9.72%) and hMPV (9.84%), matching global pediatric CAP patterns [\u003cspan additionalcitationids=\"CR15\" citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Importantly, the three viruses have distinct seasonal and age distributions. RSV shows autumn-winter peaks and a minor spring peak, which differs from other Chinese regions [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e], showing notable regional variations. Infection risk drops with age and mainly affects infants in their first year, consistent with global trends [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. These findings underscore RSV\u0026rsquo;s threat to infants and the need for stronger local surveillance and protection during autumn and winter. In contrast, AdV infection occurs sporadically throughout the year, with little seasonal variation [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. AdV is more common in children aged 1\u0026ndash;5 years, with positivity rates consistent across domestic studies [\u003cspan additionalcitationids=\"CR23\" citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. This confirms its role as a major pediatric CAP pathogen in Zunyi. The disease burden should not be overlooked. Because of AdV\u0026rsquo;s biological traits [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e], its potential for ongoing transmission demands year-round clinical vigilance. Meanwhile, hMPV infection was highly concentrated from January to April. It had the highest positivity rate in children aged 1\u0026ndash;3 years. This age distribution aligns with hMPV\u0026rsquo;s immunopathogenesis [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e], but differs from that in other Chinese regions, such as Hebei, where peaks occur in summer and autumn [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. Taken together, these characteristic distributions reflect inter-viral differences in environmental stability, transmission routes, and host immune responses. This provides a basis for targeted regional prevention and control strategies.\u003c/p\u003e \u003cp\u003eTurning to clinical features, in the SVP group, RSV-infected children were the youngest and most prone to wheezing, consistent with global evidence that RSV is the primary pathogen of lower respiratory tract infections in infants. It's induced bronchial hyperreactivity and airway narrowing underpin the high wheezing incidence [\u003cspan additionalcitationids=\"CR31 CR32\" citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. In contrast, AdV-infected children were the oldest, with significantly shorter hospital stays than the RSV and hMPV groups\u0026mdash;potentially due to AdV\u0026rsquo;s predominance in preschoolers with relatively mature immune systems and more self-limiting disease courses. However, the AdV-SVP group also showed the highest incidence of fever and tonsillar enlargement, along with the highest sepsis risk, likely due to AdV\u0026rsquo;s direct epithelial lytic effect [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e] and systemic inflammation [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. Inflammatory marker data support this: AdV-SVP had significantly higher IL-6 and WBC levels than RSV-SVP and hMPV-SVP (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05, Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). As a key pro-inflammatory cytokine, elevated IL-6 correlates with infection severity and systemic inflammatory responses [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]; AdV may induce substantial IL-6 release via mechanisms such as TLR pathway activation [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e], thereby increasing fever and sepsis risk. Elevated WBC reflects the bone marrow\u0026rsquo;s rapid inflammatory response, further confirming AdV\u0026rsquo;s invasiveness.\u003c/p\u003e \u003cp\u003eA similar pattern is observed in the VBCP group. RSV-VBCP infection mainly affected the youngest age group and was associated with a high incidence of wheezing, confirming that RSV retains its typical clinical features even in the presence of coinfection. On the other hand, the AdV-VBCP group had the shortest hospital stay, but showed the highest rates of high fever, tonsillar enlargement, and sepsis. These trends were similar to those noted in the AdV-SVP group, indicating that AdV infection tends to induce severe systemic symptoms, regardless of bacterial coinfection. Notably, inflammatory markers showed a complex pattern. The AdV-VBCP group exhibited the highest IL-6 levels, which were significantly higher than those in the RSV-SVP and hMPV-SVP groups. This may indicate that AdV plays a dominant role in the inflammatory response, even in the presence of bacterial coinfection. Elevated IL-6 is an early warning indicator and is positively correlated with sepsis risk. However, the AdV-VBCP group had the lowest WBC and hs-CRP levels, a paradoxical finding that warrants further investigation. On one hand, this may indicate an altered immune response during AdV-bacterial coinfection. For example, bacterial infection might inhibit WBC mobilization or accelerate apoptosis. On the other hand, low hs-CRP, an acute-phase protein, may be related to specific AdV strains or host immune regulation. For instance, AdV encodes proteins that interfere with host inflammatory pathways and partly suppress CRP synthesis [\u003cspan additionalcitationids=\"CR42\" citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. Additionally, this discrepancy may reflect the influence of coinfecting bacterial types. Further subdivision of bacterial profiles is needed for verification.\u003c/p\u003e \u003cp\u003eBuilding upon these findings, this study focused on identifying risk factors for VBCP. Multivariate logistic regression consistently identified elevated IL-6 levels as a common independent risk factor for bacterial coinfection in RSV-, AdV-, and hMPV-associated pneumonia. IL-6 is a core pro-inflammatory cytokine. Marked elevation of IL-6 reflects the severity of infectious stress, but it can also impair host bacterial clearance through immunosuppression [\u003cspan additionalcitationids=\"CR45\" citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. This dual role creates a microenvironment favorable for secondary bacterial infection [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e, \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]. Thus, IL-6 is a key biomarker for predicting bacterial coinfection in pediatric pneumonia.\u003c/p\u003e \u003cp\u003eNotably, distinct pathogens exhibit both similarities and differences in inflammatory marker changes during progression to VBCP. Specifically, compared with their respective SVP groups, RSV, AdV, and hMPV all showed significantly elevated IL-6 in coinfections. This finding confirms that IL-6 is a common risk factor. However, other systemic inflammatory indicators showed different trends. For instance, RSV coinfections were associated with concurrent increases in IL-6, IL-17A, WBC, and hs-CRP, consistent with typical inflammatory profiles in bacterial infections. These laboratory findings may support prompt consideration of bacterial coinfection in clinical practice. In contrast, AdV coinfections showed a marked increase in IL-6 but significant reductions in WBC and hs-CRP, underscoring that these laboratory profiles may lead to underrecognition of inflammation and warrant consideration of AdV's effects when interpreting results. This may relate to AdV-mediated inhibition of bone marrow hematopoiesis or hepatic synthetic function [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]. Ultimately, these findings highlight unique and potentially misleading laboratory results in AdV coinfections, warranting heightened clinical caution in interpretation.\u003c/p\u003e \u003cp\u003eTo further clarify clinical application, ROC curve analysis assessed the predictive value of inflammatory markers for VBCP. Single inflammatory markers showed limited predictive utility for VBCP, whereas combining IL-6 with other indicators improved predictive accuracy. This approach has potential clinical relevance and may provide auxiliary decision support for the rational use of antibiotics.\u003c/p\u003e \u003cp\u003eClinically, this study found important distinctions in patient management. AdV infection, whether in SVP or VBCP, was associated with high fever, a high sepsis incidence, and sustained IL-6 elevation. This suggests that, in the management of pediatric pneumonia in the Zunyi region, heightened vigilance for systemic complications is warranted in AdV-infected cases, with timely monitoring of IL-6 and other inflammatory markers to assess potential bacterial coinfection. In contrast, RSV infection management prioritizes wheezing control, whereas hMPV typically presents with relatively mild clinical manifestations. While differences in inflammatory markers may help distinguish SVP from VBCP, comprehensive clinical judgment is essential to avoid misinterpretation based on a single indicator.\u003c/p\u003e \u003cp\u003eDespite these insights, this study has several limitations. First, as a single-center retrospective study, selection bias cannot be ruled out. Second, inflammatory markers were measured only at admission, precluding dynamic assessment of their temporal changes. Third, the dose-response relationship between viral load and bacterial coinfection risk was not evaluated, limiting understanding of how viral replication dynamics influence secondary infections. Future prospective multicenter studies will facilitate more precise risk assessment.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn summary, this study systematically characterized the distinct epidemiological features of RSV-, AdV-, and hMPV-associated pediatric pneumonia in the Zunyi region. Elevated IL-6 was confirmed as a common independent risk factor for VBCP across all three viral etiologies, with virus-specific risk factor profiles further identified. These findings provide evidence for targeted risk assessment and guide the development of personalized antibiotic management strategies for pediatric viral pneumonia in this region.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eRSV Respiratory syncytial virus\u003c/p\u003e \u003cp\u003eAdV Adenovirus\u003c/p\u003e \u003cp\u003ehMPV Human metapneumovirus\u003c/p\u003e \u003cp\u003eMP Mycoplasma pneumoniae\u003c/p\u003e \u003cp\u003eCAP Community Acquired Pneumonia\u003c/p\u003e \u003cp\u003eVBCP viral and bacterial co-infected pneumonia\u003c/p\u003e \u003cp\u003eSVP single virus pneumonia\u003c/p\u003e \u003cp\u003eRSV-SVP single Respiratory syncytial virus pneumonia\u003c/p\u003e \u003cp\u003eAdV-SVP single Adenovirus pneumonia pneumonia\u003c/p\u003e \u003cp\u003ehMPV-SVP single Human metapneumovirus pneumonia\u003c/p\u003e \u003cp\u003eRSV-VBCP Respiratory syncytial virus and bacterial co-infected pneumonia\u003c/p\u003e \u003cp\u003eAdV- VBCP Adenovirus and bacterial co-infected pneumonia\u003c/p\u003e \u003cp\u003ehMPV- VBCP Human metapneumovirus and bacterial co-infected pneumonia\u003c/p\u003e "},{"header":"Declarations","content":" \u003cp\u003e \u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e \u003cp\u003eThis study was approved by the Ethics Review Committee of the First People\u0026rsquo;s Hospital of Zunyi (Approval No. 2026-1-70). The Ethics Review Committee of the First People\u0026rsquo;s Hospital of Zunyi has waived the requirement for informed consent because this is a retrospective analysis, all patient information was anonymized, and there were no additional interventions or risks to participants in this study. This study was conducted in full accordance with the Declaration of Helsinki.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eConsent for publication\u003c/strong\u003e \u003cp\u003eNot applicable.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eCompeting interests\u003c/strong\u003e \u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003eClinical trial number\u003c/h2\u003e \u003cp\u003eNot applicable.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eAuthor details\u003c/strong\u003e \u003cp\u003e \u003csup\u003e1\u003c/sup\u003eDepartment of Laboratory Medicine, the First People\u0026rsquo;s Hospital of Zunyi (the Third Affiliated Hospital of Zunyi Medical University), Zunyi, People\u0026rsquo;s Republic of China\u003c/p\u003e \u003cp\u003e \u003csup\u003e2\u003c/sup\u003eThe First Clinical College of Zunyi Medical University, Zunyi, Guizhou, China\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eThis project was supported by the 2026 Guizhou Provincial Health Research Project (Clinical Research Category, NO. 2026GZWJKJXM0093).\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eConception and design: DWZ. Acquisition of data: DWZ, KTT, YZ, JJM and HY. Analysis and interpretation of data: DWZ and KTT. Drafting of the article: DWZ. Critical revision of the article: DWZ and HZ. Writing\u0026mdash;review \u0026amp; editing: DWZ. Study supervision: DWZ. and HZ. All authors have read and agreed to the published version of the manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgements\u003c/h2\u003e \u003cp\u003eNot applicable.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe datasets used or analysed during this study available from the corresponding author on reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eGlobal. regional, and national incidence and mortality burden of non-COVID-19 lower respiratory infections and aetiologies, 1990\u0026ndash;2021: a systematic analysis from the Global Burden of Disease Study 2021 [J]. 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Jpn Dent Sci Rev. 2024;60:44\u0026ndash;52.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTian X, Li X, Qiu S, et al. Abnormal liver function in children hospitalized with acute respiratory infection of adenoviruses: a retrospective study [J]. Virol Sin; 2023.\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":"bmc-infectious-diseases","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"infd","sideBox":"Learn more about [BMC Infectious Diseases](http://bmcinfectdis.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/infd","title":"BMC Infectious Diseases","twitterHandle":"#bmcinfectdis","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Respiratory Syncytial Virus, Adenovirus, Human Metapneumovirus, Community Acquired Pneumonia, Risk factors","lastPublishedDoi":"10.21203/rs.3.rs-8884580/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8884580/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground \u003c/strong\u003eCommunity acquired pneumonia (CAP) is a major cause of illness and death in children under five worldwide. This study characterized the epidemiology of RSV/AdV/hMPV associated CAP in Zunyi children and identified bacterial co-infection risk factors, to provide a scientific basis for individualized pediatric CAP management in this region.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods \u003c/strong\u003eA retrospective analysis of clinical data from 2315 children with CAP admitted to Zunyi First People's Hospital (Third Affiliated Hospital of Zunyi Medical University) between January and December 2025 was performed. Univariate and multivariate logistic regression analyses identified risk factors for bacterial co-infection, and receiver operating characteristic (ROC) curve analysis evaluated the predictive value of inflammatory markers.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults \u003c/strong\u003eA total of 2,315 children with CAP were enrolled. The RSV positivity rate (22.76%) was significantly higher than that for AdV (9.72%) and hMPV (9.84%, \u003cem\u003ep\u003c/em\u003e\u0026lt;0.05). Single virus pneumonia (SVP) and viral and bacterial co-infected pneumonia (VBCP) were the main types for all three viruses. RSV infection peaked in autumn and winter, with the highest positivity in children under 1 year. AdV infection occurred year-round and was most common in children aged 1–5 years. hMPV infection was concentrated from January to April, predominantly in children aged 1–3 years. Children with RSV pneumonia were the youngest and had obvious wheezing. Children with AdV pneumonia had the highest rates of high fever, tonsillar enlargement, and sepsis, the shortest hospital stay, and significantly higher IL-6 and WBC levels. Multivariate logistic regression showed that elevated IL-6 was an independent risk factor for RSV-associated VBCP (OR=1.031, 95% CI: 1.011–1.052, \u003cem\u003eP\u003c/em\u003e=0.002), AdV-associated VBCP (OR=1.035, 95% CI: 1.015–1.056, \u003cem\u003eP\u003c/em\u003e=0.001), and hMPV-associated VBCP (OR=1.026, 95% CI: 1.006–1.046, \u003cem\u003eP\u003c/em\u003e=0.009).\u003c/p\u003e\n\u003cp\u003eFor RSV-associated VBCP, WBC was an additional independent risk factor (OR=1.062, 95% CI: 1.005–1.122, \u003cem\u003eP\u003c/em\u003e=0.032). No other indicators exhibited independent predictive value. ROC curve analysis demonstrated that combined inflammatory marker detection had predictive value for VBCP.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions \u003c/strong\u003eRSV, AdV, and hMPV cause different patterns of illness and inflammation in children with pneumonia in Zunyi. When these viruses co-occur with bacteria, the disease becomes more severe, and the risks vary by virus. High IL-6 levels are a shared, early warning sign of viral and bacterial co-infection for all three viruses.\u003c/p\u003e","manuscriptTitle":"Epidemiology, Bacterial Coinfection Risk Factors, and Inflammatory Markers in Children with RSV, AdV, and hMPV Pneumonia in Zunyi, China","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-03-08 14:54:31","doi":"10.21203/rs.3.rs-8884580/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-04-09T09:48:45+00:00","index":"","fulltext":""},{"type":"reviewerAgreed","content":"143033050559523191189820917217633144310","date":"2026-04-08T03:24:10+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"126506122539666735066433083328432463822","date":"2026-04-06T15:10:50+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"107870530239612078333907344371408834704","date":"2026-04-06T10:20:25+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-05T14:03:40+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"256740940483669432954948637802617392209","date":"2026-04-05T05:28:37+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-03-30T02:55:05+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"47373220761358774868583881077142648636","date":"2026-03-30T01:03:30+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"292954028325852098883335668332332995198","date":"2026-03-29T15:01:38+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-03-26T15:53:01+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"293478166057031386226277077329031161099","date":"2026-03-16T18:47:05+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"43133823774737270036439449135923772757","date":"2026-03-16T00:36:34+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"199739177248600646510489645171195237061","date":"2026-03-15T16:04:44+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-02-26T15:55:26+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-02-24T09:30:15+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-02-24T02:25:21+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-02-24T02:24:01+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Infectious Diseases","date":"2026-02-15T07:59:25+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-infectious-diseases","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"infd","sideBox":"Learn more about [BMC Infectious Diseases](http://bmcinfectdis.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/infd","title":"BMC Infectious Diseases","twitterHandle":"#bmcinfectdis","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"5f9a6475-5696-49b9-8ab5-f40b6d3239e5","owner":[],"postedDate":"March 8th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-05-15T01:08:14+00:00","versionOfRecord":[],"versionCreatedAt":"2026-03-08 14:54:31","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8884580","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8884580","identity":"rs-8884580","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}