Comparison of mortality and cardiovascular complications due to COVID-19, RSV, and influenza in hospitalized children and young adults

Comparison of mortality and cardiovascular complications due to COVID-19, RSV, and influenza in hospitalized children and young adults | 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 Comparison of mortality and cardiovascular complications due to COVID-19, RSV, and influenza in hospitalized children and young adults Sagya Khanal, Bishes Khanal, Fu-Sheng Chou, Anita J Moon-Grady, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5081257/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 28 Nov, 2024 Read the published version in BMC Cardiovascular Disorders → Version 1 posted 4 You are reading this latest preprint version Abstract Background Respiratory viruses are linked to cardiovascular complications. We aim to compare cardiovascular complications due to COVID-19, influenza and RSV. Methods We analyzed cross-sectional data from hospitalized children and young adults (≤ 20 years) from 2020 and 2021 using National Inpatient Sample(NIS). We included individuals hospitalized for COVID-19, RSV, and influenza, and weighted data were used to compare cardiovascular complications. Results Of 212,655 respiratory virus admissions, 85,055 were from COVID-19, 103,185 were from RSV, and 24,415 were from influenza. Myocarditis was higher in COVID-19 [0.9%,n = 740] as compared to influenza [0.2%,n = 55] and RSV [0.1%,n = 65]. In the adjusted logistic regression, the odds of myocarditis was 61% lower in influenza [aOR = 0.39 (0.20–0.76), P = 0.006], and 85% lower in RSV [aOR = 0.15 (0.07–0.34) P < 0.001] as compared to COVID-19. Heart block was higher in COVID-19 [0.8%,n = 690] versus influenza [0.5%,n = 110] and RSV [0.2%,n = 205]. After adjusting for confounders for heart block, compared to COVID-19, the odds of heart block was 49% lower in RSV [aOR = 0.51 (0.33–0.80), P = 0.004] but no statistically significant difference in influenza [aOR = 0.79 (0.48–1.31), P = 0.374] was seen. Tachyarrhythmias, cardiac arrest, and in-hospital mortality showed no differences after adjusting for covariates. Conclusion Individuals with COVID-19 infection are more likely to develop cardiovascular complications compared to influenza and RSV, highlighting the need for higher index of suspicion and prompt treatment, as well as steps to limit infection and transmission of this virus in children. COVID-19 cardiovascular complications hospital outcomes influenza mortality RSV Figures Figure 1 Figure 2 Background Respiratory viral infections represent a significant public health challenge, contributing substantially to both morbidity and mortality [ 1 ]. Common respiratory viral pathogens include adenovirus, enterovirus, human coronavirus, human metapneumovirus, rhinovirus (RV), influenza, parainfluenza, and respiratory syncytial virus (RSV) [ 2 ]. Notably, COVID-19, influenza, and RSV exhibit similar clinical presentations and share common transmission routes through droplets and aerosols, which complicates their clinical differentiation [ 1 ]. Respiratory syncytial virus (RSV) is the leading cause of hospital admissions in infants and young children, [ 3 ] while influenza and SARS-CoV-2 are more prevalent in older children [ 4 ]. Previous studies have established a connection between respiratory viral infections and major cardiovascular complications [ 5 – 18 ]. RSV infection has been associated with myocarditis, [ 5 ] ventricular tachycardia, [ 6 , 7 ] and heart block [ 8 – 9 ] Influenza infection is a recognized cause of myopericarditis [ 10 – 12 ] and is associated with an elevated risk of acute heart failure and acute ischemic heart disease [ 13 ]. SARS-CoV-2 infection manifests a wide range of clinical presentations, including myocardial involvement such as myocarditis, dysrhythmias, heart failure, myocardial infarction, and thromboembolic events [ 14 – 18 ]. The emergence of SARS-CoV-2 in 2019 led to a significant increase in hospitalizations across all age groups and was associated with a high risk of in-hospital mortality [ 19 ]. Although cardiovascular manifestations of respiratory viral infections have been documented, [ 5 , 6 , 8 , 10 , 13 , 14 , 18 ] they have largely been reported separately. No study has systematically compared the clinical complications and outcomes associated with COVID-19, influenza, and RSV infections in the pediatric population. This study aims to compare in-hospital mortality and major cardiovascular complications among hospitalized children and young adults with COVID-19, influenza, and RSV infections. Methods Study population and variables This retrospective study utilized hospital discharge records from the National Inpatient Sample (NIS) for the years 2020 and 2021. The NIS is a component of the Healthcare Cost and Utilization Project (HCUP), funded by the Agency for Healthcare Research and Quality (AHRQ) [ 20 ]. The NIS sampling frame encompasses data from 48 statewide data organizations, including 47 states plus the District of Columbia, representing approximately 98% of the U.S. population. It includes a stratified 20% sample of discharges from U.S. community hospitals, excluding long-term acute care hospitals and rehabilitation facilities. The NIS ensures patient confidentiality because of the de-identified nature of data. A detailed description of the database is available on the HCUP website [ 20 ]. Our study focused on individuals aged 20 years or younger who were hospitalized with a diagnosis of COVID-19, influenza, or respiratory syncytial virus (RSV). The International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM), was utilized to identify hospitalized children diagnosed with COVID-19, influenza, RSV, and other variables studied. To minimize confounding effects, we excluded individuals with co-respiratory infections (i.e., those diagnosed with more than one of the studied viral infections: COVID-19, influenza, or RSV) and those who were transferred between hospitals to prevent double counting. (Fig. 1 ). To identify COVID-19 cases within the database, we utilized the ICD-10-CM code B97.29 for records from January 1 to March 31, 2020, and U07.1 for records from April 1, 2020, onward [ 21 ]. For RSV infection, the following ICD-10-CM codes were employed: B97.4, J12.1, J20.5, and J21.0. We excluded cases of bronchiolitis that did not have a corresponding RSV diagnosis. We excluded admission that did not have complete data for analysis. Severity, used as a variable in the analysis, denotes the severity of illness has four categories: 1) minor loss of function, which includes cases with no comorbidity or complications; 2) moderate loss of function; 3) major loss of function; and 4) extreme loss of function [ 22 ]. Outcome variables The primary outcomes were in-hospital mortality and major cardiovascular complications associated with COVID-19, influenza, or RSV infection. For the purposes of analysis, major cardiovascular complications were myocarditis, tachyarrhythmia, heart block, sudden cardiac arrest, and the need for extracorporeal membrane oxygenation (ECMO). Additionally, we compared disease severity and length of hospital stay across the study groups. The ICD-10 codes corresponding to the diagnoses and procedures analyzed in this study are presented in supplementary table 1 . Statistical analysis We conducted both descriptive and inferential analyses, followed by logistic regression modeling, to evaluate the data. Given that the NIS is a complex survey dataset, we incorporated clusters, strata, and weighting as recommended by the Healthcare Cost and Utilization Project (HCUP) to generate national estimates and ensure the accuracy of the statistical analyses. Continuous variables, such as age, length of stay, and disease severity, were reported as medians with interquartile ranges. Categorical variables were analyzed using weight-adjusted chi-square tests. For multivariable analysis, we selected variables with reliable and consistent ICD-10 codes. Initially, univariable regression analysis was performed for variables of interest, followed by multivariable regression analysis that accounted for additional covariates, including age group, sex, asthma/reactive airway disease, prematurity, obesity, diabetes, congenital heart disease, chromosomal anomalies, ZIP code of household neighborhood, and disease severity. These covariates were identified through a comprehensive literature review and clinical expertise and were finalized prior to conducting the analyses. The patient’s ZIP code was categorized into quartiles based on the estimated median household income of residents within that ZIP code, with quartiles representing the range from the lowest to highest income, indicating the poorest to wealthiest populations. All statistical analyses were conducted using Stata statistical software (version 15.1) and R (version 4.3) with RStudio (version 1.2). Figures were generated using the ggplot2 package in R [ 23 ]. Results Of 212,655 respiratory virus admissions, 85,055 were from COVID-19, 24,415 were from influenza, and 103,185 were from RSV. Among these, 46,845 (55.1%) of the COVID-19 cases, 11,290 (46.3%) of the influenza cases, and 46,445 (45.0%) of the RSV cases were female patients. The median age of children hospitalized with COVID-19 was 15 years (IQR: 3–19), with influenza it was 4 years (IQR: 1–9), and with RSV it was under 1 year (IQR: 0–1). COVID-19 admissions were more prevalent among young adults (11–20 years), whereas influenza and RSV admissions were more common among younger children (0–2 years). Among children with underlying medical conditions, hospitalized children and young adults with a history of asthma/reactive airway disease were more common in those with influenza (21.6%, n = 5,265), followed by COVID-19 (14.4%, n = 12,260) and RSV (13.6%, n = 14,040). Children with obesity were more likely to have COVID-19 (14.2%, n = 12,095) compared to influenza (2.1%, n = 510) and RSV (0.5%, n = 485). Additionally, prematurely born children were more likely to have RSV (4.5%, n = 4,660) compared to COVID-19 (1.5%, n = 1,280) and influenza (2.1%, n = 505) (Table 1 ). Table 1 Characteristics of patients, comorbid conditions, and complications due to COVID-19, influenza and RSV. Total Respi virus cases: 212,655 Variables Respiratory virus with total number(percentages) COVID-19 Influenza RSV P Value Total number (n) 85,055 24,415 103,185 N/A Female 46845 (55.1) 11290 (46.3) 46445 (45.0) < 0.001 Age, years (median [IQR]) 15 [3–19] 4 [1–9] 0 [0–1] < 0.001 Age group (year) < 0.001 0–2 20405 (24.0) 10015 (41.0) 91700 (88.9) 3–5 4455 (5.2) 4265 (17.5) 7820 (7.6) 6–10 7235 (8.5) 4805 (19.7) 2150 (2.1) 11–20 52960 (62.3) 5330 (21.8) 1515 (1.5) Zip Code* < 0.001 1st quartile 30980 (36.9) 8365 (34.6) 32290 (31.6) 2nd quartile 21540 (25.6) 6095 (25.2) 26500 (25.9) 3rd quartile 18870 (22.5) 5695 (23.5) 24180 (23.6) 4th quartile 12655 (15.1) 4045 (16.7) 19340 (18.9) Comorbid conditions CHD a 2530 (3.0) 970 (4.0) 4985 (4.8) < 0.001 Obesity 12095 (14.2) 510 (2.1) 485 (0.5) < 0.001 Diabetes 5085 (6.0) 710.0 (2.9) 270 (0.3) < 0.001 Chromosomal Anomalies 2180 (2.6) 730 (3.0) 2250 (2.2) 0.004 Asthma/reactive airway 12260 (14.4) 5265 (21.6) 14040 (13.6) < 0.001 Prematurity 1280 (1.5) 505 (2.1) 4660 (4.5) < 0.001 Cardiovascular Complications Myocarditis 740 (0.9) 55 (0.2) 65 (0.1) < 0.001 Tachyarrhythmia 1290 (1.5) 235 (1.0) 635 (0.6) < 0.001 Heart Block 690 (0.8) 115 (0.5) 205 (0.2) < 0.001 Sudden Cardiac Arrest 310 (0.4) 50 (0.2) 135 (0.1) < 0.001 ECMO b 170 (0.2) 55 (0.2) 45 (0.0) < 0.001 Length of stay (LOS) (Median[IQR]) in days 3 [2–5] 2 [2–4] 3 [2–4] < 0.001 Disease Severity (Median[IQR]) C 3 [2–3] 2 [1–3] 2 [1–3] < 0.001 In-hospital mortality 580 (0.7) 65 (0.3) 130 (0.1) < 0.001 a Congenital Heart Disease b Extracorporeal membrane oxygenation c Severity illness subclass according to loss of function *Zip Code: Neighborhood ZIP Codes classify the estimated median household income of residents in a patient's ZIP Code into four quartiles. The quartiles are identified from lowest to highest, indicating the lowest-income neighborhoods to highest-income neighborhoods. We performed univariable and multivariable logistic regression analyses to compare in-hospital mortality and major cardiovascular complications across COVID-19, influenza, and RSV cases. Multivariable logistic regression was performed after adjusting for confounding factors including age group, gender, prematurity, obesity, diabetes, asthma, congenital heart disease, chromosomal anomalies, and disease severity. Using COVID-19 as the reference group, we assessed the risk of complications associated with influenza and RSV. The in-hospital mortality rate was 0.7% (n = 580) for COVID-19, 0.3% (n = 65) for influenza, and 0.1% (n = 130) for RSV. Descriptive analysis indicated higher in-hospital mortality for COVID-19 compared to influenza and RSV. However, when adjusted for covariates, the differences in in-hospital mortality were not statistically significant, with an adjusted odds ratio (aOR) of 0.92 (95% CI: 0.49–1.71, P = 0.799) for influenza and 0.67 (95% CI: 0.39–1.14, P = 0.142) for RSV, relative to COVID-19 (Table 2 ). In this model, those with diabetes and higher disease severity were associated with increased risk of in-hospital mortality. The descriptive statistics table with individuals who died vs those who survived are presented in Table 3 . Table 2 Logistic Regression of in-hospital mortality, cardiovascular and non-cardiovascular complications. (Taking COVID-19 as reference) Complications Respiratory viruses Unadjusted Odds Ratio (95% CI) P value Adjusted Odds Ratio (95% CI) P value In- hospital Mortality Reference (COVID-19) - Influenza 0.38 (0.21–0.69) 0.01 0.92 (0.49–1.71) 0.799 RSV 0.18 (1.11–0.28) 0.00 0.67 (0.39–1.14) 0.142 Cardiovascular Complications Myocarditis Reference (COVID-19) - Influenza 0.25 (0.14–0.47) < 0.001 0.39 (0.20–0.76) 0.006 RSV 0.049(0.02–0.09) < 0.001 0.15 (0.07–0.34) < 0.001 Heart Block Reference (COVID-19) - Influenza 0.57 (0.37–0.90) 0.015 0.79 (0.48–1.31) 0.374 RSV 0.24 (0.17–0.34) < 0.001 0.51 (0.33–0.80) 0.004 Tachyarrhythmia Reference (COVID-19) - Influenza 0.63 (0.46–0.86) 0.004 1.21 (0.85–1.74) 0.277 RSV 0.40 (0.32–0.49) < 0.001 1.15 (0.84–1.59) 0.366 Sudden Cardiac arrest Reference (COVID-19) - Influenza 0.56 (0.28–1.09) 0.09 1.14 (0.55–2.35) 0.722 RSV 0.35 (0.22–0.56) < 0.001 0.85 (0.49–1.47) 0.569 Table 3 Stratification of respiratory virus cases and complications by those who died vs those who survived. Variables Died (number and percentages) P-value No Yes Total number 211829 775 N/A Female 104235 (49.2) 315 (40.6) 0.039 Age (median[IQR]) 2 [0–12] 15 [2–19] < 0.001 Age group (in years) < 0.001 0–2 121889 (57.54) 215 (27.74) 3–5 16504 (7.79) 30 (3.87) 6–10 14105 (6.66) 80 (10.32) 11–20 59329 (28.01) 450 (58.06) Zip Code* 0.073 1st quartile 71320 (34) 290 (38.2) 2nd quartile 53945 (25.7) 185 (24.3) 3rd quartile 48525 (23.1) 210 (27.6) 4th quartile 35960 (17.1) 75 (9.9) Respiratory viruses < 0.001 COVID-19 84445 (39.9) 580 (74.8) Influenza 24350 (11.5) 65 (8.4) RSV 103035 (48.6) 130 (16.8) Comorbid conditions CHD a 8400 (4.0) 85 (11.0) < 0.001 Obesity 12950 (6.1) 140 (18.1) < 0.001 Diabetes 5990 (2.8) 70 (9.0) < 0.001 Chromosomal Anomalies 5115 (2.4) 45 (5.8) 0.006 Asthma 31430 (14.8) 130 (6.8) 0.50 Prematurity 6425 (3.0) 20 (2.6) 0.75 Cardiovascular Complications Myocarditis 825 (0.4) 15 (1.9) 0.002 Tachyarrhythmia 2060 (1.0) 95 (12.3) < 0.001 Heart Block 995 (0.5) 15 (1.9) < 0.001 Sudden Cardiac Arrest 255 (0.1) 235 (30.3) < 0.001 ECMO b 165 (0.1) 125 (16.1) < 0.001 In-hospital mortality 0 (0) 775 (100) < 0.001 a Congenital Heart Disease b Extracorporeal membrane oxygenation c Severity illness subclass according to loss of function *Zip Code: Neighborhood ZIP Codes classify the estimated median household income of residents in a patient's ZIP Code into four quartiles. The quartiles are identified from lowest to highest, indicating the lowest-income neighborhoods to highest-income neighborhoods. Regarding cardiovascular complications, myocarditis was more frequent in COVID-19 cases (0.9%, n = 740) compared to influenza (0.2%, n = 55) and RSV (0.1%, n = 65) cases in descriptive analyses. The risk of myocarditis was 61% lower in influenza with an adjusted odds ratio (aOR) of 0.39 (95% CI: 0.20–0.76, P = 0.006) and 85% lower in RSV with an adjusted odds ratio (aOR) of 0.15 (95% CI: 0.07–0.34, P < 0.001) compared to COVID-19 (Table 2 and Fig. 2 ). The descriptive statistics table with individuals with myocarditis vs those without myocarditis are presented in Table 3 . Similarly, the risk of heart block was 49% lower in RSV with an adjusted odds ratio (aOR) of 0.51 (95% CI: 0.33–0.80, P = 0.004) compared to COVID-19, though it was not statistically significant for influenza (aOR 0.79, 95% CI: 0.48–1.31, P = 0.374). While descriptive analyses suggested that tachyarrhythmia and sudden cardiac arrest were more common in COVID-19, these findings were not statistically significant in the multivariable logistic regression models (Table 2 ). The median length of hospital stay was 3 days (IQR: 2–5) for COVID-19, 2 days (IQR: 2–4) for influenza, and 3 days (IQR: 2–4) for RSV (Table 1 ). Discussion Using the NIS 2020–2021 database, we report the following major findings. First, the in-hospital mortality rates were similar for COVID-19, influenza, and RSV infections requiring hospitalization. Second, the risk of cardiovascular complications, particularly myocarditis and heart block, were more common in COVID-19. The similarity in in-hospital mortality rates among these respiratory viruses, after adjusting for confounders, aligns with findings from previous studies. For instance, a study conducted in Mexico by Laris-González et al. reported comparable in-hospital mortality in multivariable analysis between COVID-19 and influenza [ 24 ]. Hedberg et al., in their study based in Sweden, compared clinical phenotypes and outcomes of different respiratory viral infections in both pediatric (≤ 15 years) and adult cohorts. Their results indicated that in the adult cohort, in-hospital mortality was significantly higher for COVID-19 compared to influenza (aHR 4.43, 95% CI: 3.51 to 5.59) and RSV (aHR 3.81, 95% CI: 2.72 to 5.34). However, in the pediatric cohort, the comparison of in-hospital mortality (30 days and 90 days) was similar [ 25 ]. The milder course of COVID-19 in young children and infants, compared to adults, may partially explain the similar in-hospital mortality rates observed for COVID-19, influenza, and RSV [ 26 ]. The risk of myocarditis was notably higher in COVID-19 compared to influenza and RSV. This was particularly evident in young adults aged 11–20 years, with obesity identified as a common comorbid condition (Table 4 ). The higher prevalence of myocarditis in COVID-19 may be attributed to the distinct pathophysiological mechanisms and immune responses triggered by SARS-CoV-2. As a cardiotropic virus, SARS-CoV-2 significantly impacts myocardial tissue and the cardiac conduction system, causing myocarditis by binding to ACE2 (Angiotensin-Converting Enzyme 2) receptors expressed in myocardial cells, pericytes, and pneumocytes, leading to direct cellular damage and uncontrolled inflammatory responses [ 27 ]. Consistent with our findings, data from the Centers for Disease Control and Prevention (CDC) indicated that myocarditis was 16 times more prevalent in COVID-19 patients than in those without the infection, particularly among older children, younger adolescents ( 75 years) [ 28 ]. In a subset analysis using NIS 2020 data, we previously compared clinical outcomes in myocarditis cases associated with COVID-19 versus non-COVID-19 cases and found that while the risk of mortality was similar between the two groups, acute kidney injury was more common in COVID-19-associated myocarditis (aOR = 1.9, 95% CI: 1.1–3.3, P = 0.02). In that study, rates of tachyarrhythmias, heart blocks, sudden cardiac arrest, and ECMO use were similar between the two groups [ 29 ]. Table 4 Stratification of respiratory virus cases and complications by those with and without myocarditis. Variables Myocarditis (number and percentages) P-value No Yes Total number 211815 840 N/A Female 104300 (49.2) 280 (33.33) < 0.001 Age (median[IQR]) 2 [0–12] 11 [6–17] < 0.001 Age group (in years) < 0.001 0–2 12010 (57.6) 110 (13.1) 3–5 16470 (7.8) 70 (8.338) 6–10 13970 (6.6) 220 (26.2) 11–20 59365 (28.0) 440 (52.4) Zip Code* 0.92 1st quartile 71355 (34.0) 280 (33.5) 2nd quartile 53925 (25.7) 210 (25.1) 3rd quartile 48560 (23.2) 185 (22.2) 4th quartile 35880 (17.1) 160 (19.2) Respiratory viruses COVID-19 84315 (39.8) 740 (88.1) < 0.001 Influenza 24360 (11.5) 55 (6.5) 0.046 RSV 103140(48.7) 45 (5.4) < 0.001 Comorbid conditions CHD a 8455 (4.0) 30 (3.6) < 0.001 Obesity 12990 (6.1) 100 (11.9) 0.001 Diabetes 6050 (2.9) 15 (1.8) 0.40 Chromosomal Anomalies 5150 (2.439) 10 (1.2) 0.29 Asthma 31430 (14.8) 135 (16.1) 0.67 Prematurity 6440 (3.04) 5 (0.6) 0.75 Cardiovascular complications Tachyarrhythmia 2055 (1.0) 105 (12.5) < 0.001 Heart Block 965 (0.5) 45 (5.4) < 0.001 Sudden Cardiac Arrest 480 (0.23) 15 (1.8) < 0.001 ECMO b 265 (0.13) 25 (3.0) < 0.001 In-hospital mortality 760 (0.4) 15 (1.8) 0.002 a Congenital Heart Disease b Extracorporeal membrane oxygenation c Severity illness subclass according to loss of function *Zip Code: Neighborhood ZIP Codes classify the estimated median household income of residents in a patient's ZIP Code into four quartiles. The quartiles are identified from lowest to highest, indicating the lowest-income neighborhoods to highest-income neighborhoods. Studies on the risk of heart block associated with various respiratory viral infections have been conducted separately. In this study, we compared the risk of heart block across COVID-19, influenza, and RSV. We found that heart block was more common in COVID-19 compared to RSV, although the difference was not statistically significant when compared to influenza. The exact mechanism by which COVID-19 leads to heart block remains unclear. Some studies suggest that heart block may result from direct disruption of the heart's electrical conduction system by the SARS-CoV-2 virus. Additionally, it has been proposed that direct viral infiltration of cardiomyocytes via angiotensin converting enzyme 2 (ACE2) receptors, followed by systemic inflammation, may contribute to cardiac injury [ 30 ]. During the 2009 influenza pandemic, Ukimura et al. reported four cases of influenza-related complete heart block (CHB) requiring temporary pacing, highlighting the potential for severe cardiac complications like heart block during respiratory viral infections [ 31 ]. Few studies seem to investigate and compare heart block due to these respiratory viruses. This gap in the literature highlights the necessity of further exploration and understanding of this specific complication of viral infection in children. Our study's main strength lies in the use of NIS 2020–2021 data, which provides a large sample size based on population sampling of hospitalized pediatric populations with respiratory viral infections. However, there are limitations to this approach. The NIS database utilizes hospital discharge records from all HCUP-participating hospitals, excluding rehabilitation and long-term acute care hospitals. It includes only inpatient records, so the findings may not be generalizable to outpatient settings or patients who were transferred between hospitals. The database relies on ICD-10 codes for diagnosing respiratory infections, which may lack detailed information on the procedures and tests used for diagnoses. Additionally, as with any medical and billing database, the NIS may contain incorrect or missing information, leading to potential inaccuracies. This study did not include cases with co-respiratory viral infections (e.g., COVID-19 + influenza, Influenza + RSV, etc.). Furthermore, we were unable to assess the influence of vaccination (RSV, COVID-19, Influenza) on clinical outcomes, as vaccination status is not captured in the database. Conclusions In conclusion, our findings indicate that children with COVID-19 infections are at increased risk of cardiovascular complications, including myocarditis and heart block. We recommend measures to prevent COVID-19 infection and to anticipate and promptly manage these cardiovascular complications in risk-prone children especially those with underlying comorbid conditions to prevent mortality. Abbreviations COVID-19 Corona virus disease of 2019 RSV Respiratory syncytial virus RV Rhino virus SARS-CoV-2 Severe acute respiratory syndrome coronavirus 2 NIS National inpatient sample HCUP Healthcare cost and utilization project AHRQ Agency for healthcare research and quality ICD-10-CM International classification of diseases, tenth revision, clinical modification ECMO Extracorporeal membrane oxygenation IQR Interquartile range CI Confidence interval aOR adjusted Odds ratio aHR adjusted Hazard’s ratio ACE2 Angiotensin-converting enzyme 2 CDC Centers for disease control and prevention CHB Complete heart block Declarations Ethics approval and consent to participate As this study utilized publicly available de-identified data, it received expedited review approval from the UCSF Fresno Community Medical Regional Center under 45 CFR 46.116(f). IRB No: 2023024 Consent for publication Not applicable Availability of data and materials The dataset supporting the conclusions of this study can be accessed on the HCUP website. https://hcup-us.ahrq.gov/ 20 Competing interests The authors declare that they have no competing interests. Funding None. Author’s contribution SK was responsible for conceptualization, methodology, writing the original draft, and revisions. BK contributed to the methodology, data analysis, visualization, drafting of the original manuscript, and revisions. FSC was involved in writing, reviewing, editing, and supervision. AJMG also contributed to writing, review, editing, and supervision. LVG played a role in conceptualization, methodology, data collection and analysis, visualization, writing, review, editing, and supervision. SK and BK contributed equally to the work. All authors read and approved the final manuscript. Author’s information Nepal Medical College and Teaching Hospital, Kathmandu, Nepal. Sagya Khanal Kathmandu Medical College and Teaching Hospital, Sinamangal, Kathmandu, Nepal. Bishes Khanal Department of Neonatal-Perinatal Medicine, Kaiser Permanente Riverside Medical Center, CA, USA Fu-Sheng Chou Division of Pediatric Cardiology, UCSF Benioff Children’s Hospital, Department of Pediatrics, University of California, San Francisco, San Francisco, CA, USA Anita J Moon-Grady Division of Pediatric Cardiology, University of California, San Francisco, Fresno Regional campus, United States of America. Laxmi V Ghimire References Kesson AM. Respiratory virus infections. Paediatr Respir Rev. 2007;8:240–8. Troy NM, Bosco A. Respiratory viral infections and host responses; insights from genomics. Respir Res. 2016;17:156. Suh M, Movva N, Jiang X, Bylsma LC, Reichert H, Fryzek JP, et al. Respiratory Syncytial Virus Is the Leading Cause of United States Infant Hospitalizations, 2009–2019: A Study of the National (Nationwide) Inpatient Sample. J Infect Dis. 2022;226(Suppl 2):S154–63. Fernandes DM, Oliveira CR, Guerguis S, Eisenberg R, Choi J, Kim M, et al. Severe acute respiratory syndrome Coronavirus 2 clinical syndromes and predictors of disease severity in hospitalized children and youth. J Pediatr. 2021;230:23–e3110. Menchise A. Myocarditis in the setting of RSV bronchiolitis. Fetal Pediatr Pathol. 2011;30:64–8. Huang M, Bigos D, Levine M. Ventricular arrhythmia associated with respiratory syncytial viral infection. Pediatr Cardiol. 1998;19:498–500. Olesch CA, Bullock AM. Bradyarrhythmia and supraventricular tachycardia in a neonate with RSV. J Paediatr Child Health. 1998;34:199–201. Haddad W, Agoudemos M, Basnet S. Prolonged sinoatrial block in an infant with respiratory syncytial viral bronchiolitis. Pediatr Cardiol. 2012;33:1203–5. Bairan AC. Complete heart block and respiratory syncytial virus: Infection. Am J Dis Child. 1974;127:264. Mamas MA, Fraser D, Neyses L. Cardiovascular manifestations associated with influenza virus infection. Int J Cardiol. 2008;130:304–9. Onitsuka H, Imamura T, Miyamoto N, Shibata Y, Kashiwagi T, Ayabe T, et al. Clinical manifestations of influenza a myocarditis during the influenza epidemic of winter 1998–1999. J Cardiol. 2001;37:315–23. Greaves K, Oxford JS, Price CP, Clarke GH, Crake T. The prevalence of myocarditis and skeletal muscle injury during acute viral infection in adults: measurement of cardiac troponins I and T in 152 patients with acute influenza infection. Arch Intern Med. 2003;163:165–8. Chow EJ, Rolfes MA, O’Halloran A, Anderson EJ, Bennett NM, Billing L, et al. Acute Cardiovascular Events Associated With Influenza in Hospitalized Adults: A Cross-sectional Study. Ann Intern Med. 2020;173:605–13. Long B, Brady WJ, Koyfman A, Gottlieb M. Cardiovascular complications in COVID-19. Am J Emerg Med. 2020;38:1504–7. Danzi GB, Loffi M, Galeazzi G, Gherbesi E. Acute pulmonary embolism and COVID-19 pneumonia: a random association? Eur Heart J. 2020;41:1858–1858. Wang D, Hu B, Hu C, Zhu F, Liu X, Zhang J, et al. Clinical characteristics of 138 hospitalized patients with 2019 novel Coronavirus-infected pneumonia in Wuhan, China. JAMA. 2020;323:1061–9. Xie Y, Wang X, Yang P, Zhang S. COVID-19 complicated by acute pulmonary embolism. Radiol Cardiothorac Imaging. 2020;2:e200067. Rathore SS, Rojas GA, Sondhi M, Pothuru S, Pydi R, Kancherla N, et al. Myocarditis associated with Covid-19 disease: A systematic review of published case reports and case series. Int J Clin Pract. 2021;75:e14470. Shi S, Qin M, Shen B, Cai Y, Liu T, Yang F, et al. Association of Cardiac Injury With Mortality in Hospitalized Patients With COVID-19 in Wuhan, China. JAMA Cardiol. 2020;5:802–10. HCUP-US NIS overview. http://www.hcup-us.ahrq.gov/nisoverview.jsp . Accessed 4 Sep 2024. COVID-19 Hospital Data - COVID-19 hospital encounters by week. 2024. https://www.cdc.gov/nchs/covid19/nhcs/hospital-encounters-by-week.htm . Accessed 4 Sep 2024. Healthcare cost and utilization project (HCUP.) NIS notes. http://www.hcup-us.ahrq.gov/db/vars/aprdrg_severity/nisnote.jsp . Accessed 4 Sep 2024. RStudio Team. RStudio: integrated development for R, Boston. MA: RStudio, Inc.; 2016. http://www.rstudio.com/ . Accessed 4 Sep 2024. Laris-González A, Avilés-Robles M, Domínguez-Barrera C, Parra-Ortega I, Sánchez-Huerta JL, Ojeda-Diezbarroso K, et al. Influenza vs. COVID-19: Comparison of clinical characteristics and outcomes in pediatric patients in Mexico city. Front Pediatr. 2021;9:676611. Hedberg P, Karlsson Valik J, van der Werff S, Tanushi H, Requena Mendez A, Granath F, et al. Clinical phenotypes and outcomes of SARS-CoV-2, influenza, RSV and seven other respiratory viruses: a retrospective study using complete hospital data. Thorax. 2022;77:154–63. Götzinger F, Santiago-García B, Noguera-Julián A, Lanaspa M, Lancella L, Calò Carducci FI, et al. COVID-19 in children and adolescents in Europe: a multinational, multicentre cohort study. Lancet Child Adolesc Health. 2020;4:653–61. Shu H, Zhao C, Wang DW. Understanding COVID-19-related myocarditis: pathophysiology, diagnosis, and treatment strategies. Cardiol Plus. 2023;8:72–81. Boehmer TK, Kompaniyets L, Lavery AM, Hsu J, Ko JY, Yusuf H, et al. MMWR Morb Mortal Wkly Rep. 2021;70:1228–32. Association Between COVID-19 and Myocarditis Using Hospital-Based Administrative Data - United States, March 2020-January 2021. Ghimire LV, Chou F-S, Aljohani OA, Moon-Grady AJ. Comparison of adverse clinical outcomes in children hospitalized for myocarditis with and without COVID-19. J Pediatr. 2023;261:113561. Bassi R, Ismail Z, Salabei JK, Charles K, Haider AA, Hussein A, et al. COVID-19-Induced Complete Heart Block: Case Series and Literature Review. Cureus. 2023;15:e37517. Ukimura A, Izumi T, Matsumori A, Clinical Research Committee on Myocarditis Associated. with 2009 Influenza A (H1N1) Pandemic in Japan organized by Japanese Circulation Society. A national survey on myocarditis associated with the 2009 influenza A (H1N1) pandemic in Japan. Circ J. 2010;74:2193–9. Additional Declarations No competing interests reported. Supplementary Files SupplementaryTable1.docx Cite Share Download PDF Status: Published Journal Publication published 28 Nov, 2024 Read the published version in BMC Cardiovascular Disorders → Version 1 posted Editorial decision: Revision requested 24 Sep, 2024 Editor assigned by journal 23 Sep, 2024 Submission checks completed at journal 23 Sep, 2024 First submitted to journal 13 Sep, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-5081257","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":358418226,"identity":"c7ba7c25-865b-4100-aad7-a2c365d03f17","order_by":0,"name":"Sagya Khanal","email":"","orcid":"","institution":"Nepal Medical College and Teaching Hospital","correspondingAuthor":false,"prefix":"","firstName":"Sagya","middleName":"","lastName":"Khanal","suffix":""},{"id":358418227,"identity":"d39894e6-7a88-48bb-bee0-dc722c876dfa","order_by":1,"name":"Bishes Khanal","email":"","orcid":"","institution":"Kathmandu Medical College and Teaching Hospital","correspondingAuthor":false,"prefix":"","firstName":"Bishes","middleName":"","lastName":"Khanal","suffix":""},{"id":358418228,"identity":"b03add8e-cc4b-4ce0-8f0c-567a69f1ae55","order_by":2,"name":"Fu-Sheng Chou","email":"","orcid":"","institution":"Kaiser Permanente Riverside Medical Center","correspondingAuthor":false,"prefix":"","firstName":"Fu-Sheng","middleName":"","lastName":"Chou","suffix":""},{"id":358418229,"identity":"44142a67-eae8-4e0d-9ff6-252fe9e0b38f","order_by":3,"name":"Anita J Moon-Grady","email":"","orcid":"","institution":"UCSF Benioff Children’s Hospital, University of California, San Francisco","correspondingAuthor":false,"prefix":"","firstName":"Anita","middleName":"J","lastName":"Moon-Grady","suffix":""},{"id":358418230,"identity":"b705fd79-b4e0-4ec9-a4ba-e8bb82068581","order_by":4,"name":"Laxmi V Ghimire","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA7UlEQVRIiWNgGAWjYBACAxCRwGCXwMbA2MDAUAHkMR9gYOAhrCUZquUMkMeWQIQWBoYDCWCKsY0YLexnTDc8YDiQxyd2uO3Dx3mH5eXbGBgfvG3Do4UnLe1GAsOBYjbpxOaZM7cdNtxwjIHZcC4+LQzJx4Bajie2AbUw8247nGAg38AmzYtPC//DNqCWwxAtf+ccTgA6jP03Xi0SYFugWhgbDicwHGNgY8av5RnQLwbJYC2MPcfSgX5hbJaccw63Fvv+HLObPyrsEufPTn/M8KPGGhhizAc/vCnDrQUWCMgAFKejYBSMglEwCigCAHkQUYSvI43/AAAAAElFTkSuQmCC","orcid":"","institution":"University of California, San Francisco","correspondingAuthor":true,"prefix":"","firstName":"Laxmi","middleName":"V","lastName":"Ghimire","suffix":""}],"badges":[],"createdAt":"2024-09-13 05:48:36","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5081257/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5081257/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12872-024-04366-0","type":"published","date":"2024-11-28T15:58:28+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":68653834,"identity":"edc778a4-4bbf-4beb-a77b-59d10c62d657","added_by":"auto","created_at":"2024-11-10 13:49:07","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":80962,"visible":true,"origin":"","legend":"\u003cp\u003eFlow diagram for in-hospital admission for COVID-19, influenza and RSV infection.\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-5081257/v1/a1bd36221250e0bbd166c3e8.png"},{"id":68653831,"identity":"027ea278-774b-41c6-b417-d03ed7ade7b1","added_by":"auto","created_at":"2024-11-10 13:49:06","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":65832,"visible":true,"origin":"","legend":"\u003cp\u003eRisk of myocarditis in COVID-19, influenza and RSV infection.\u003c/p\u003e","description":"","filename":"Figure2covidflursv.png","url":"https://assets-eu.researchsquare.com/files/rs-5081257/v1/b5f98e8f6972e8b62e8cf696.png"},{"id":70389517,"identity":"94febb61-9d9c-4cb0-9920-f0dd79f4e515","added_by":"auto","created_at":"2024-12-02 17:28:51","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":912047,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5081257/v1/7086dd70-b187-4e6e-99ed-532549b1f647.pdf"},{"id":68653832,"identity":"c4ae4c14-b24b-4fc8-8e20-ebfc001cefa7","added_by":"auto","created_at":"2024-11-10 13:49:06","extension":"docx","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":7790,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTable1.docx","url":"https://assets-eu.researchsquare.com/files/rs-5081257/v1/a3816f26a286c6b995b41c94.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Comparison of mortality and cardiovascular complications due to COVID-19, RSV, and influenza in hospitalized children and young adults","fulltext":[{"header":"Background","content":"\u003cp\u003eRespiratory viral infections represent a significant public health challenge, contributing substantially to both morbidity and mortality [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Common respiratory viral pathogens include adenovirus, enterovirus, human coronavirus, human metapneumovirus, rhinovirus (RV), influenza, parainfluenza, and respiratory syncytial virus (RSV) [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Notably, COVID-19, influenza, and RSV exhibit similar clinical presentations and share common transmission routes through droplets and aerosols, which complicates their clinical differentiation [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eRespiratory syncytial virus (RSV) is the leading cause of hospital admissions in infants and young children, [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e] while influenza and SARS-CoV-2 are more prevalent in older children [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Previous studies have established a connection between respiratory viral infections and major cardiovascular complications [\u003cspan additionalcitationids=\"CR6 CR7 CR8 CR9 CR10 CR11 CR12 CR13 CR14 CR15 CR16 CR17\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. RSV infection has been associated with myocarditis, [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e] ventricular tachycardia, [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e] and heart block [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e] Influenza infection is a recognized cause of myopericarditis [\u003cspan additionalcitationids=\"CR11\" citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e] and is associated with an elevated risk of acute heart failure and acute ischemic heart disease [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. SARS-CoV-2 infection manifests a wide range of clinical presentations, including myocardial involvement such as myocarditis, dysrhythmias, heart failure, myocardial infarction, and thromboembolic events [\u003cspan additionalcitationids=\"CR15 CR16 CR17\" citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe emergence of SARS-CoV-2 in 2019 led to a significant increase in hospitalizations across all age groups and was associated with a high risk of in-hospital mortality [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Although cardiovascular manifestations of respiratory viral infections have been documented, [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e] they have largely been reported separately. No study has systematically compared the clinical complications and outcomes associated with COVID-19, influenza, and RSV infections in the pediatric population. This study aims to compare in-hospital mortality and major cardiovascular complications among hospitalized children and young adults with COVID-19, influenza, and RSV infections.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy population and variables\u003c/h2\u003e \u003cp\u003eThis retrospective study utilized hospital discharge records from the National Inpatient Sample (NIS) for the years 2020 and 2021. The NIS is a component of the Healthcare Cost and Utilization Project (HCUP), funded by the Agency for Healthcare Research and Quality (AHRQ) [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. The NIS sampling frame encompasses data from 48 statewide data organizations, including 47 states plus the District of Columbia, representing approximately 98% of the U.S. population. It includes a stratified 20% sample of discharges from U.S. community hospitals, excluding long-term acute care hospitals and rehabilitation facilities. The NIS ensures patient confidentiality because of the de-identified nature of data. A detailed description of the database is available on the HCUP website [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eOur study focused on individuals aged 20 years or younger who were hospitalized with a diagnosis of COVID-19, influenza, or respiratory syncytial virus (RSV). The International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM), was utilized to identify hospitalized children diagnosed with COVID-19, influenza, RSV, and other variables studied. To minimize confounding effects, we excluded individuals with co-respiratory infections (i.e., those diagnosed with more than one of the studied viral infections: COVID-19, influenza, or RSV) and those who were transferred between hospitals to prevent double counting. (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eTo identify COVID-19 cases within the database, we utilized the ICD-10-CM code B97.29 for records from January 1 to March 31, 2020, and U07.1 for records from April 1, 2020, onward [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. For RSV infection, the following ICD-10-CM codes were employed: B97.4, J12.1, J20.5, and J21.0. We excluded cases of bronchiolitis that did not have a corresponding RSV diagnosis. We excluded admission that did not have complete data for analysis.\u003c/p\u003e \u003cp\u003eSeverity, used as a variable in the analysis, denotes the severity of illness has four categories: 1) minor loss of function, which includes cases with no comorbidity or complications; 2) moderate loss of function; 3) major loss of function; and 4) extreme loss of function [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eOutcome variables\u003c/h2\u003e \u003cp\u003eThe primary outcomes were in-hospital mortality and major cardiovascular complications associated with COVID-19, influenza, or RSV infection. For the purposes of analysis, major cardiovascular complications were myocarditis, tachyarrhythmia, heart block, sudden cardiac arrest, and the need for extracorporeal membrane oxygenation (ECMO). Additionally, we compared disease severity and length of hospital stay across the study groups. The ICD-10 codes corresponding to the diagnoses and procedures analyzed in this study are presented in supplementary table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003e We conducted both descriptive and inferential analyses, followed by logistic regression modeling, to evaluate the data. Given that the NIS is a complex survey dataset, we incorporated clusters, strata, and weighting as recommended by the Healthcare Cost and Utilization Project (HCUP) to generate national estimates and ensure the accuracy of the statistical analyses. Continuous variables, such as age, length of stay, and disease severity, were reported as medians with interquartile ranges. Categorical variables were analyzed using weight-adjusted chi-square tests.\u003c/p\u003e \u003cp\u003eFor multivariable analysis, we selected variables with reliable and consistent ICD-10 codes. Initially, univariable regression analysis was performed for variables of interest, followed by multivariable regression analysis that accounted for additional covariates, including age group, sex, asthma/reactive airway disease, prematurity, obesity, diabetes, congenital heart disease, chromosomal anomalies, ZIP code of household neighborhood, and disease severity. These covariates were identified through a comprehensive literature review and clinical expertise and were finalized prior to conducting the analyses.\u003c/p\u003e \u003cp\u003eThe patient\u0026rsquo;s ZIP code was categorized into quartiles based on the estimated median household income of residents within that ZIP code, with quartiles representing the range from the lowest to highest income, indicating the poorest to wealthiest populations. All statistical analyses were conducted using Stata statistical software (version 15.1) and R (version 4.3) with RStudio (version 1.2). Figures were generated using the ggplot2 package in R [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eOf 212,655 respiratory virus admissions, 85,055 were from COVID-19, 24,415 were from influenza, and 103,185 were from RSV. Among these, 46,845 (55.1%) of the COVID-19 cases, 11,290 (46.3%) of the influenza cases, and 46,445 (45.0%) of the RSV cases were female patients. The median age of children hospitalized with COVID-19 was 15 years (IQR: 3\u0026ndash;19), with influenza it was 4 years (IQR: 1\u0026ndash;9), and with RSV it was under 1 year (IQR: 0\u0026ndash;1). COVID-19 admissions were more prevalent among young adults (11\u0026ndash;20 years), whereas influenza and RSV admissions were more common among younger children (0\u0026ndash;2 years).\u003c/p\u003e \u003cp\u003eAmong children with underlying medical conditions, hospitalized children and young adults with a history of asthma/reactive airway disease were more common in those with influenza (21.6%, n\u0026thinsp;=\u0026thinsp;5,265), followed by COVID-19 (14.4%, n\u0026thinsp;=\u0026thinsp;12,260) and RSV (13.6%, n\u0026thinsp;=\u0026thinsp;14,040). Children with obesity were more likely to have COVID-19 (14.2%, n\u0026thinsp;=\u0026thinsp;12,095) compared to influenza (2.1%, n\u0026thinsp;=\u0026thinsp;510) and RSV (0.5%, n\u0026thinsp;=\u0026thinsp;485). Additionally, prematurely born children were more likely to have RSV (4.5%, n\u0026thinsp;=\u0026thinsp;4,660) compared to COVID-19 (1.5%, n\u0026thinsp;=\u0026thinsp;1,280) and influenza (2.1%, n\u0026thinsp;=\u0026thinsp;505) (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\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\u003eCharacteristics of patients, comorbid conditions, and complications due to COVID-19, influenza and RSV. Total Respi virus cases: 212,655\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=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e \u003cp\u003eRespiratory virus with total number(percentages)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCOVID-19\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eInfluenza\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRSV\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eP Value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal number (n)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e85,055\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24,415\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e103,185\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e46845 (55.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11290 (46.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e46445 (45.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" 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\u003eAge, years (median [IQR])\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15 [3\u0026ndash;19]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4 [1\u0026ndash;9]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 [0\u0026ndash;1]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" 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\u003eAge group (year)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"4\" rowspan=\"5\"\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\u003e0\u0026ndash;2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20405 (24.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10015 (41.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e91700 (88.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u0026ndash;5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4455 (5.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4265 (17.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7820 (7.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u0026ndash;10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7235 (8.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4805 (19.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2150 (2.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e11\u0026ndash;20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e52960 (62.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5330 (21.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1515 (1.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eZip Code*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"4\" rowspan=\"5\"\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\u003e1st quartile\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30980 (36.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8365 (34.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e32290 (31.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2nd quartile\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21540 (25.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6095 (25.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e26500 (25.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3rd quartile\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18870 (22.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5695 (23.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e24180 (23.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4th quartile\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12655 (15.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4045 (16.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19340 (18.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003eComorbid conditions\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCHD\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2530 (3.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e970 (4.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4985 (4.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" 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\u003eObesity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12095 (14.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e510 (2.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e485 (0.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" 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\u003eDiabetes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5085 (6.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e710.0 (2.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e270 (0.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" 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\u003eChromosomal Anomalies\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2180 (2.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e730 (3.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2250 (2.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAsthma/reactive airway\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12260 (14.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5265 (21.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14040 (13.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" 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\u003ePrematurity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1280 (1.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e505 (2.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4660 (4.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003eCardiovascular Complications\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMyocarditis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e740 (0.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e55 (0.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e65 (0.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" 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\u003eTachyarrhythmia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1290 (1.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e235 (1.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e635 (0.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" 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\u003eHeart Block\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e690 (0.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e115 (0.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e205 (0.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" 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\u003eSudden Cardiac Arrest\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e310 (0.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e50 (0.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e135 (0.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" 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\u003eECMO\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e170 (0.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e55 (0.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e45 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" 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\u003eLength of stay (LOS) (Median[IQR]) in days\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3 [2\u0026ndash;5]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 [2\u0026ndash;4]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3 [2\u0026ndash;4]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" 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\u003eDisease Severity (Median[IQR])\u003csup\u003eC\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3 [2\u0026ndash;3]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 [1\u0026ndash;3]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2 [1\u0026ndash;3]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" 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\u003eIn-hospital mortality\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e580 (0.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e65 (0.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e130 (0.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" 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\u003csup\u003ea\u003c/sup\u003eCongenital Heart Disease\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003csup\u003eb\u003c/sup\u003eExtracorporeal membrane oxygenation\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003csup\u003ec\u003c/sup\u003eSeverity illness subclass according to loss of function\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e*Zip Code: Neighborhood ZIP Codes classify the estimated median household income of residents in a patient's ZIP Code into four quartiles. The quartiles are identified from lowest to highest, indicating the lowest-income neighborhoods to highest-income neighborhoods.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eWe performed univariable and multivariable logistic regression analyses to compare in-hospital mortality and major cardiovascular complications across COVID-19, influenza, and RSV cases. Multivariable logistic regression was performed after adjusting for confounding factors including age group, gender, prematurity, obesity, diabetes, asthma, congenital heart disease, chromosomal anomalies, and disease severity. Using COVID-19 as the reference group, we assessed the risk of complications associated with influenza and RSV.\u003c/p\u003e \u003cp\u003eThe in-hospital mortality rate was 0.7% (n\u0026thinsp;=\u0026thinsp;580) for COVID-19, 0.3% (n\u0026thinsp;=\u0026thinsp;65) for influenza, and 0.1% (n\u0026thinsp;=\u0026thinsp;130) for RSV. Descriptive analysis indicated higher in-hospital mortality for COVID-19 compared to influenza and RSV. However, when adjusted for covariates, the differences in in-hospital mortality were not statistically significant, with an adjusted odds ratio (aOR) of 0.92 (95% CI: 0.49\u0026ndash;1.71, P\u0026thinsp;=\u0026thinsp;0.799) for influenza and 0.67 (95% CI: 0.39\u0026ndash;1.14, P\u0026thinsp;=\u0026thinsp;0.142) for RSV, relative to COVID-19 (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). In this model, those with diabetes and higher disease severity were associated with increased risk of in-hospital mortality. The descriptive statistics table with individuals who died vs those who survived are presented in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\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\u003eLogistic Regression of in-hospital mortality, cardiovascular and non-cardiovascular complications. (Taking COVID-19 as reference)\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=\"left\" 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 \u003cp\u003eComplications\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRespiratory viruses\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eUnadjusted Odds Ratio (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAdjusted Odds Ratio (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eIn- hospital Mortality\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReference \u003c/p\u003e \u003cp\u003e(COVID-19)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c6\" namest=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eInfluenza\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.38 (0.21\u0026ndash;0.69)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.92 (0.49\u0026ndash;1.71)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.799\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRSV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.18 (1.11\u0026ndash;0.28)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.67 (0.39\u0026ndash;1.14)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.142\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003eCardiovascular Complications\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eMyocarditis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReference (COVID-19)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c6\" namest=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eInfluenza\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.25 (0.14\u0026ndash;0.47)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.39 (0.20\u0026ndash;0.76)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.006\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRSV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.049(0.02\u0026ndash;0.09)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.15 (0.07\u0026ndash;0.34)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eHeart Block\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReference (COVID-19)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c6\" namest=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eInfluenza\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.57 (0.37\u0026ndash;0.90)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.015\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.79 (0.48\u0026ndash;1.31)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.374\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRSV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.24 (0.17\u0026ndash;0.34)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.51 (0.33\u0026ndash;0.80)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eTachyarrhythmia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReference (COVID-19)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c6\" namest=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eInfluenza\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.63 (0.46\u0026ndash;0.86)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.21 (0.85\u0026ndash;1.74)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.277\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRSV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.40 (0.32\u0026ndash;0.49)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.15 (0.84\u0026ndash;1.59)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.366\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eSudden Cardiac arrest\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReference (COVID-19)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c6\" namest=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eInfluenza\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.56 (0.28\u0026ndash;1.09)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.14 (0.55\u0026ndash;2.35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.722\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRSV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.35 (0.22\u0026ndash;0.56)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.85 (0.49\u0026ndash;1.47)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.569\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \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\u003eStratification of respiratory virus cases and complications by those who died vs those who survived.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eDied (number and percentages)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal number\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e211829\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e775\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e104235 (49.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e315 (40.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.039\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (median[IQR])\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 [0\u0026ndash;12]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15 [2\u0026ndash;19]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\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\u003eAge group (in years)\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\" morerows=\"4\" rowspan=\"5\"\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\u003e0\u0026ndash;2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e121889 (57.54)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e215 (27.74)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u0026ndash;5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16504 (7.79)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30 (3.87)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u0026ndash;10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14105 (6.66)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e80 (10.32)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e11\u0026ndash;20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e59329 (28.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e450 (58.06)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eZip Code*\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\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e0.073\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1st quartile\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e71320 (34)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e290 (38.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2nd quartile\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e53945 (25.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e185 (24.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3rd quartile\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e48525 (23.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e210 (27.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4th quartile\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e35960 (17.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e75 (9.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRespiratory viruses\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\" morerows=\"3\" rowspan=\"4\"\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\u003eCOVID-19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e84445 (39.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e580 (74.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInfluenza\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e24350 (11.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e65 (8.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRSV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e103035 (48.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e130 (16.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eComorbid conditions\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCHD\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8400 (4.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e85 (11.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\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\u003eObesity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12950 (6.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e140 (18.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\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\u003eDiabetes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5990 (2.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e70 (9.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\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\u003eChromosomal Anomalies\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5115 (2.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e45 (5.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.006\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAsthma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e31430 (14.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e130 (6.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.50\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrematurity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6425 (3.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20 (2.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.75\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eCardiovascular Complications\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMyocarditis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e825 (0.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15 (1.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTachyarrhythmia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2060 (1.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e95 (12.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\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\u003eHeart Block\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e995 (0.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15 (1.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\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\u003eSudden Cardiac Arrest\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e255 (0.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e235 (30.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\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\u003eECMO\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e165 (0.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e125 (16.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\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\u003eIn-hospital mortality\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e775 (100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\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=\"4\"\u003e\u003csup\u003ea\u003c/sup\u003eCongenital Heart Disease\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003e\u003csup\u003eb\u003c/sup\u003eExtracorporeal membrane oxygenation\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003e\u003csup\u003ec\u003c/sup\u003eSeverity illness subclass according to loss of function\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003e*Zip Code: Neighborhood ZIP Codes classify the estimated median household income of residents in a patient's ZIP Code into four quartiles. The quartiles are identified from lowest to highest, indicating the lowest-income neighborhoods to highest-income neighborhoods.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eRegarding cardiovascular complications, myocarditis was more frequent in COVID-19 cases (0.9%, n\u0026thinsp;=\u0026thinsp;740) compared to influenza (0.2%, n\u0026thinsp;=\u0026thinsp;55) and RSV (0.1%, n\u0026thinsp;=\u0026thinsp;65) cases in descriptive analyses. The risk of myocarditis was 61% lower in influenza with an adjusted odds ratio (aOR) of 0.39 (95% CI: 0.20\u0026ndash;0.76, P\u0026thinsp;=\u0026thinsp;0.006) and 85% lower in RSV with an adjusted odds ratio (aOR) of 0.15 (95% CI: 0.07\u0026ndash;0.34, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) compared to COVID-19 (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e and Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The descriptive statistics table with individuals with myocarditis vs those without myocarditis are presented in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. Similarly, the risk of heart block was 49% lower in RSV with an adjusted odds ratio (aOR) of 0.51 (95% CI: 0.33\u0026ndash;0.80, P\u0026thinsp;=\u0026thinsp;0.004) compared to COVID-19, though it was not statistically significant for influenza (aOR 0.79, 95% CI: 0.48\u0026ndash;1.31, P\u0026thinsp;=\u0026thinsp;0.374). While descriptive analyses suggested that tachyarrhythmia and sudden cardiac arrest were more common in COVID-19, these findings were not statistically significant in the multivariable logistic regression models (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe median length of hospital stay was 3 days (IQR: 2\u0026ndash;5) for COVID-19, 2 days (IQR: 2\u0026ndash;4) for influenza, and 3 days (IQR: 2\u0026ndash;4) for RSV (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eUsing the NIS 2020\u0026ndash;2021 database, we report the following major findings. First, the in-hospital mortality rates were similar for COVID-19, influenza, and RSV infections requiring hospitalization. Second, the risk of cardiovascular complications, particularly myocarditis and heart block, were more common in COVID-19.\u003c/p\u003e \u003cp\u003eThe similarity in in-hospital mortality rates among these respiratory viruses, after adjusting for confounders, aligns with findings from previous studies. For instance, a study conducted in Mexico by Laris-Gonz\u0026aacute;lez et al. reported comparable in-hospital mortality in multivariable analysis between COVID-19 and influenza [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Hedberg et al., in their study based in Sweden, compared clinical phenotypes and outcomes of different respiratory viral infections in both pediatric (\u0026le;\u0026thinsp;15 years) and adult cohorts. Their results indicated that in the adult cohort, in-hospital mortality was significantly higher for COVID-19 compared to influenza (aHR 4.43, 95% CI: 3.51 to 5.59) and RSV (aHR 3.81, 95% CI: 2.72 to 5.34). However, in the pediatric cohort, the comparison of in-hospital mortality (30 days and 90 days) was similar [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. The milder course of COVID-19 in young children and infants, compared to adults, may partially explain the similar in-hospital mortality rates observed for COVID-19, influenza, and RSV [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe risk of myocarditis was notably higher in COVID-19 compared to influenza and RSV. This was particularly evident in young adults aged 11\u0026ndash;20 years, with obesity identified as a common comorbid condition (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). The higher prevalence of myocarditis in COVID-19 may be attributed to the distinct pathophysiological mechanisms and immune responses triggered by SARS-CoV-2. As a cardiotropic virus, SARS-CoV-2 significantly impacts myocardial tissue and the cardiac conduction system, causing myocarditis by binding to ACE2 (Angiotensin-Converting Enzyme 2) receptors expressed in myocardial cells, pericytes, and pneumocytes, leading to direct cellular damage and uncontrolled inflammatory responses [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Consistent with our findings, data from the Centers for Disease Control and Prevention (CDC) indicated that myocarditis was 16 times more prevalent in COVID-19 patients than in those without the infection, particularly among older children, younger adolescents (\u0026lt;\u0026thinsp;16 years), and older adults (\u0026gt;\u0026thinsp;75 years) [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. In a subset analysis using NIS 2020 data, we previously compared clinical outcomes in myocarditis cases associated with COVID-19 versus non-COVID-19 cases and found that while the risk of mortality was similar between the two groups, acute kidney injury was more common in COVID-19-associated myocarditis (aOR\u0026thinsp;=\u0026thinsp;1.9, 95% CI: 1.1\u0026ndash;3.3, P\u0026thinsp;=\u0026thinsp;0.02). In that study, rates of tachyarrhythmias, heart blocks, sudden cardiac arrest, and ECMO use were similar between the two groups [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\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\u003eStratification of respiratory virus cases and complications by those with and without myocarditis.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eMyocarditis (number and percentages)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal number\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e211815\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e840\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e104300 (49.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e280 (33.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\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\u003eAge (median[IQR])\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 [0\u0026ndash;12]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11 [6\u0026ndash;17]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003eAge group (in years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"4\" rowspan=\"5\"\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\u003e0\u0026ndash;2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12010 (57.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e110 (13.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u0026ndash;5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16470 (7.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e70 (8.338)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u0026ndash;10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13970 (6.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e220 (26.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e11\u0026ndash;20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e59365 (28.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e440 (52.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003eZip Code*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e0.92\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1st quartile\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e71355 (34.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e280 (33.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2nd quartile\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e53925 (25.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e210 (25.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3rd quartile\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e48560 (23.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e185 (22.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4th quartile\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e35880 (17.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e160 (19.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eRespiratory viruses\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCOVID-19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e84315 (39.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e740 (88.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\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\u003eInfluenza\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e24360 (11.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e55 (6.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.046\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRSV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e103140(48.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e45 (5.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eComorbid conditions\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCHD\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8455 (4.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30 (3.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\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\u003eObesity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12990 (6.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e100 (11.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiabetes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6050 (2.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15 (1.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.40\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChromosomal Anomalies\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5150 (2.439)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10 (1.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.29\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAsthma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e31430 (14.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e135 (16.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.67\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrematurity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6440 (3.04)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5 (0.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.75\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eCardiovascular complications\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTachyarrhythmia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2055 (1.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e105 (12.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\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\u003eHeart Block\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e965 (0.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e45 (5.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\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\u003eSudden Cardiac Arrest\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e480 (0.23)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15 (1.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\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\u003eECMO\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e265 (0.13)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25 (3.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\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\u003eIn-hospital mortality\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e760 (0.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15 (1.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003e\u003csup\u003ea\u003c/sup\u003eCongenital Heart Disease\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003e\u003csup\u003eb\u003c/sup\u003eExtracorporeal membrane oxygenation\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003e\u003csup\u003ec\u003c/sup\u003eSeverity illness subclass according to loss of function\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003e*Zip Code: Neighborhood ZIP Codes classify the estimated median household income of residents in a patient's ZIP Code into four quartiles. The quartiles are identified from lowest to highest, indicating the lowest-income neighborhoods to highest-income neighborhoods.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eStudies on the risk of heart block associated with various respiratory viral infections have been conducted separately. In this study, we compared the risk of heart block across COVID-19, influenza, and RSV. We found that heart block was more common in COVID-19 compared to RSV, although the difference was not statistically significant when compared to influenza. The exact mechanism by which COVID-19 leads to heart block remains unclear. Some studies suggest that heart block may result from direct disruption of the heart's electrical conduction system by the SARS-CoV-2 virus. Additionally, it has been proposed that direct viral infiltration of cardiomyocytes via angiotensin converting enzyme 2 (ACE2) receptors, followed by systemic inflammation, may contribute to cardiac injury [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. During the 2009 influenza pandemic, Ukimura et al. reported four cases of influenza-related complete heart block (CHB) requiring temporary pacing, highlighting the potential for severe cardiac complications like heart block during respiratory viral infections [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. Few studies seem to investigate and compare heart block due to these respiratory viruses. This gap in the literature highlights the necessity of further exploration and understanding of this specific complication of viral infection in children.\u003c/p\u003e \u003cp\u003eOur study's main strength lies in the use of NIS 2020\u0026ndash;2021 data, which provides a large sample size based on population sampling of hospitalized pediatric populations with respiratory viral infections. However, there are limitations to this approach. The NIS database utilizes hospital discharge records from all HCUP-participating hospitals, excluding rehabilitation and long-term acute care hospitals. It includes only inpatient records, so the findings may not be generalizable to outpatient settings or patients who were transferred between hospitals. The database relies on ICD-10 codes for diagnosing respiratory infections, which may lack detailed information on the procedures and tests used for diagnoses. Additionally, as with any medical and billing database, the NIS may contain incorrect or missing information, leading to potential inaccuracies. This study did not include cases with co-respiratory viral infections (e.g., COVID-19\u0026thinsp;+\u0026thinsp;influenza, Influenza\u0026thinsp;+\u0026thinsp;RSV, etc.). Furthermore, we were unable to assess the influence of vaccination (RSV, COVID-19, Influenza) on clinical outcomes, as vaccination status is not captured in the database.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eIn conclusion, our findings indicate that children with COVID-19 infections are at increased risk of cardiovascular complications, including myocarditis and heart block. We recommend measures to prevent COVID-19 infection and to anticipate and promptly manage these cardiovascular complications in risk-prone children especially those with underlying comorbid conditions to prevent mortality.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eCOVID-19\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eCorona virus disease of 2019\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eRSV\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eRespiratory syncytial virus\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eRV\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eRhino virus\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eSARS-CoV-2\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eSevere acute respiratory syndrome coronavirus 2\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eNIS\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eNational inpatient sample\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eHCUP\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eHealthcare cost and utilization project\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eAHRQ\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAgency for healthcare research and quality\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eICD-10-CM\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eInternational classification of diseases, tenth revision, clinical modification\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eECMO\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eExtracorporeal membrane oxygenation\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eIQR\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eInterquartile range\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eCI\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eConfidence interval\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eaOR\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eadjusted Odds ratio\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eaHR\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eadjusted Hazard\u0026rsquo;s ratio\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eACE2\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAngiotensin-converting enzyme 2\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eCDC\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eCenters for disease control and prevention\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eCHB\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eComplete heart block\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAs this study utilized publicly available de-identified data, it received expedited review approval from the UCSF Fresno Community Medical Regional Center under 45 CFR 46.116(f). IRB No: 2023024\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe dataset supporting the conclusions of this study can be accessed on the HCUP website. https://hcup-us.ahrq.gov/ \u003csup\u003e20\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNone.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor\u0026rsquo;s contribution\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSK was responsible for conceptualization, methodology, writing the original draft, and revisions. BK contributed to the methodology, data analysis, visualization, drafting of the original manuscript, and revisions. FSC was involved in writing, reviewing, editing, and supervision. AJMG also contributed to writing, review, editing, and supervision. LVG played a role in conceptualization, methodology, data collection and analysis, visualization, writing, review, editing, and supervision. SK and BK contributed equally to the work. All authors read and approved the final manuscript.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor\u0026rsquo;s information\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNepal Medical College and Teaching Hospital, Kathmandu, Nepal.\u003c/p\u003e\n\u003cp\u003eSagya Khanal\u003c/p\u003e\n\u003cp\u003eKathmandu Medical College and Teaching Hospital, Sinamangal, Kathmandu, Nepal.\u003c/p\u003e\n\u003cp\u003eBishes Khanal\u003c/p\u003e\n\u003cp\u003eDepartment of Neonatal-Perinatal Medicine, Kaiser Permanente Riverside Medical Center, CA, USA\u003c/p\u003e\n\u003cp\u003eFu-Sheng Chou\u003c/p\u003e\n\u003cp\u003eDivision of Pediatric Cardiology, UCSF Benioff Children\u0026rsquo;s Hospital, Department of Pediatrics, University of California, San Francisco, San Francisco, CA, USA\u003c/p\u003e\n\u003cp\u003eAnita J Moon-Grady\u003c/p\u003e\n\u003cp\u003eDivision of Pediatric Cardiology, University of California, San Francisco, Fresno Regional campus, United States of America.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eLaxmi V Ghimire\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eKesson AM. Respiratory virus infections. Paediatr Respir Rev. 2007;8:240\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTroy NM, Bosco A. Respiratory viral infections and host responses; insights from genomics. Respir Res. 2016;17:156.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSuh M, Movva N, Jiang X, Bylsma LC, Reichert H, Fryzek JP, et al. Respiratory Syncytial Virus Is the Leading Cause of United States Infant Hospitalizations, 2009\u0026ndash;2019: A Study of the National (Nationwide) Inpatient Sample. J Infect Dis. 2022;226(Suppl 2):S154\u0026ndash;63.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFernandes DM, Oliveira CR, Guerguis S, Eisenberg R, Choi J, Kim M, et al. Severe acute respiratory syndrome Coronavirus 2 clinical syndromes and predictors of disease severity in hospitalized children and youth. J Pediatr. 2021;230:23\u0026ndash;e3110.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMenchise A. Myocarditis in the setting of RSV bronchiolitis. Fetal Pediatr Pathol. 2011;30:64\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHuang M, Bigos D, Levine M. Ventricular arrhythmia associated with respiratory syncytial viral infection. Pediatr Cardiol. 1998;19:498\u0026ndash;500.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOlesch CA, Bullock AM. Bradyarrhythmia and supraventricular tachycardia in a neonate with RSV. J Paediatr Child Health. 1998;34:199\u0026ndash;201.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHaddad W, Agoudemos M, Basnet S. Prolonged sinoatrial block in an infant with respiratory syncytial viral bronchiolitis. Pediatr Cardiol. 2012;33:1203\u0026ndash;5.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBairan AC. Complete heart block and respiratory syncytial virus: Infection. Am J Dis Child. 1974;127:264.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMamas MA, Fraser D, Neyses L. Cardiovascular manifestations associated with influenza virus infection. Int J Cardiol. 2008;130:304\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOnitsuka H, Imamura T, Miyamoto N, Shibata Y, Kashiwagi T, Ayabe T, et al. Clinical manifestations of influenza a myocarditis during the influenza epidemic of winter 1998\u0026ndash;1999. J Cardiol. 2001;37:315\u0026ndash;23.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGreaves K, Oxford JS, Price CP, Clarke GH, Crake T. The prevalence of myocarditis and skeletal muscle injury during acute viral infection in adults: measurement of cardiac troponins I and T in 152 patients with acute influenza infection. Arch Intern Med. 2003;163:165\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChow EJ, Rolfes MA, O\u0026rsquo;Halloran A, Anderson EJ, Bennett NM, Billing L, et al. Acute Cardiovascular Events Associated With Influenza in Hospitalized Adults: A Cross-sectional Study. Ann Intern Med. 2020;173:605\u0026ndash;13.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLong B, Brady WJ, Koyfman A, Gottlieb M. Cardiovascular complications in COVID-19. Am J Emerg Med. 2020;38:1504\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDanzi GB, Loffi M, Galeazzi G, Gherbesi E. Acute pulmonary embolism and COVID-19 pneumonia: a random association? Eur Heart J. 2020;41:1858\u0026ndash;1858.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWang D, Hu B, Hu C, Zhu F, Liu X, Zhang J, et al. Clinical characteristics of 138 hospitalized patients with 2019 novel Coronavirus-infected pneumonia in Wuhan, China. JAMA. 2020;323:1061\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eXie Y, Wang X, Yang P, Zhang S. COVID-19 complicated by acute pulmonary embolism. Radiol Cardiothorac Imaging. 2020;2:e200067.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRathore SS, Rojas GA, Sondhi M, Pothuru S, Pydi R, Kancherla N, et al. Myocarditis associated with Covid-19 disease: A systematic review of published case reports and case series. Int J Clin Pract. 2021;75:e14470.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShi S, Qin M, Shen B, Cai Y, Liu T, Yang F, et al. Association of Cardiac Injury With Mortality in Hospitalized Patients With COVID-19 in Wuhan, China. JAMA Cardiol. 2020;5:802\u0026ndash;10.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHCUP-US NIS overview. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.hcup-us.ahrq.gov/nisoverview.jsp\u003c/span\u003e\u003cspan address=\"http://www.hcup-us.ahrq.gov/nisoverview.jsp\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Accessed 4 Sep 2024.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCOVID-19 Hospital Data - COVID-19 hospital encounters by week. 2024. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.cdc.gov/nchs/covid19/nhcs/hospital-encounters-by-week.htm\u003c/span\u003e\u003cspan address=\"https://www.cdc.gov/nchs/covid19/nhcs/hospital-encounters-by-week.htm\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Accessed 4 Sep 2024.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHealthcare cost and utilization project (HCUP.) NIS notes. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.hcup-us.ahrq.gov/db/vars/aprdrg_severity/nisnote.jsp\u003c/span\u003e\u003cspan address=\"http://www.hcup-us.ahrq.gov/db/vars/aprdrg_severity/nisnote.jsp\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Accessed 4 Sep 2024.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRStudio Team. RStudio: integrated development for R, Boston. MA: RStudio, Inc.; 2016. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.rstudio.com/\u003c/span\u003e\u003cspan address=\"http://www.rstudio.com/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Accessed 4 Sep 2024.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLaris-Gonz\u0026aacute;lez A, Avil\u0026eacute;s-Robles M, Dom\u0026iacute;nguez-Barrera C, Parra-Ortega I, S\u0026aacute;nchez-Huerta JL, Ojeda-Diezbarroso K, et al. Influenza vs. COVID-19: Comparison of clinical characteristics and outcomes in pediatric patients in Mexico city. Front Pediatr. 2021;9:676611.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHedberg P, Karlsson Valik J, van der Werff S, Tanushi H, Requena Mendez A, Granath F, et al. Clinical phenotypes and outcomes of SARS-CoV-2, influenza, RSV and seven other respiratory viruses: a retrospective study using complete hospital data. Thorax. 2022;77:154\u0026ndash;63.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eG\u0026ouml;tzinger F, Santiago-Garc\u0026iacute;a B, Noguera-Juli\u0026aacute;n A, Lanaspa M, Lancella L, Cal\u0026ograve; Carducci FI, et al. COVID-19 in children and adolescents in Europe: a multinational, multicentre cohort study. Lancet Child Adolesc Health. 2020;4:653\u0026ndash;61.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShu H, Zhao C, Wang DW. Understanding COVID-19-related myocarditis: pathophysiology, diagnosis, and treatment strategies. Cardiol Plus. 2023;8:72\u0026ndash;81.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBoehmer TK, Kompaniyets L, Lavery AM, Hsu J, Ko JY, Yusuf H, et al. MMWR Morb Mortal Wkly Rep. 2021;70:1228\u0026ndash;32. Association Between COVID-19 and Myocarditis Using Hospital-Based Administrative Data - United States, March 2020-January 2021.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGhimire LV, Chou F-S, Aljohani OA, Moon-Grady AJ. Comparison of adverse clinical outcomes in children hospitalized for myocarditis with and without COVID-19. J Pediatr. 2023;261:113561.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBassi R, Ismail Z, Salabei JK, Charles K, Haider AA, Hussein A, et al. COVID-19-Induced Complete Heart Block: Case Series and Literature Review. Cureus. 2023;15:e37517.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eUkimura A, Izumi T, Matsumori A, Clinical Research Committee on Myocarditis Associated. with 2009 Influenza A (H1N1) Pandemic in Japan organized by Japanese Circulation Society. A national survey on myocarditis associated with the 2009 influenza A (H1N1) pandemic in Japan. Circ J. 2010;74:2193\u0026ndash;9.\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":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-cardiovascular-disorders","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bcar","sideBox":"Learn more about [BMC Cardiovascular Disorders](http://bmccardiovascdisord.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bcar/default.aspx","title":"BMC Cardiovascular Disorders","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"COVID-19, cardiovascular complications, hospital outcomes, influenza, mortality, RSV","lastPublishedDoi":"10.21203/rs.3.rs-5081257/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5081257/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eRespiratory viruses are linked to cardiovascular complications. We aim to compare cardiovascular complications due to COVID-19, influenza and RSV.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eWe analyzed cross-sectional data from hospitalized children and young adults (\u0026le;\u0026thinsp;20 years) from 2020 and 2021 using National Inpatient Sample(NIS). We included individuals hospitalized for COVID-19, RSV, and influenza, and weighted data were used to compare cardiovascular complications.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eOf 212,655 respiratory virus admissions, 85,055 were from COVID-19, 103,185 were from RSV, and 24,415 were from influenza. Myocarditis was higher in COVID-19 [0.9%,n\u0026thinsp;=\u0026thinsp;740] as compared to influenza [0.2%,n\u0026thinsp;=\u0026thinsp;55] and RSV [0.1%,n\u0026thinsp;=\u0026thinsp;65]. In the adjusted logistic regression, the odds of myocarditis was 61% lower in influenza [aOR\u0026thinsp;=\u0026thinsp;0.39 (0.20\u0026ndash;0.76), P\u0026thinsp;=\u0026thinsp;0.006], and 85% lower in RSV [aOR\u0026thinsp;=\u0026thinsp;0.15 (0.07\u0026ndash;0.34) P\u0026thinsp;\u0026lt;\u0026thinsp;0.001] as compared to COVID-19. Heart block was higher in COVID-19 [0.8%,n\u0026thinsp;=\u0026thinsp;690] versus influenza [0.5%,n\u0026thinsp;=\u0026thinsp;110] and RSV [0.2%,n\u0026thinsp;=\u0026thinsp;205]. After adjusting for confounders for heart block, compared to COVID-19, the odds of heart block was 49% lower in RSV [aOR\u0026thinsp;=\u0026thinsp;0.51 (0.33\u0026ndash;0.80), P\u0026thinsp;=\u0026thinsp;0.004] but no statistically significant difference in influenza [aOR\u0026thinsp;=\u0026thinsp;0.79 (0.48\u0026ndash;1.31), P\u0026thinsp;=\u0026thinsp;0.374] was seen. Tachyarrhythmias, cardiac arrest, and in-hospital mortality showed no differences after adjusting for covariates.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eIndividuals with COVID-19 infection are more likely to develop cardiovascular complications compared to influenza and RSV, highlighting the need for higher index of suspicion and prompt treatment, as well as steps to limit infection and transmission of this virus in children.\u003c/p\u003e","manuscriptTitle":"Comparison of mortality and cardiovascular complications due to COVID-19, RSV, and influenza in hospitalized children and young adults","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-11-10 13:49:01","doi":"10.21203/rs.3.rs-5081257/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-09-24T11:21:00+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-09-23T10:16:49+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-09-23T10:16:38+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Cardiovascular Disorders","date":"2024-09-13T05:47:12+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-cardiovascular-disorders","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bcar","sideBox":"Learn more about [BMC Cardiovascular Disorders](http://bmccardiovascdisord.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bcar/default.aspx","title":"BMC Cardiovascular Disorders","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"42c94014-acb8-4bb3-9366-c9159a2f86f7","owner":[],"postedDate":"November 10th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-12-02T17:24:10+00:00","versionOfRecord":{"articleIdentity":"rs-5081257","link":"https://doi.org/10.1186/s12872-024-04366-0","journal":{"identity":"bmc-cardiovascular-disorders","isVorOnly":false,"title":"BMC Cardiovascular Disorders"},"publishedOn":"2024-11-28 15:58:28","publishedOnDateReadable":"November 28th, 2024"},"versionCreatedAt":"2024-11-10 13:49:01","video":"","vorDoi":"10.1186/s12872-024-04366-0","vorDoiUrl":"https://doi.org/10.1186/s12872-024-04366-0","workflowStages":[]},"version":"v1","identity":"rs-5081257","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5081257","identity":"rs-5081257","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}