Epidemiological and clinical characteristics of parainfluenza virus infection in hospitalized neonates in Southeast China

Epidemiological and clinical characteristics of parainfluenza virus infection in hospitalized neonates in Southeast China | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Epidemiological and clinical characteristics of parainfluenza virus infection in hospitalized neonates in Southeast China Lianghua Lu, Yunzhu Wang, Yahui Li, Dongying Zhao This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6456374/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background: Human parainfluenza virus (HPIV) is a clinically significant pathogen responsible for acute respiratory tract infections (ARTIs) in infants. This study aimed to elucidate the epidemiological characteristics, clinical manifestations, and severity risk factors in neonates with HPIV. Methods: This retrospective study included infants admitted to the neonatology departments of two tertiary hospitals in southeast China between January 2016 and December 2023, diagnosed with lower respiratory tract infections (LRTIs) or febrile illnesses. HPIV was detected via standardized molecular assays, including either Double Amplification Technique or Direct Immunofluorescent Antibody Assay. Results: Among 7,557 neonates who underwent throat swabs, 212 neonates were tested positive for HPIV, accounting for 2.7% of all LRTI cases in the study cohort. The detection rate of HPIVs increased with age. Neonates with HPIV infection demonstrated significantly higher prevalence rates of nasal congestion (79.7% vs 59.6%, P < 0.001) and poor feeding (17% vs 4.7%, P < 0.001) compared to those with respiratory syncytial virus (RSV) infection. Conversely, moist rales (57.1% Vs 80.1%, P < 0.001) and wheezing (6.6% Vs 17.8%, P < 0.001) were observed less frequently in the HPIV group. Moreover, preterm birth, poor feeding and cyanosis were identified as significant risk factors for neonatal intensive care unit (NICU) hospitalization in HPIV-infected neonates. Conclusions : HPIV represents an important etiological agent of LRTIs among hospitalized neonates in Southeast China, exhibiting distinct clinical characteristics that differentiate it from RSV infection. Notably, preterm infants are at highest risk for severe disease manifestations,requiring intensive monitoring. neonates lower respiratory tract infections human parainfluenza virus Figures Figure 1 Introduction Lower respiratory tract infections (LRTIs) are a significant cause of morbidity and mortality among neonates, posing a substantial threat to their health. Neonatal pneumonia alone is estimated to account for 6.1% of total global neonatal mortality[ 1 ]. This alarming statistic underscores the urgent need for a deeper understanding of the etiological factors and clinical characteristics of these infections. The unique physiological anatomy of the neonatal respiratory system, coupled with an immature immune response, renders neonates particularly susceptible to a wide range of infections. These infections can be caused by various pathogens, including viruses, bacteria, and other microorganisms. Among the viral pathogens, respiratory syncytial virus (RSV) has been extensively documented as the most common cause of community-acquired pneumonia in neonates. The clinical characteristics of RSV infection in neonates have been thoroughly investigated in numerous studies [ 2 , 3 ], providing valuable insights into its epidemiology and management. However, RSV is not the sole viral culprit in neonatal LRTIs. Other viruses, such as human parainfluenza virus (HPIV), human metapneumovirus, adenovirus, influenza virus and human coronavirus were also among the predominant pathogens implicated in the etiology of neonatal viral pneumonia[ 4 ]. Distinct viral etiologies demonstrate different clinical presentations and divergent prognostic outcomes. A comprehensive understanding of the clinical manifestations associated with these viral infections enables clinicians to implement more evidence-based disease management strategies, ensuring that neonates receive the most appropriate and effective care. Early and accurate identification of the specific viral pathogen can guide targeted interventions, reduce the inappropriate use of antibiotics, and improve overall patient outcomes. Human parainfluenza virus (HPIV) was reported as the second common detected virus in neonates in some regions, following respiratory syncytial virus (RSV)[ 5 , 6 ]. HPIV exists in four genetically different types, HPIV1, HPIV2, HPIV3, and HPIV4. These are enveloped, negative‑sense RNA viruses that belong to the Paramyxoviridae family[ 7 ]. Among hospitalized children, the reported incidence of HPIVs varies, ranging from 2–10%[ 4 , 8 ]. In the United States, HPIVs accounted for 6.8% of all hospitalizations for fever or acute respiratory illnesses in children under 5 years of age, with an estimated annual hospitalization rate of 1.02 per 1000 children[ 9 ]. Globally, HPIV is responsible for 4–14% of ALRI hospital admissions and accounts for 4% of childhood ALRI mortality[ 10 ]. Outbreaks of HPIV3 infection was also reported in neonatal intensive care units[ 11 , 12 ]. However, few reports have focused on the burden and clinical characteristics of neonatal HPIV infection, and the extent of the clinical problem in this vulnerable population remains largely unknown. In this study, we aimed to elucidate the regional HPIV infection pattern among hospitalized neonates in Southeast China. In addition, we compared the clinical characteristics of HPIV and RSV infection. As RSV is a leading cause of neonatal pneumonia, understanding their differences helps clinicians distinguish between the two, enabling accurate diagnosis and tailored treatment. Methods Study design This multicenter, retrospective cohort study was conducted at two tertiary care medical centers in Southeast China: Xinhua Hospital affiliated with Shanghai Jiao Tong University School of Medicine and Children's Hospital of Soochow University. The study protocol received ethical approval from both institutional review boards (Ethics Committee of Children’s Hospital of Soochow University and the Ethics Committee of Xinhua Hospital affiliated to Shanghai Jiao Tong University School of Medicine). Study population During the study period (January 2016-December 2023), standardized respiratory specimens (throat swabs or nasopharyngeal aspirates) were collected within 24 hours of admission from neonates meeting the predefined diagnostic criteria for LRTIs or febrile illnesses (axillary temperature ≥37.3°C). LRTI diagnosis required fulfillment of all following criteria: 1) ≥2 respiratory symptoms (cough, nasal flaring, wheezing, tachypnea [>60 breaths/min], or grunting) 2) Physical examination findings (chest retractions or abnormal auscultation [crackles/wheezes]) 3) Radiographic confirmation (new-onset infiltrates on chest X-ray) [3]. Low birth weight was considered to be less than 2500 g for the present study. All throat swabs were immediately sent to the laboratory for detection of HPIV or RSV within 2 hours Laboratory methods HPIV and RSV were detected in throat swabs by Double Amplification Technique (using a seven respiratory virus nucleic acid detection kit, Zhongchi Bio, China) or nasal passage aspirates by DFA (using the D3 ultra DFA respiratory virus screening and identification kit, Athens, Ohio, USA). Nasal passage aspirates were collected as previously described[13]. Patients were additionally tested for pathogenic bacteria in tracheal aspirate using aerobic culture. Aerobic blood culture was used in cases of suspected sepsis. Data collection Data on patient demographics, clinical symptoms, complications, underlying diseases (ie, congenital heart disease, bronchopulmonary dysplasia, bronchopulmonary malformation, Down’s syndrome)[3], and laboratory findings (including radiographic outcomes) were obtained from the hospital medical records system. Chest radiography was performed using standard equipment and radiographic techniques and reviewed by radiologists in digital format. Statistical analysis Statistical analysis was performed using SPSS v.22 for Windows (SPSS Inc., Chicago, IL). Categorical data were analyzed using the Chi-square test. Continuous data were analyzed using the T-test for normally distributed data, while the Mann-Whitney test was used for data that failed to show a normal distribution. Variables with a p value of less than 0.01 in the Chi-square test were selected for binary logistic regression analysis. All tests were two-tailed, with P < 0.05 considered statistically significant. Results Incidence and demography of neonates with HPIV infection During the 8-year study period (2016-2023), a total of 7557 throat swabs were obtained from neonates hospitalized with LRTIs or febrile illness in the two tertiary hospitals. Of these, 212 cases were confirmed with HPIV, accounting for 2.7% (212/7557) of all LRTI cases. Among HPIV-positive cases, 29 (13.7%) demonstrated viral co-infections, predominantly with RSV (37.9% of co-infections), followed by adenovirus (27.6%) and influenza virus (17.2%). RSV was the most common virus in neonates co-infected with HPIV (Table 1). Table 1 Distribution of co-infection with HPIV Co-infection distribution Positive number Percent（%） RSV 11 37.9 Mycoplasma pneumoniae 5 17.2 Influenza virus 5 17.2 Adenovirus 8 27.6 Total co-infection 29 100 HPIV, Human parainfluenza virus; RSV, Respiratory syncytial virus The HPIV-infected neonates demonstrated an age range of 2-28 days (median 22 days, IQR 17-27). Gender distribution was balanced, with 109 (51.4 %) male neonates. While most cases were term infants (93.4%), only 14 neonates (6.6 %) were reported to have a gestational age of less than 37 weeks. As detailed in Table 2, HPIV detection rates exhibited a significant age-dependent increase, progressing from 0.3% in the first postnatal week to 4.1% by the fourth week. Table 2 Age distribution of hospitalized neonates with lower respiratory tract infections (LRTI) related to HPIV Age HPIV positive cases Total cases Incidence (%) ～1w 4 1163 0.3 ～2w 31 1340 2.3 ～3w 59 2218 2.7 ～4w 118 2836 4.1 Monthly distribution of neonates with HPIV infection In general, HPIV infections exhibited attenuated seasonal fluctuations, distinct from RSV's marked winter seasonality (November-February). The monthly variation in HPIV incidence is relatively modest. Case counts demonstrated a significant 1.8-fold increase in the second versus first semester (136 vs 76 cases, P <0.05), with distinct summer peaks in July (n=28) and August (n=30) accounting for 27.3% of annual cases (Figure. 1). Clinical and laboratory characteristics in neonates with HPIV and RSV infection Clinical and laboratory characteristics in neonates with HPIV and RSV infection are summarized in Table 3 (Table3 is presented at the end of the manuscript). HPIV-infected neonates presented at significantly older postnatal ages (median 23 days, IQR 17-27) compared to RSV cases (median 17 days, IQR 13-24, P < 0.05). Nasal congestion was markedly more prevalent in HPIV cases (79.7% vs 59.6%, P < 0.05). Feeding difficulties were 3.6-fold more common with HPIV (17% vs 4.7%, P< 0.05). Auscultatory findings showed inverse patterns: moist rales (57.1% vs 80.1%, P< 0.05) and wheezing rales (6.6% vs 17.8%, P< 0.05) were significantly less prevalent in HPIV cases. The percentage of underlying conditions in HPIV- positive neonates was more than triple that observed in RSV-positive neonates (15.6% vs 4.0%, P< 0.05), particularly congenital heart disease (9.4% vs 2.1%). Liver impairment was more common with HPIV (15.7% vs 8.7%, P< 0.05), whereas myocardial stress markers (55.6% vs 83.4%, P< 0.05) predominated in RSV cases. Critical care requirements showed no intergroup differences: supplemental oxygen (13.7% vs 15.7%, P=0.444) and mechanical ventilation (1.4% vs 1.6%, P=0.880) were similarly utilized (Table 3). Median hospitalization duration was identical (10 days, IQR 8-12) regardless of viral etiology, suggesting comparable disease acuity despite phenotypic differences. Table 3 Comparison of Clinical and laboratory characteristics between neonates with HPIV and RSV infection. Clinical parameters value HPIV-LRTI (n=212) RSV-LRTI (n=1547) P value Demographic data Age (median, IQR) 23 (17-27) 17 (13-24) <0.001 Sex (male, %) 109 (51.4) 848 (54.8) 0.351 Preterm birth (n, %) 14 (6.6) 55 (3.6) 0.032 Birth weight (median, IQR) 3300 (3000-3600) 3350 (3100-3600) 0.082 Underlying condition (n, %) 33 (15.6) 76(4.9) <0.001 Clinical symptoms Cough (n, %) 204 (96.2) 1538 (99.4) <0.001 Stuffy nose (n, %) 169 (79.7) 922 (59.6) <0.001 Fever (n, %) 62 (29.2) 390 (25.2) 0.207 Dyspnea (n,%) 3 (1.4) 31 (2) 0.559 Cyanosis (n, %) 16 (7.5) 76(4.9) 0.106 Refusal to feed (n, %) 36 (17) 72 (4.7) <0.001 Diarrhoea (n, %) 25 (11.8) 256 (16.5) 0.076 Jaundice (n, %) 32 (15.1) 248 (16.0) 0.727 Physical examination Moist rales (n, %) 121(57.1) 1239 (80.1) <0.001 Wheezing rales (n, %) 14 (6.6) 275 (17.8) <0.001 Laboratory Tests White blood cells (median, IQR) 9.5 (7.3-12.8) 8.35 (6.8-10.1) <0.001 Alanine transaminase increase (n, %) 33 (15.7) 133 (8.7) 0.001 Creatine kinase-MB increase (n, %) 115 (55.6) 777(83.4) <0.001 Abnormal chest X-ray (n, %) 187 (88.2) 1411 (91.2 ) 0.155 Therapy Supplemental oxygen (n, %) 29 (13.7) 243(15.7) 0.444 Mechanical ventilation (n, %) 3 (1.4) 24 (1.6) 0.880 Duration of hospital days (median, IQR) 10 (8-13) 10 (8-12) 0.413 Underlying conditions: Congenital heart disease; Bronchopulmonary dysplasia; Bronchopulmonary malformation; HPIV, Human parainfluenza virus; RSV, Respiratory syncytial virus; LRTI, Lower respiratory tract infections; IQR, Inter-quartile ranges. In the present study, a total of 12 cases were hospitalized in the NICU and health care in the NICU was considered a marker of severe illness. Compared to neonates admitted to the ward, NICU-admitted neonates exhibited higher rates of: preterm birth (41.7% vs 4.5%), cyanosis (50% vs 5%), and feeding refusal (50% vs 15%) (all P < 0.05). Multivariate analysis by logistic regression revealed that preterm birth and cyanosis were high risk factors for NICU stay (Table 4). Table 4 Risk factors of NICU stay in neonates with HPIV related LRTI Parameters NICU Ward P OR 95% CI n =12 n=200 Low limit Up limit Preterm (n, %) 5 (41.7) 9 (4.5） <0.001 165.0 14 1901 Cyanosis (n, %) 6 (50) 10 (5) <0.001 67.8 7.0 660.8 Refusal to feed (n, %) 6 (50) 30 (15) 0.038 7.1 0.988 45.5 HPIV, Human parainfluenza virus; LRTI, Lower respiratory tract infections; NICU, neonatal intensive care unit; OR, odds ration; CI, confidence interval. Discussion Human parainfluenza virus (HPIV) infections are a common cause of morbidity in neonates, particularly those hospitalized with LRTI. Our study focused on investigating the epidemiological and clinical features of HPIV infections among hospitalized neonates in two tertiary hospitals located in Southeast China. The results of our research provide valuable insights into the infection patterns and risk factors associated with severe disease outcomes in neonates affected by HPIV. Our findings revealed that HPIV accounts for 2.7% of all LRTI cases in neonates. When compared to the incidence reported in Ningbo province in China, which was 3.06% (30 out of 981 cases) [14], our observed rate was slightly lower. Additionally, it was only half of the incidence observed in a study conducted in Korea, where HPIV was identified in 6.9% (5 out of 72) of neonatal LRTI cases[5]. These differences in incidence rates may be attributed to regional epidemiological variations, as well as disparities in the methodologies used for pathogen detection across different studies. It is important to consider these factors when interpreting and comparing incidence data from various regions. Furthermore, our data demonstrate an age-dependent increase in HPIV incidence. This trend is similar to the epidemiology of RSV [3]. The age-dependent increase in HPIV incidence can help explain the relatively lower infection rates observed in neonatal populations compared to children under five years of age [7]. In this study, we did not incorporate HPIV subtype stratification in our analysis. This limitation was primarily due to the detection methodology employed. Specifically, HPIV was detected using pan-viral detection assays, which are broad-spectrum tests designed to identify a wide range of viral pathogens. While these assays are valuable for detecting the presence of HPIV, they do not provide detailed information on specific subtypes. The decision to use pan-viral detection assays was largely driven by resource constraints, as more specialized subtype-specific assays can be costly and may not be feasible in both research settings. Despite this limitation, we can still draw some inferences about the likely dominant subtype based on existing data. According to national surveillance reports from the Chinese Center for Disease Control and Prevention (China CDC), HPIV-3 is the predominant subtype in China. The aggregate data from 2019 to 2023 indicate that HPIV-3 constitutes over 50% of all laboratory-confirmed HPIV cases in the country[15]. Existing studies also demonstrated that HPIV3 exhibits the highest infection rate among pediatric HPIV cases[7, 16]. Moreover, HPIV3 was reported to cause outbreak in neonatal care unit[11]. Given the heightened vulnerability of neonates, the presence of HPIV-3 in neonatal care units can lead to significant morbidity and challenges in infection control. Considering these lines of evidence, it is reasonable to infer that HPIV-3 is likely the dominant subtype in our neonatal cohort. Future studies with more detailed subtype-specific analyses would be valuable in confirming this inference and providing a more comprehensive understanding of HPIV infections in neonatal populations. When comparing HPIV infections to RSV infections in neonates, our study revealed some notable differences in the clinical profiles of affected infants. Specifically, neonates infected with HPIV had a higher percentage of preterm births compared to those infected with RSV. Furthermore, we found that a higher proportion of HPIV-positive neonates had underlying conditions compared to RSV-positive neonates. This finding underscores the potential complexity of HPIV infections in neonates, as preterm birth and underlying conditions can exacerbate the severity of respiratory illnesses. However, interestingly, the presence of these underlying conditions did not influence the neonatal intensive care unit (NICU) admission rates for HPIV-positive neonates. This contrasts with the observations made in RSV-positive neonates, where underlying conditions were associated with increased NICU admissions[3]. This discrepancy may be attributed to differences in monitoring equipment and NICU administration procedures across different hospitals. It is possible that the specific protocols and resources available in the NICU settings of our study hospitals influenced the management and admission decisions for HPIV-positive neonates. In this study, we identified prematurity and cyanosis as significant risk factors for severe disease requiring NICU admission among neonates with HPIV infections. These findings are clinically relevant, as they can help clinicians in the early identification of neonates who are at higher risk of severe diseases. By recognizing these risk factors, healthcare providers can implement closer monitoring, more targeted interventions, or preemptive treatments to improve outcomes for these vulnerable infants. Our results emphasize the importance of considering both prematurity and cyanosis as key indicators for potential severe HPIV infections, enabling healthcare teams to provide the most appropriate and timely care to neonates in need. In contrast to the distinct winter-spring seasonal peak characteristic of RSV infections, HPIV demonstrates no pronounced seasonal surge during these periods. We noticed a slight peak prevalence during the summer months, which was also observed in previous report[15, 17] . This pattern may be associated with several factors. Firstly, there is an outbreak of Coronavirus Disease 2019(COVID-19) pandemic in china from 2020. The pandemic may cause changes in circulation patterns of HPIV infections[18, 19]. Secondly, increasing indoor activities of elder children and closer contact with neonates during vacations, facilitating the transmission of respiratory viruses. Decreasing infections of other highly contagious viruses, such as RSV, in summer may also decrease the public awareness of infection prevention. Therefore, health interventions promotion, such as hand hygiene practices, targeting these periods could potentially reduce the incidence of HPIV infections. The clinical presentation of HPIV infection in neonates is nonspecific and often mimics other respiratory infections such as RSV. This makes it challenging to differentiate between the two infections based on clinical symptoms alone. However, our study found that HPIV-positive neonates were more likely to present with symptoms like stuffy nose and refusal to feed, which could be useful in differentiating HPIV from other infections. Early detection is crucial as it helps prevent or reduce the inappropriate use of antibiotics, which is particularly important given the nonspecific clinical presentation of HPIV infections. Accurate and timely diagnosis allows for more targeted and appropriate treatment strategies, improving patient outcomes and reducing the risk of severe diseases. Moreover, the medical burden of HPIV infections urges the need for vaccines for clinical prevention as there is no effective vaccines available at present[20, 21]. Our study has some limitations. Firstly, this retrospective study was conducted in only two tertiary hospitals, which limits the generalizability of our findings. There were also selection biases as the study relied on hospital admissions. Secondly, we analyzed the monthly distribution of HPIV infection without considering the COVID-19 prevalence (year 2020 and 2021) during the study period as different epidemic prevention policies adopted in the two cities. Therefore, the epidemic effect on HPIV infection cannot be excluded[22]. Last but not least, different unique protocols and detection tools in the two hospitals may affect the reliability of the findings. Future research should aim to validate our findings in a larger, multicenter cohort and explore the role of other factors such as maternal health, environmental exposures and feeding patterns in the pathogenesis of HPIV infection. Conclusions This study demonstrates that HPIV is a significant etiological agent of LRTIs in hospitalized neonates in Southeast China, accounting for 2.7% of cases. Our findings highlight distinct clinical features of HPIV infection, including a higher prevalence of nasal congestion and feeding difficulties compared to RSV, as well as lower rates of wheezing and moist rales. Importantly, preterm birth and cyanosis were identified as key risk factors for severe disease requiring NICU admission. Abbreviations HPIV, human parainfluenza virus; LRTI, lower respiratory tract infection; RSV, respiratory syncytial virus; NICU, neonatal intensive care unit; COVID-19, Coronavirus Disease 2019. Declarations Ethics declaration This study was approved by the Ethics Committee of the Children’s Hospital of Soochow University and the Ethics Committee of Xinhua Hospital affiliated with Shanghai Jiao Tong University School of Medicine. All parents or legal guardians were fully informed of the research protocol and provided written consent. Clinical trial number Not applicable Consent for publication Not applicable Availability of data and materials The datasets used and analyzed during this study are available from the corresponding author upon reasonable request. Competing interests The authors declare that they have no competing interests. Funding This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors. Authors’ contributions Lianghua Lu: Conception, data collection and analysis; Yunzhu Wang: Data collection, figures preparation; Yahui Li: Data analysis, manuscript draft; Dongying Zhao: Supervision, conception and design, manuscript review and editing. All authors read and approved the final manuscript References Nair NS, Lewis LE, Dhyani VS, Murthy S, Godinho M, Lakiang T, et al. Factors Associated With Neonatal Pneumonia and its Mortality in India: A Systematic Review and Meta-Analysis. Indian Pediatr. 2021;58(11):1059-66. Cerar S, Kučan R, Paro-Panjan D, Nosan G. The burden of viral lower respiratory tract infections during the neonatal period: six-year experience at a tertiary referral hospital. Croat Med J. 2022;63(4):343. Lu L, Yan Y, Yang B, Xiao Z, Feng X, Wang Y, et al. Epidemiological and clinical profiles of respiratory syncytial virus infection in hospitalized neonates in Suzhou, China. BMC Infect Dis. 2015;15(1):431. Perez A, Lively JY, Curns A, Weinberg GA, Halasa NB, Staat MA, et al. Respiratory Virus Surveillance Among Children with Acute Respiratory Illnesses - New Vaccine Surveillance Network, United States, 2016-2021. MMWR Morb Mortal Wkly Rep. 2022;71(40):1253-9. Song WS, Song BJ, Kim WD. Clinical Characteristics of Acute Respiratory Tract Infections in Full-Term Newborns without Risk Factors. Neonatal Med. 2015;22(1):27-33. Guan X, Gao S, Zhao H, Zhou H, Yang Y, Yu S, et al. Clinical characteristics of hospitalized term and preterm infants with community-acquired viral pneumonia. BMC Pediatr. 2022;22(1):1-10. Wang F, Zhao LQ, Zhu RN, Deng J, Sun Y, Ding YX, et al. Parainfluenza Virus Types 1, 2, and 3 in Pediatric Patients with Acute Respiratory Infections in Beijing During 2004 to 2012. Chin Med J (Engl). 2015;128(20):2726-30. Feng L, Lai S, Li F, Ye X, Li S, Ren X, et al. Viral etiologies of hospitalized pneumonia patients aged less than five years in six provinces, 2009-2012. Chin J Epidemiol. 2014;35(6):646-9. Weinberg GA, Hall CB, Iwane MK, Poehling KA, Edwards KM, Griffin MR, et al. Parainfluenza Virus Infection of Young Children: Estimates of the Population-Based Burden of Hospitalization. J Pediatr. 2009;154(5):694-9. Wang X, Li Y, Deloria-Knoll M, Madhi SA, Cohen C, Arguelles VL, et al. Global burden of acute lower respiratory infection associated with human parainfluenza virus in children younger than 5 years for 2018: a systematic review and meta-analysis. Lancet Glob Health. 2021;9(8):E1077-87. Maeda H, Haneda K, Honda Y. Parainfluenza virus type 3 outbreak in a neonatal intensive care unit. Pediatr Int. 2017;59(11):1219-22. Moisiuk S, Robson D, Klass L, Kliewer G, Wasyliuk W, Davi M, et al. Outbreak of parainfluenza virus type 3 in an intermediate care neonatal nursery. Pediatr Infect Dis J. 1998;17(1):49-53. Chen ZR, Ji W, Wang YQ, Yan YD, Shao XJ, Zhang XL, et al. Etiology of acute bronchiolitis and the relationship with meteorological conditions in hospitalized infants in China. J Formos Med Assoc. 2014;113(7):463-9. Zhou CB, Lu WW, Zhang YZ, et al. Analysis of detection of 13 respiratory non-bacterial pathogens in children in Ningbo area from 2019 to 2021. Zhonghua Yu Fang Yi Xue Za Zhi. 2022;56(12):1751-8. Gao Y, Ma Y, Feng D, Zhang F, Wang B, Liu X, et al. Epidemiological Characteristics of Human Parainfluenza Viruses Infections - China, 2019-2023. China CDC Wkly. 2024;6(12):235-41. Abu-Helalah M, Abu Lubad M, Al-Hanaktah M, Al Tibi A, Alhousani M, Drysdale SB. The Epidemiology and Clinical Burdens of Human Parainfluenza Virus Infections Amongst Hospitalized Children Under 5 Years of Age in Jordan: A National Multi-Center Cross-Sectional Study. Viruses. 2025;17(2):170. Chen Z, Zhu Y, Wang Y, Zhou W, Yan Y, Zhu C, et al. Association of meteorological factors with childhood viral acute respiratory infections in subtropical China: an analysis over 11 years. Arch Virol. 2014;159(4):631-9 Laird TS, Hamilton M, William N, Karanwal S, Marsh K, Evans J. Trends in human parainfluenza virus in Scotland before and after the peak of the COVID-19 pandemic, January 2017 to October 2023. Euro Surveill. 2025;30(2):2400147. Kim HM, Rhee JE, Lee NJ, Woo SH, Park AK, Lee J, et al. Recent increase in the detection of human parainfluenza virus during the coronavirus disease-2019 pandemic in the Republic of Korea. Virol J. 2022;19(1) Outlaw VK, Cheloha RW, Jurgens EM, Bovier FT, Zhu Y, Kreitler DF, et al. Engineering protease-resistant peptides to inhibit human parainfluenza viral respiratory infection. J Am Chem Soc. 2021;143(15):5958-66. Mackow N, Amaro-Carambot E, Liang B, Surman S, Lingemann M, Yang L, et al. Attenuated Human Parainfluenza Virus Type 1 (HPIV1) Expressing the Fusion Glycoprotein of Human Respiratory Syncytial Virus (RSV) as a Bivalent HPIV1/RSV Vaccine. J Virol. 2015;89 (20):10319-32. Wu R, Zhang J, Mo L. Analysis of respiratory virus detection in hospitalized children with acute respiratory infection during the COVID-19 pandemic. Virol J. 2023; 20:25 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted 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-6456374","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":458689579,"identity":"85233ff7-3f5f-4a2d-986f-3781c3c2d009","order_by":0,"name":"Lianghua Lu","email":"","orcid":"","institution":"Children's hospital of Soochow University","correspondingAuthor":false,"prefix":"","firstName":"Lianghua","middleName":"","lastName":"Lu","suffix":""},{"id":458689580,"identity":"410e3958-940c-40e1-885b-8cec860dc8d0","order_by":1,"name":"Yunzhu Wang","email":"","orcid":"","institution":"Kunshan Sixth People's Hospital","correspondingAuthor":false,"prefix":"","firstName":"Yunzhu","middleName":"","lastName":"Wang","suffix":""},{"id":458689582,"identity":"f441773a-c770-484b-8277-44c5d4c1771d","order_by":2,"name":"Yahui Li","email":"","orcid":"","institution":"Xinhua Hostital, Shanghai Jiao Tong University School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Yahui","middleName":"","lastName":"Li","suffix":""},{"id":458689583,"identity":"b55e41b2-c7c4-4c62-b2f8-8fa52fe60646","order_by":3,"name":"Dongying Zhao","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA9UlEQVRIiWNgGAWjYFCCBIYDiX9s7OwPHD7A8MCAOC2MDz42pCUzHDyWwJBApBZmw5kNhxgbDp8xANpIBJBvzzGT5t1xgJmx7czHDwkFhxO3MzA/fHQDjxbGnjdALWfu8DHznN0skWBwOHFnA5uxcQ4eLcwSQFt42J4xs0mc3QDWsuEAD5s0Pi1sEC2HGXvk3zz+QZQWHokcY8OZbYcZZzCcYSPOFgmeZ4UPPpxJSzZgOGZmkWCQbrzhMAG/yLcnbziQUGFjZ8Bw+PGND3+sZTccb374GJ8WBgYOlOhrBoYIXuUgwP4AmVdHUP0oGAWjYBSMPAAAveNW6PjrY8oAAAAASUVORK5CYII=","orcid":"","institution":"Xinhua Hostital, Shanghai Jiao Tong University School of Medicine","correspondingAuthor":true,"prefix":"","firstName":"Dongying","middleName":"","lastName":"Zhao","suffix":""}],"badges":[],"createdAt":"2025-04-15 15:38:20","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6456374/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6456374/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":83282182,"identity":"c42d61a4-4c99-484e-8683-d922e4438f36","added_by":"auto","created_at":"2025-05-22 10:32:21","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":47734,"visible":true,"origin":"","legend":"\u003cp\u003eMonthly distribution of HPIV and RSV infection in hospitalized neonates with LRTI\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-6456374/v1/febf841ab3d87ecb103e2610.jpeg"},{"id":93014958,"identity":"a482b1c1-d03e-4efd-94b3-24142bf10b06","added_by":"auto","created_at":"2025-10-08 07:47:08","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":891034,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6456374/v1/8adc5674-7a88-446b-bb91-e638de7663ec.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Epidemiological and clinical characteristics of parainfluenza virus infection in hospitalized neonates in Southeast China","fulltext":[{"header":"Introduction","content":"\u003cp\u003eLower respiratory tract infections (LRTIs) are a significant cause of morbidity and mortality among neonates, posing a substantial threat to their health. Neonatal pneumonia alone is estimated to account for 6.1% of total global neonatal mortality[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. This alarming statistic underscores the urgent need for a deeper understanding of the etiological factors and clinical characteristics of these infections.\u003c/p\u003e \u003cp\u003eThe unique physiological anatomy of the neonatal respiratory system, coupled with an immature immune response, renders neonates particularly susceptible to a wide range of infections. These infections can be caused by various pathogens, including viruses, bacteria, and other microorganisms. Among the viral pathogens, respiratory syncytial virus (RSV) has been extensively documented as the most common cause of community-acquired pneumonia in neonates. The clinical characteristics of RSV infection in neonates have been thoroughly investigated in numerous studies [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e], providing valuable insights into its epidemiology and management.\u003c/p\u003e \u003cp\u003eHowever, RSV is not the sole viral culprit in neonatal LRTIs. Other viruses, such as human parainfluenza virus (HPIV), human metapneumovirus, adenovirus, influenza virus and human coronavirus were also among the predominant pathogens implicated in the etiology of neonatal viral pneumonia[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Distinct viral etiologies demonstrate different clinical presentations and divergent prognostic outcomes. A comprehensive understanding of the clinical manifestations associated with these viral infections enables clinicians to implement more evidence-based disease management strategies, ensuring that neonates receive the most appropriate and effective care. Early and accurate identification of the specific viral pathogen can guide targeted interventions, reduce the inappropriate use of antibiotics, and improve overall patient outcomes.\u003c/p\u003e \u003cp\u003eHuman parainfluenza virus (HPIV) was reported as the second common detected virus in neonates in some regions, following respiratory syncytial virus (RSV)[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. HPIV exists in four genetically different types, HPIV1, HPIV2, HPIV3, and HPIV4. These are enveloped, negative‑sense RNA viruses that belong to the Paramyxoviridae family[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Among hospitalized children, the reported incidence of HPIVs varies, ranging from 2\u0026ndash;10%[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. In the United States, HPIVs accounted for 6.8% of all hospitalizations for fever or acute respiratory illnesses in children under 5 years of age, with an estimated annual hospitalization rate of 1.02 per 1000 children[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Globally, HPIV is responsible for 4\u0026ndash;14% of ALRI hospital admissions and accounts for 4% of childhood ALRI mortality[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Outbreaks of HPIV3 infection was also reported in neonatal intensive care units[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. However, few reports have focused on the burden and clinical characteristics of neonatal HPIV infection, and the extent of the clinical problem in this vulnerable population remains largely unknown.\u003c/p\u003e \u003cp\u003eIn this study, we aimed to elucidate the regional HPIV infection pattern among hospitalized neonates in Southeast China. In addition, we compared the clinical characteristics of HPIV and RSV infection. As RSV is a leading cause of neonatal pneumonia, understanding their differences helps clinicians distinguish between the two, enabling accurate diagnosis and tailored treatment.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cstrong\u003e\u003cem\u003eStudy design\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis multicenter, retrospective cohort study was conducted at two tertiary care medical centers in Southeast China: Xinhua Hospital affiliated with Shanghai Jiao Tong University School of Medicine and Children\u0026apos;s Hospital of Soochow University. The study protocol received ethical approval from both institutional review boards (Ethics Committee of Children\u0026rsquo;s Hospital of Soochow University and the Ethics Committee of Xinhua Hospital affiliated to Shanghai Jiao Tong University School of Medicine).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eStudy population\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDuring the study period (January 2016-December 2023), standardized respiratory specimens (throat swabs or nasopharyngeal aspirates) were collected within 24 hours of admission from neonates meeting the predefined diagnostic criteria for LRTIs or febrile illnesses (axillary temperature \u0026ge;37.3\u0026deg;C). LRTI diagnosis required fulfillment of all following criteria: 1) \u0026ge;2 respiratory symptoms (cough, nasal flaring, wheezing, tachypnea [\u0026gt;60 breaths/min], or grunting) 2) Physical examination findings (chest retractions or abnormal auscultation [crackles/wheezes]) 3) Radiographic confirmation (new-onset infiltrates on chest X-ray) [3]. Low birth weight was considered to be less than 2500 g for the present study. All throat swabs were immediately sent to the laboratory for detection of HPIV or RSV within 2 hours\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eLaboratory methods\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eHPIV\u0026nbsp;and RSV were detected in throat swabs by Double Amplification Technique (using a seven respiratory virus nucleic acid detection kit, Zhongchi Bio, China) or nasal passage aspirates by DFA (using the D3 ultra DFA respiratory virus screening and identification kit, Athens, Ohio, USA). Nasal passage aspirates were collected as previously described[13]. Patients were additionally tested for pathogenic bacteria in tracheal aspirate using aerobic culture. Aerobic blood culture was used in cases of suspected sepsis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eData collection\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData on patient demographics, clinical symptoms, complications, underlying diseases (ie, congenital heart disease, bronchopulmonary dysplasia, bronchopulmonary malformation, Down\u0026rsquo;s syndrome)[3], and laboratory findings (including radiographic outcomes) were obtained from the hospital medical records system. Chest radiography was performed using standard equipment and radiographic techniques and reviewed by radiologists in digital format.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eStatistical analysis\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eStatistical analysis was performed using SPSS v.22 for Windows (SPSS Inc., Chicago, IL). Categorical data were analyzed using the Chi-square test. Continuous data were analyzed using the T-test for normally distributed data, while the Mann-Whitney test was used for data that failed to show a normal distribution. Variables with a p value of less than 0.01 in the Chi-square test were selected for binary logistic regression analysis. All tests were two-tailed, with P \u0026lt; 0.05 considered statistically significant.\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003e\u003cem\u003eIncidence and demography of neonates with HPIV infection\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDuring the 8-year study period (2016-2023), a total of 7557 throat swabs were obtained from neonates hospitalized with LRTIs or febrile illness in the two tertiary hospitals. Of these, 212 cases were confirmed with HPIV, accounting for 2.7% (212/7557) of all LRTI cases. Among HPIV-positive cases, 29 (13.7%) demonstrated viral co-infections, predominantly with RSV (37.9% of co-infections), followed by adenovirus (27.6%) and influenza virus (17.2%). RSV was the most common virus in neonates co-infected with HPIV (Table 1).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1 Distribution of co-infection with HPIV\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 38.664%;\"\u003e\n \u003cp\u003eCo-infection distribution\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31.5789%;\"\u003e\n \u003cp\u003ePositive number\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29.7571%;\"\u003e\n \u003cp\u003ePercent（%）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 38.664%;\"\u003e\n \u003cp\u003eRSV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31.5789%;\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29.7571%;\"\u003e\n \u003cp\u003e37.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 38.664%;\"\u003e\n \u003cp\u003eMycoplasma pneumoniae\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31.5789%;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29.7571%;\"\u003e\n \u003cp\u003e17.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 38.664%;\"\u003e\n \u003cp\u003eInfluenza virus \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31.5789%;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29.7571%;\"\u003e\n \u003cp\u003e17.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 38.664%;\"\u003e\n \u003cp\u003eAdenovirus \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31.5789%;\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29.7571%;\"\u003e\n \u003cp\u003e27.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 38.664%;\"\u003e\n \u003cp\u003eTotal co-infection \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 31.5789%;\"\u003e\n \u003cp\u003e29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29.7571%;\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eHPIV, Human parainfluenza virus; RSV, Respiratory syncytial virus \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe HPIV-infected neonates demonstrated an age range of 2-28 days (median 22 days, IQR 17-27). Gender distribution was balanced, with 109 (51.4 %) male neonates. While most cases were term infants (93.4%), only 14 neonates (6.6 %) were reported to have a gestational age of less than 37 weeks. As detailed in Table 2, HPIV detection rates exhibited a significant age-dependent increase, progressing from 0.3% in the first postnatal week to 4.1% by the fourth week.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2 Age distribution of hospitalized neonates with lower respiratory tract infections (LRTI) related to HPIV\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"523\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 18.7023%;\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 30.5344%;\"\u003e\n \u003cp\u003eHPIV positive cases\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21.9466%;\"\u003e\n \u003cp\u003eTotal cases\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28.8168%;\"\u003e\n \u003cp\u003eIncidence (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 18.7023%;\"\u003e\n \u003cp\u003e～1w\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 30.5344%;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21.9466%;\"\u003e\n \u003cp\u003e1163\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28.8168%;\"\u003e\n \u003cp\u003e0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 18.7023%;\"\u003e\n \u003cp\u003e～2w\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 30.5344%;\"\u003e\n \u003cp\u003e31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21.9466%;\"\u003e\n \u003cp\u003e1340\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28.8168%;\"\u003e\n \u003cp\u003e2.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 18.7023%;\"\u003e\n \u003cp\u003e～3w\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 30.5344%;\"\u003e\n \u003cp\u003e59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21.9466%;\"\u003e\n \u003cp\u003e2218\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28.8168%;\"\u003e\n \u003cp\u003e2.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 18.7023%;\"\u003e\n \u003cp\u003e～4w\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 30.5344%;\"\u003e\n \u003cp\u003e118\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21.9466%;\"\u003e\n \u003cp\u003e2836\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28.8168%;\"\u003e\n \u003cp\u003e4.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eMonthly distribution of neonates with HPIV infection\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn general, HPIV infections exhibited attenuated seasonal fluctuations, distinct from RSV\u0026apos;s marked winter seasonality (November-February). The monthly variation in HPIV incidence is relatively modest. Case counts demonstrated a significant 1.8-fold increase in the second versus first semester (136 vs 76 cases, \u003cem\u003eP\u003c/em\u003e\u0026lt;0.05), with distinct summer peaks in July (n=28) and August (n=30) accounting for 27.3% of annual cases (Figure. 1).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eClinical and laboratory characteristics in neonates with HPIV and RSV infection\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eClinical and laboratory characteristics in neonates with HPIV and RSV infection are summarized in Table 3 (Table3 is presented at the end of the manuscript). HPIV-infected neonates presented at significantly older postnatal ages (median 23 days, IQR 17-27) compared to RSV cases (median 17 days, IQR 13-24, \u003cem\u003eP\u003c/em\u003e\u0026lt; 0.05). Nasal congestion was markedly more prevalent in HPIV cases (79.7% vs 59.6%, \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05). Feeding difficulties were 3.6-fold more common with HPIV (17% vs 4.7%, P\u0026lt; 0.05). Auscultatory findings showed inverse patterns: moist rales (57.1% vs 80.1%, P\u0026lt; 0.05) and wheezing rales (6.6% vs 17.8%, P\u0026lt; 0.05) were significantly less prevalent in HPIV cases. The percentage of underlying conditions in HPIV- positive neonates was more than triple that observed in RSV-positive neonates (15.6% vs 4.0%, P\u0026lt; 0.05), particularly congenital heart disease (9.4% vs 2.1%).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eLiver impairment was more common with HPIV (15.7% vs 8.7%, P\u0026lt; 0.05), whereas myocardial stress markers (55.6% vs 83.4%, P\u0026lt; 0.05) predominated in RSV cases. Critical care requirements showed no intergroup differences: supplemental oxygen (13.7% vs 15.7%, P=0.444) and mechanical ventilation (1.4% vs 1.6%, P=0.880) were similarly utilized (Table 3). Median hospitalization duration was identical (10 days, IQR 8-12) regardless of viral etiology, suggesting comparable disease acuity despite phenotypic differences.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3 Comparison of Clinical and laboratory characteristics between neonates with HPIV and RSV infection.\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"646\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 280px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eClinical parameters value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHPIV-LRTI\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(n=212) \u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRSV-LRTI\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(n=1547)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eP value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 280px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDemographic data\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 280px;\"\u003e\n \u003cp\u003eAge (median, IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003e23 (17-27)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003e17 (13-24)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 280px;\"\u003e\n \u003cp\u003eSex (male, %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003e109 (51.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003e848 (54.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e0.351\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 280px;\"\u003e\n \u003cp\u003ePreterm birth (n, %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003e14 (6.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003e55 (3.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e0.032\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 280px;\"\u003e\n \u003cp\u003eBirth weight (median, IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003e3300 (3000-3600)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003e3350 (3100-3600)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e0.082\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 280px;\"\u003e\n \u003cp\u003eUnderlying condition (n, %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003e33 (15.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003e76(4.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 280px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eClinical symptoms\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 280px;\"\u003e\n \u003cp\u003eCough (n, %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003e204 (96.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003e1538 (99.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 280px;\"\u003e\n \u003cp\u003eStuffy nose (n, %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003e169 (79.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003e922 (59.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 280px;\"\u003e\n \u003cp\u003eFever (n, %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003e62 (29.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003e390 (25.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e0.207\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 280px;\"\u003e\n \u003cp\u003eDyspnea (n,%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003e3 (1.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003e31 (2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e0.559\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 280px;\"\u003e\n \u003cp\u003eCyanosis (n, %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003e16 (7.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003e76(4.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e0.106\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 280px;\"\u003e\n \u003cp\u003eRefusal to feed (n, %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003e36 (17)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003e72 (4.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 280px;\"\u003e\n \u003cp\u003eDiarrhoea (n, %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003e25 (11.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003e256 (16.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e0.076\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 280px;\"\u003e\n \u003cp\u003eJaundice (n, %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003e32 (15.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003e248 (16.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e0.727\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 280px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePhysical examination\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 280px;\"\u003e\n \u003cp\u003eMoist rales (n, %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003e121(57.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003e1239 (80.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 280px;\"\u003e\n \u003cp\u003eWheezing rales (n, %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003e14 (6.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003e275 (17.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 280px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLaboratory Tests\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 280px;\"\u003e\n \u003cp\u003eWhite blood cells (median, IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003e9.5 (7.3-12.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003e8.35 (6.8-10.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 280px;\"\u003e\n \u003cp\u003eAlanine transaminase increase (n, %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003e33 (15.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003e133 (8.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 280px;\"\u003e\n \u003cp\u003eCreatine kinase-MB increase (n, %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003e115 (55.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003e777(83.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 280px;\"\u003e\n \u003cp\u003eAbnormal chest X-ray (n, %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003e187 (88.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003e1411 (91.2 )\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e0.155\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 280px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTherapy\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 280px;\"\u003e\n \u003cp\u003eSupplemental oxygen (n, %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003e29 (13.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003e243(15.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e0.444\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 280px;\"\u003e\n \u003cp\u003eMechanical ventilation (n, %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003e3 (1.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003e24 (1.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e0.880\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 280px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDuration of hospital days\u0026nbsp;\u003c/strong\u003e(median, IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003e\u0026nbsp;10 (8-13)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003e10 (8-12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e0.413\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eUnderlying conditions: Congenital heart disease; Bronchopulmonary dysplasia; Bronchopulmonary malformation; HPIV, Human parainfluenza virus; RSV, Respiratory syncytial virus; LRTI, Lower respiratory tract infections; IQR, Inter-quartile ranges.\u003c/p\u003e\n\u003cp\u003eIn the present study, a total of 12 cases were hospitalized in the NICU and health care in the NICU was considered a marker of severe illness. Compared to neonates admitted to the ward, NICU-admitted neonates exhibited higher rates of: preterm birth (41.7% vs 4.5%), cyanosis (50% vs 5%), and feeding refusal (50% vs 15%) (all \u003cem\u003eP\u003c/em\u003e\u0026lt; 0.05). Multivariate analysis by logistic regression revealed that preterm birth and cyanosis were high risk factors for NICU stay (Table 4).\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4 Risk factors of NICU stay in neonates with HPIV related LRTI\u003c/strong\u003e\u003c/p\u003e\n\u003cdiv align=\"\"\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"610\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 172px;\"\u003e\n \u003cp\u003eParameters\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003eNICU\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003eWard\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 62px;\"\u003e\n \u003cp\u003eP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 65px;\"\u003e\n \u003cp\u003eOR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 163px;\"\u003e\n \u003cp\u003e95% CI\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003en =12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003en=200\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003eLow limit\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003eUp limit\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 172px;\"\u003e\n \u003cp\u003ePreterm (n, %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e5 (41.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e9 (4.5）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e165.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e1901\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 172px;\"\u003e\n \u003cp\u003eCyanosis (n, %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e6 (50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e10 (5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e67.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e7.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e660.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 172px;\"\u003e\n \u003cp\u003eRefusal to feed (n, %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e6 (50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e30 (15)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.038\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e7.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e0.988\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e45.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eHPIV, Human parainfluenza virus; LRTI, Lower respiratory tract infections; NICU, neonatal intensive care unit; OR, odds ration; CI, confidence interval.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eHuman parainfluenza virus (HPIV) infections are a common cause of morbidity in neonates, particularly those hospitalized with LRTI. Our study focused on investigating the epidemiological and clinical features of HPIV infections among hospitalized neonates in two tertiary hospitals located in Southeast China. The results of our research provide valuable insights into the infection patterns and risk factors associated with severe disease outcomes in neonates affected by HPIV.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Our findings revealed that HPIV accounts for 2.7% of all LRTI cases in neonates. When compared to the incidence reported in Ningbo province in China, which was 3.06% (30 out of 981 cases) [14], our observed rate was slightly lower. Additionally, it was only half of the incidence observed in a study conducted in Korea, where HPIV was identified in 6.9% (5 out of 72) of neonatal LRTI cases[5]. These differences in incidence rates may be attributed to regional epidemiological variations, as well as disparities in the methodologies used for pathogen detection across different studies. It is important to consider these factors when interpreting and comparing incidence data from various regions. Furthermore, our data demonstrate an age-dependent increase in HPIV incidence. This trend is similar to the epidemiology of RSV [3]. The age-dependent increase in HPIV incidence can help explain the relatively lower infection rates observed in neonatal populations compared to children under five years of age [7].\u003c/p\u003e\n\u003cp\u003eIn this study, we did not incorporate HPIV subtype stratification in our analysis. This limitation was primarily due to the detection methodology employed. Specifically, HPIV was detected using pan-viral detection assays, which are broad-spectrum tests designed to identify a wide range of viral pathogens. While these assays are valuable for detecting the presence of HPIV, they do not provide detailed information on specific subtypes. The decision to use pan-viral detection assays was largely driven by resource constraints, as more specialized subtype-specific assays can be costly and may not be feasible in both research settings. Despite this limitation, we can still draw some inferences about the likely dominant subtype based on existing data. According to national surveillance reports from the Chinese Center for Disease Control and Prevention (China CDC), HPIV-3 is the predominant subtype in China. The aggregate data from 2019 to 2023 indicate that HPIV-3 constitutes over 50% of all laboratory-confirmed HPIV cases in the country[15]. Existing studies also demonstrated that HPIV3 exhibits the highest infection rate among pediatric HPIV cases[7, 16]. Moreover, HPIV3 was reported to cause outbreak in neonatal care unit[11]. Given the heightened vulnerability of neonates, the presence of HPIV-3 in neonatal care units can lead to significant morbidity and challenges in infection control. Considering these lines of evidence, it is reasonable to infer that HPIV-3 is likely the dominant subtype in our neonatal cohort. Future studies with more detailed subtype-specific analyses would be valuable in confirming this inference and providing a more comprehensive understanding of HPIV infections in neonatal populations.\u003c/p\u003e\n\u003cp\u003eWhen comparing HPIV infections to RSV infections in neonates, our study revealed some notable differences in the clinical profiles of affected infants. Specifically, neonates infected with HPIV had a higher percentage of preterm births compared to those infected with RSV. Furthermore, we found that a higher proportion of HPIV-positive neonates had underlying conditions compared to RSV-positive neonates. This finding underscores the potential complexity of HPIV infections in neonates, as preterm birth and underlying conditions can exacerbate the severity of respiratory illnesses. However, interestingly, the presence of these underlying conditions did not influence the neonatal intensive care unit (NICU) admission rates for HPIV-positive neonates. This contrasts with the observations made in RSV-positive neonates, where underlying conditions were associated with increased NICU admissions[3]. This discrepancy may be attributed to differences in monitoring equipment and NICU administration procedures across different hospitals. It is possible that the specific protocols and resources available in the NICU settings of our study hospitals influenced the management and admission decisions for HPIV-positive neonates.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn this study, we identified prematurity and cyanosis as significant risk factors for severe disease requiring NICU admission among neonates with HPIV infections. These findings are clinically relevant, as they can help clinicians in the early identification of neonates who are at higher risk of severe diseases. By recognizing these risk factors, healthcare providers can implement closer monitoring, more targeted interventions, or preemptive treatments to improve outcomes for these vulnerable infants. Our results emphasize the importance of considering both prematurity and cyanosis as key indicators for potential severe HPIV infections, enabling healthcare teams to provide the most appropriate and timely care to neonates in need.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn contrast to the distinct winter-spring seasonal peak characteristic of RSV infections, HPIV demonstrates no pronounced seasonal surge during these periods. We noticed a slight peak prevalence during the summer months, which was also observed in previous report[15, 17] . This pattern may be associated with several factors. Firstly, there is an outbreak of Coronavirus Disease 2019(COVID-19) pandemic in china from 2020. The pandemic may cause changes in circulation patterns of HPIV infections[18, 19]. Secondly, increasing indoor activities of elder children and closer contact with neonates during vacations, facilitating the transmission of respiratory viruses. Decreasing infections of other highly contagious viruses, such as RSV, in summer may also decrease the public awareness of infection prevention. Therefore, health interventions promotion, such as hand hygiene practices, targeting these periods could potentially reduce the incidence of HPIV infections.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe clinical presentation of HPIV infection in neonates is nonspecific and often mimics other respiratory infections such as RSV. This makes it challenging to differentiate between the two infections based on clinical symptoms alone. However, our study found that HPIV-positive neonates were more likely to present with symptoms like stuffy nose and refusal to feed, which could be useful in differentiating HPIV from other infections. Early detection is crucial as it helps prevent or reduce the inappropriate use of antibiotics, which is particularly important given the nonspecific clinical presentation of HPIV infections. Accurate and timely diagnosis allows for more targeted and appropriate treatment strategies, improving patient outcomes and reducing the risk of severe diseases. Moreover, the medical burden of HPIV infections urges the need for vaccines for clinical prevention as there is no effective vaccines available at present[20, 21].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eOur study has some limitations. Firstly, this retrospective study was conducted in only two tertiary hospitals, which limits the generalizability of our findings. There were also selection biases as the study relied on hospital admissions. Secondly, we analyzed the monthly distribution of HPIV infection without considering the COVID-19 prevalence (year 2020 and 2021) during the study period as different epidemic prevention policies adopted in the two cities. Therefore, the epidemic effect on HPIV infection cannot be excluded[22]. Last but not least, different unique protocols and detection tools in the two hospitals may affect the reliability of the findings. Future research should aim to validate our findings in a larger, multicenter cohort and explore the role of other factors such as maternal health, environmental exposures and feeding patterns in the pathogenesis of HPIV infection.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThis study demonstrates that HPIV is a significant etiological agent of LRTIs in hospitalized neonates in Southeast China, accounting for 2.7% of cases. Our findings highlight distinct clinical features of HPIV infection, including a higher prevalence of nasal congestion and feeding difficulties compared to RSV, as well as lower rates of wheezing and moist rales. Importantly, preterm birth and cyanosis were identified as key risk factors for severe disease requiring NICU admission.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eHPIV, human parainfluenza virus; LRTI, lower respiratory tract infection; RSV, respiratory syncytial virus; NICU, neonatal intensive care unit; COVID-19, Coronavirus Disease 2019.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics declaration\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was approved by the Ethics Committee of the Children\u0026rsquo;s Hospital of Soochow University and the Ethics Committee of Xinhua Hospital affiliated with Shanghai Jiao Tong University School of Medicine. All parents or legal guardians were fully informed of the research protocol and provided written consent.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical trial number\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\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\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and analyzed during this study are available from the corresponding author upon reasonable request.\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\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eLianghua Lu: Conception, data collection and analysis; Yunzhu Wang: Data collection, figures preparation; Yahui Li: Data analysis, manuscript draft; Dongying Zhao: Supervision, conception and design, manuscript review and editing.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAll authors read and approved the final manuscript\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eNair NS, Lewis LE, Dhyani VS, Murthy S, Godinho M, Lakiang T, et al. Factors Associated With Neonatal Pneumonia and its Mortality in India: A Systematic Review and Meta-Analysis. Indian Pediatr. 2021;58(11):1059-66.\u003c/li\u003e\n\u003cli\u003eCerar S, Kučan R, Paro-Panjan D, Nosan G. The burden of viral lower respiratory tract infections during the neonatal period: six-year experience at a tertiary referral hospital. Croat Med J. 2022;63(4):343.\u003c/li\u003e\n\u003cli\u003eLu L, Yan Y, Yang B, Xiao Z, Feng X, Wang Y, et al. Epidemiological and clinical profiles of respiratory syncytial virus infection in hospitalized neonates in Suzhou, China. BMC Infect Dis. 2015;15(1):431.\u003c/li\u003e\n\u003cli\u003ePerez A, Lively JY, Curns A, Weinberg GA, Halasa NB, Staat MA, et al. Respiratory Virus Surveillance Among Children with Acute Respiratory Illnesses - New Vaccine Surveillance Network, United States, 2016-2021. MMWR Morb Mortal Wkly Rep. 2022;71(40):1253-9.\u003c/li\u003e\n\u003cli\u003eSong WS, Song BJ, Kim WD. Clinical Characteristics of Acute Respiratory Tract Infections in Full-Term Newborns without Risk Factors. Neonatal Med. 2015;22(1):27-33.\u003c/li\u003e\n\u003cli\u003eGuan X, Gao S, Zhao H, Zhou H, Yang Y, Yu S, et al. Clinical characteristics of hospitalized term and preterm infants with community-acquired viral pneumonia. BMC Pediatr. 2022;22(1):1-10.\u003c/li\u003e\n\u003cli\u003eWang F, Zhao LQ, Zhu RN, Deng J, Sun Y, Ding YX, et al. Parainfluenza Virus Types 1, 2, and 3 in Pediatric Patients with Acute Respiratory Infections in Beijing During 2004 to 2012. Chin Med J (Engl). 2015;128(20):2726-30.\u003c/li\u003e\n\u003cli\u003eFeng L, Lai S, Li F, Ye X, Li S, Ren X, et al. Viral etiologies of hospitalized pneumonia patients aged less than five years in six provinces, 2009-2012. Chin J Epidemiol. 2014;35(6):646-9.\u003c/li\u003e\n\u003cli\u003eWeinberg GA, Hall CB, Iwane MK, Poehling KA, Edwards KM, Griffin MR, et al. Parainfluenza Virus Infection of Young Children: Estimates of the Population-Based Burden of Hospitalization. J Pediatr. 2009;154(5):694-9.\u003c/li\u003e\n\u003cli\u003eWang X, Li Y, Deloria-Knoll M, Madhi SA, Cohen C, Arguelles VL, et al. Global burden of acute lower respiratory infection associated with human parainfluenza virus in children younger than 5 years for 2018: a systematic review and meta-analysis. Lancet Glob Health. 2021;9(8):E1077-87.\u003c/li\u003e\n\u003cli\u003eMaeda H, Haneda K, Honda Y. Parainfluenza virus type 3 outbreak in a neonatal intensive care unit. Pediatr Int. 2017;59(11):1219-22.\u003c/li\u003e\n\u003cli\u003eMoisiuk S, Robson D, Klass L, Kliewer G, Wasyliuk W, Davi M, et al. Outbreak of parainfluenza virus type 3 in an intermediate care neonatal nursery. Pediatr Infect Dis J. 1998;17(1):49-53.\u003c/li\u003e\n\u003cli\u003eChen ZR, Ji W, Wang YQ, Yan YD, Shao XJ, Zhang XL, et al. Etiology of acute bronchiolitis and the relationship with meteorological conditions in hospitalized infants in China. J Formos Med Assoc. 2014;113(7):463-9.\u003c/li\u003e\n\u003cli\u003eZhou CB, Lu WW, Zhang YZ, et al. Analysis of detection of 13 respiratory non-bacterial pathogens in children in Ningbo area from 2019 to 2021. Zhonghua Yu Fang Yi Xue Za Zhi. 2022;56(12):1751-8. \u003c/li\u003e\n\u003cli\u003eGao Y, Ma Y, Feng D, Zhang F, Wang B, Liu X, et al. Epidemiological Characteristics of Human Parainfluenza Viruses Infections - China, 2019-2023. China CDC Wkly. 2024;6(12):235-41.\u003c/li\u003e\n\u003cli\u003eAbu-Helalah M, Abu Lubad M, Al-Hanaktah M, Al Tibi A, Alhousani M, Drysdale SB. The Epidemiology and Clinical Burdens of Human Parainfluenza Virus Infections Amongst Hospitalized Children Under 5 Years of Age in Jordan: A National Multi-Center Cross-Sectional Study. Viruses. 2025;17(2):170.\u003c/li\u003e\n\u003cli\u003eChen Z, Zhu Y, Wang Y, Zhou W, Yan Y, Zhu C, et al. Association of meteorological factors with childhood viral acute respiratory infections in subtropical China: an analysis over 11 years. Arch Virol. 2014;159(4):631-9\u003c/li\u003e\n\u003cli\u003eLaird TS, Hamilton M, William N, Karanwal S, Marsh K, Evans J. Trends in human parainfluenza virus in Scotland before and after the peak of the COVID-19 pandemic, January 2017 to October 2023. Euro Surveill. 2025;30(2):2400147.\u003c/li\u003e\n\u003cli\u003eKim HM, Rhee JE, Lee NJ, Woo SH, Park AK, Lee J, et al. Recent increase in the detection of human parainfluenza virus during the coronavirus disease-2019 pandemic in the Republic of Korea. Virol J. 2022;19(1) \u003c/li\u003e\n\u003cli\u003eOutlaw VK, Cheloha RW, Jurgens EM, Bovier FT, Zhu Y, Kreitler DF, et al. Engineering protease-resistant peptides to inhibit human parainfluenza viral respiratory infection. J Am Chem Soc. 2021;143(15):5958-66.\u003c/li\u003e\n\u003cli\u003eMackow N, Amaro-Carambot E, Liang B, Surman S, Lingemann M, Yang L, et al. Attenuated Human Parainfluenza Virus Type 1 (HPIV1) Expressing the Fusion Glycoprotein of Human Respiratory Syncytial Virus (RSV) as a Bivalent HPIV1/RSV Vaccine. J Virol. 2015;89 (20):10319-32.\u003c/li\u003e\n\u003cli\u003eWu R, Zhang J, Mo L. Analysis of respiratory virus detection in hospitalized children with acute respiratory infection during the COVID-19 pandemic. Virol J. 2023; 20:25\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"neonates, lower respiratory tract infections, human parainfluenza virus","lastPublishedDoi":"10.21203/rs.3.rs-6456374/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6456374/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground: \u003c/strong\u003eHuman parainfluenza virus (HPIV) is a clinically significant pathogen responsible for acute respiratory tract infections (ARTIs) in infants. This study aimed to elucidate the epidemiological characteristics, clinical manifestations, and severity risk factors in neonates with HPIV.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods: \u003c/strong\u003eThis retrospective study included infants admitted to the neonatology departments of two tertiary hospitals in southeast China between January 2016 and December 2023, diagnosed with lower respiratory tract infections (LRTIs) or febrile illnesses. HPIV was detected via standardized molecular assays, including either Double Amplification Technique or Direct Immunofluorescent Antibody Assay.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults: \u003c/strong\u003eAmong 7,557 neonates who underwent throat swabs, 212 neonates were tested positive for HPIV, accounting for 2.7% of all LRTI cases in the study cohort. The detection rate of HPIVs increased with age. Neonates with HPIV infection demonstrated significantly higher prevalence rates of nasal congestion (79.7% vs 59.6%, \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001) and poor feeding (17% vs 4.7%,\u003cem\u003e P\u003c/em\u003e \u0026lt; 0.001) compared to those with respiratory syncytial virus (RSV) infection. Conversely, moist rales (57.1% Vs 80.1%, \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001) and wheezing (6.6% Vs 17.8%, \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001) were observed less frequently in the HPIV group. Moreover, preterm birth, poor feeding and cyanosis were identified as significant risk factors for neonatal intensive care unit (NICU) hospitalization in HPIV-infected neonates.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions\u003c/strong\u003e: HPIV represents an important etiological agent of LRTIs among hospitalized neonates in Southeast China, exhibiting distinct clinical characteristics that differentiate it from RSV infection. Notably, preterm infants are at highest risk for severe disease manifestations,requiring intensive monitoring.\u003c/p\u003e","manuscriptTitle":"Epidemiological and clinical characteristics of parainfluenza virus infection in hospitalized neonates in Southeast China","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-05-22 10:32:16","doi":"10.21203/rs.3.rs-6456374/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"5fe9e2d1-03b7-400c-810b-0dd6c7857a15","owner":[],"postedDate":"May 22nd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-10-08T07:39:00+00:00","versionOfRecord":[],"versionCreatedAt":"2025-05-22 10:32:16","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6456374","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6456374","identity":"rs-6456374","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}