Healthcare-Associated Infections in Chinese Neonates: A Multicenter Retrospective Period Prevalence Survey in Jiangsu Province (2023)

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Understanding the epidemiological characteristics of neonatal HAI is of major guiding significance for the development of targeted public health policies and clinical prevention strategies. This study aimed to investigate the epidemiology of neonatal HAI in Jiangsu Province, China, in 2023. Methods A retrospective period prevalence survey was conducted in Jiangsu Province, China, from September to October 2024. Data on neonatal HAI occurring between January and December 2023 were collected using a structured questionnaire. Thirty hospitals from 13 cities ultimately participated and completed the survey. Results Among 36,957 neonates (327,098 patient-days), 370 HAI episodes were identified, yielding a prevalence of 1.0% (95% CI: 0.9%–1.1%). Neonates with a birth weight < 1500 g faced a dramatically higher risk (RR = 17.0, 95% CI: 14.0–20.8; p < 0.001). The most common infection sites were bloodstream (45.7%), lower respiratory tract (39.2%), and gastrointestinal tract (5.5%). Predominant pathogens included coagulase-negative staphylococci (18.2%) and Klebsiella pneumoniae (17.2%). Device-associated infection rates were 0.7‰ (95% CI: 0.4–1.0) for central line-associated bloodstream infection and 1.2‰ (95% CI: 0.7–1.6) for ventilator-associated pneumonia. Conclusion This first province-wide study reveals a relatively low overall prevalence of HAI among neonates in Jiangsu. Prevention priorities should focus on high-risk neonatal birthweight < 1500 g and bloodstream infections, supported by optimized staffing levels for both nursing and infection preventionist personnel, as well as strengthened microbiological surveillance. Neonatal Healthcare-associated infections Multi-center study Device-associated infections Figures Figure 1 Figure 2 Background Advances in medical technology have significantly improved survival rates for preterm infants and neonates with congenital anomalies. Yet these vulnerable patients exhibit functionally immature immune systems and organ dysfunction relative to healthy term infants, with clinical severity inversely correlated with gestational age. Prolonged hospitalization exposes them to multiple infection risks: intensive antimicrobial use, invasive procedures such as surgery, intravascular catheterization and mechanical ventilation, and environmental contact with multidrug-resistant pathogens. Such interventions disrupt microbial homeostasis and compromise mucocutaneous barrier integrity, creating synergistic conditions that predispose to healthcare-associated infections (HAI)—which are associated with extended hospitalization, elevated healthcare costs, and increased mortality[ 1 ]. Global epidemiological studies report substantial neonatal HAI burdens, with incidence rates ranging from 3.35% to 21.40% across clinical settings[ 2 – 6 ]. Recurrent outbreaks continue to challenge healthcare systems worldwide[ 7 , 8 ], underscoring the need for updated regional surveillance. Neonatal HAI epidemiology exhibits marked geographical and temporal variation. For instance, a 1999 U.S. Neonatal Intensive Care Unit (NICU) study across 29 units reported an 11.4% infection rate, predominantly involving bloodstream, respiratory, and ear/nose/throat infections, with coagulase-negative staphylococci (CoNS), Enterococcus spp ., and Escherichia coli as primary pathogens[ 3 ]. Similarly, a 2011 European multicenter study documented 10.7% HAI incidence featuring primarily bloodstream infections where CoNS accounted for 58.1% of isolates[ 4 ]. Conversely, an Egyptian single-center study observed a substantially higher rate (21.40%) dominated by pulmonary infections[ 5 ]. China’s only multicenter investigation conducted in 2013 across 17 NICUs reported a 3.35% HAI rate with bloodstream infections predominating (68.4%)[ 2 ]. However, this pivotal study is now over a decade old. Given the substantial investments in healthcare infrastructure and infection control programs over the past decade, particularly in economically developed regions like Jiangsu Province—a region of over 84 million people with an advanced healthcare system—there is a pressing need to reassess the contemporary epidemiology of neonatal HAI. Prevalence surveys typically employ point prevalence or period prevalence. While point prevalence requires fewer resources and is internationally prevalent, it may underestimate short-duration HAI (such as lower respiratory tract and urinary tract infections) and generally yields lower rates than period prevalence[ 9 ]. Our study therefore adopted the period prevalence approach. Under the guidance of the Jiangsu Provincial Health Commission and the Hospital Infection Control Branch of the Jiangsu Maternal and Child Health Association (JSMCHA-ICB), we conducted a multicenter, province-wide retrospective survey to assess the prevalence of neonatal HAI in Jiangsu Province for the year 2023. This study represents the first comprehensive effort of its kind in the region in recent years, aiming to address current knowledge gaps by: (1) determining the period prevalence and epidemiological characteristics of neonatal HAIs, and (2) identifying high-risk populations and predominant pathogens to guide the development of targeted, precision prevention strategies. Methods Study Design and Setting This multicenter, retrospective period prevalence survey was conducted to determine the epidemiological characteristics of neonatal HAI in Jiangsu Province from January 1 to December 31, 2023. Invitations were extended to all of secondary-level hospitals and above that operated neonatal wards within the province. Ultimately, 30 hospitals agreed to participate and completed the survey. Study population The study population included all neonates (birth to 28 days of age) hospitalized for ≥ 48 hours in the neonatal wards or NICUs of the participating hospitals during the 2023 calendar year. Neonates admitted solely to delivery rooms or outpatient settings, or with hospitalization duration < 48 hours, were excluded. Data collection was performed between September and October 2024. Survey Instrument Development and Validation The structured electronic questionnaire was developed by JSMCHA-ICB in accordance with the U.S. Centers for Disease Control and Prevention/National Healthcare Safety Network (CDC/NHSN) HAI criteria and China’s National Health Commission Guidelines for the Construction of Neonatal Wards [ 10 , 11 ]. A multidisciplinary expert panel—including HAI prevention specialists, neonatologists, clinical microbiologists, and epidemiologists—designed and reviewed the instrument. The final questionnaire consisted of four modules comprising 59 key data items.The full English version of the questionnaire is available as Supplementary File 1. Hospital Demographics Name, location, type (general/maternity and child health specialty), accreditation level (Tertiary/Secondary); total bed capacity; number and qualifications of infection preventionists (IP). Neonatal Ward Parameters Ward type (general/NICU); approved and operational bed capacities; compliance with layout standards (area per bed ≥ 6m², bed spacing ≥ 1m); staffing levels (physicians, nurses, support staff as of December 31, 2023); Infection prevention infrastructure including isolation room availability, active HAI surveillance, high-efficiency particulate air filtration, and environmental monitoring frequency. HAI Surveillance Data Total neonates admitted and patient-days in 2023; distributions by birthweight (≤ 1000g, 1001–1500g, 1501–2500g, > 2500g); total HAI cases. Device Utilization Data Total device-days stratified by birthweight. For each HAI case, additional details were recorded: infection date, site, microbiological testing conducted, identified pathogens, birthweight, and device association. An accompanying Data Collection Guide—containing standardized definitions—was developed to ensure consistency. Prior to full deployment, a pilot study was conducted in three representative hospitals: a provincial tertiary specialty hospital, a prefectural tertiary general hospital, and a secondary specialty hospital. Feedback from the pilot helped refine the questionnaire and guide, improving clarity, feasibility, and completeness. Data Collection Procedures Data collection was performed electronically using "Wenjuanxing", a widely adopted online survey platform in China compliant with the Cybersecurity Law of the People's Republic of China and healthcare data security regulations. The platform ensures data security through encrypted transmission, access controls, and backups. Each participating hospital designated a certified IP as the primary data collector. IP retrospectively reviewed medical records, infection surveillance logs, microbiological laboratory reports, and nursing documentation for all neonates hospitalized in the neonatal ward throughout 2023. They identified all eligible hospitalized neonates. Each neonate was screened, and all HAI meeting the predefined case definitions occurring during their 2023 hospitalization were confirmed. Following departmental head verification, data were entered into the online platform. Prior to data collection, all designated IP received standardized training from the study core team (JSMCHA-ICB experts). Three experienced infection control specialists served as reviewers, performing logic consistency and plausibility checks on all submitted questionnaires. Flagged anomalous data were clarified and corrected exclusively via the platform's secure messaging system. Continuous technical support was provided throughout the data collection period. Definitions HAI, including catheter-related bloodstream infections (CLABSI) and ventilator-associated pneumonia (VAP), were defined according to the CDC/NHSN criteria[ 10 ]. Key diagnostic elements included: 1) absence of infection or incubation at admission; 2) onset ≥ 48 hours post-admission; and 3) association with medical care or healthcare exposure. Infections acquired during birth canal passage were classified as HAI. Statistical Analysis Statistical analyses were performed using SPSS Statistics (Version 26.0). Categorical variables are presented as frequencies and percentages. Continuous variables are presented as median with interquartile range (IQR). Rates were compared using the Chi-square test ( χ² ) or Fisher's exact test (when expected cell frequencies were < 5), with the significance level set at α = 0.05 (two-tailed). Results Characteristics of Participating Hospitals and Study Population A total of 30 hospitals from all 13 prefecture-level cities in Jiangsu Province participated in the study, ensuring broad geographic representation (Fig. 1). Among them, 20 (66.7%) were women and children's specialty hospitals and 26 (86.7%) were tertiary hospitals (Table 1 ). Specialty hospitals cared for a substantially larger proportion of the study population (79.4% of neonates, 81.6% of patient-days) than general hospitals. All participating hospitals employed real-time nosocomial infection surveillance systems and conducted active surveillance; the median number of IP was 0.6 (IQR 0.5–0.8) per 100 beds. Furthermore, 43.3% (13/30) of institutions did not meet the recommended nurse-to-neonate ratio. Table 1 Characteristics of Participating Hospitals and the Study Population Characteristic Overall (N = 30) Women and Children's Hospitals (N = 20) General Hospitals (N = 10) Hospital Level, n (%) Tertiary 26 (86.7) 16 (80.0) 10 (100.0) Secondary 4 (13.3) 4 (20.0) 0 (0.0) Neonatal Ward Type, n (%) NICU 28 (93.3) 19 (95.0) 9 (90.0) Neonatal Ward 30 (100) 20 (100) 10 (100) IP Staffing Median IP per 100 beds (IQR)* 0.6 (0.5–0.8) 0.8 (0.6–0.9) 0.5 (0.4–0.6) Study Population (2023) Total neonates admitted, n (%) 36957 29329 (79.4) 7628 (21.6) Total patient-days, n (%) 327098 266922 (81.6) 60176 (19.4) *IP, infection preventionist. Insert Fig. 1 here HAI Prevalence and Distribution A total of 370 episodes of HAI were observed among 36,957 neonates, corresponding to a prevalence of 1.0% (95% CI: 0.9%–1.1%). Considerable variation in HAI rates was observed across different birthweight categories (Table 2 ). Neonates with a birthweight < 1500 g exhibited a substantially higher incidence of HAI, accounting for nearly half of all episodes (46.7%, 173/370). Their relative risk of HAI was 17.0 times greater (95% CI: 14.0–20.8; P < 0.001) than that of neonates weighing ≥ 1500 g. The HAI prevalence was significantly higher in specialty hospitals (1.07%) than in general hospitals (0.75%) (χ² = 6.253, p = 0.012). Similarly, tertiary hospitals had a significantly higher infection rate (1.03%) compared to secondary hospitals (0.16%) (χ² = 9.236, p = 0.002). Geographically, HAI rates varied among the 13 prefecture-level cities, with three cities reporting prevalence rates above the upper confidence limit of the overall provincial rate (Fig. 2). Table 2 Distribution of HAI by birthweight Birthweight (g) Patients n (%) Patient-Days n (%) HAI Cases n (%) Incidence Rate %(95% CI) Median (IQR)* ≤ 1000 535 (1.4) 18748 (5.7) 56 (15.1) 10.5 (7.9–13.1) 4.7(0.0-12.3) 1001–1500 1277 (3.5) 40760 (12.5) 117 (31.6) 9.2 (7.6–10.7) 5.9 (0.0-10.3) 1501–2500 7453 (20.2) 90830 (27.8) 91 (24.6) 1.2 (1.0-1.5) 0.6 (0.0-1.5) >2500 27692 (74.9) 176760 (54.0) 106 (28.7) 0.4 (0.3–0.5) 0.2 (0.1–0.4) Total 36957 327098 370 1.0 (0.9–1.1) 0.5 (0.3–1.8) *The median (IQR) calculation for each subgroup was restricted to the hospitals that reported cases (≤ 1000 g: n = 22; 1001–1500 g: n = 27; >1500 g: n = 30). Insert Fig. 2 here Distribution of Infection Sites and Pathogens Among 370 neonates with HAI, cultures were performed in 263 (71.1%) cases, and 192 pathogens were isolated (Table 3 ), of which multiple organisms were isolated from 7 samples. The pathogen distribution comprised 157 (81.8%; 96 Gram-negative and 61 Gram-positive) bacterial strains, 23 (12.0%) fungal isolates, and 12 (6.3%) viral agents. CoNS (18.2%) and Klebsiella pneumoniae (17.2%) represented the predominant microbial groups. CoNS was particularly prominent in bloodstream infections, accounting for 29.5% of pathogens isolated from this site. Klebsiella pneumoniae was a major pathogen in both bloodstream (17.1%) and lower respiratory tract (21.2%) infections. Rotavirus dominated gastrointestinal infections. Six multidrug-resistant organisms were identified, including three strains of carbapenem-resistant Klebsiella pneumoniae , two methicillin-resistant Staphylococcus aureus , and one carbapenem-resistant Enterobacter cloacae complex . Table 3 Pathogen distribution by infection site among neonates with HAI (n,%) Pathogen Total Pathogens n (%) Bloodstream n (%) Lower respiratory tract n (%) Gastrointestinal tract n (%) Other sites n (%)* Coagulase-negative staphylococci 35 (18.2) 31 (29.5) 2 (3.8) 0 2 (11.8) Klebsiella pneumoniae 33 (17.2) 18 (17.1) 11 (21.2) 1 (5.6) 3 (17.6) Candida albicans 12 (6.3) 7 (6.7) 2 (3.8) 1 (5.6) 2 (11.8) Escherichia coli 15 (7.8) 5 (4.8) 7 (13.5) 1 (5.6) 2 (11.8) Enterobacter aerogenes 12 (6.3) 6 (5.7) 6 (11.5) 0 0 Enterobacter cloacae complex 11 (5.7) 7 (6.7) 2 (3.8) 1 (5.6) 1 (5.9) Staphylococcus aureus 10 (5.2) 6 (5.7) 3 (5.8) 0 1 (5.9) Rotavirus 9 (4.7) 0 0 9 (50) 0 Acinetobacter baumannii 6 (3.1) 2 (1.9) 4 (7.7) 0 0 Pseudomonas aeruginosa 6 (3.1) 2 (1.9) 4 (7.7) 0 0 Candida parapsilosis 6 (3.1) 6 (5.7) 0 0 0 Enterococcus faecalis 5 (2.6) 4 (3.8) 0 1 (5.6) 0 Enterococcus faecium 5 (2.6) 3 (2.9) 1 (1.9) 0 1 (5.9) C.glabrata 3 (1.6) 2 (1.9) 1 (1.9) 0 0 Murivirus 3 (1.6) 0 0 0 3 (17.6) Streptococcus salivarius 3 (1.6) 0 1 (1.9) 1 (5.6) 1 (5.9) Other pathogens 18 (9.4) 6 (5.7) 8 (15.4) 3 (16.7) 1 (5.9) Total 192 105 52 18 17 Negative culture 77 20 26 6 25 Not cultured 107 2 31 35 39 Multiple organisms 7 4 2 0 1 *Other sites including Upper respiratory ,n = 18, Central nervous system (n = 3), Urinary tract (n = 2), Oral cavity(n = 2), Ear/nose/throat (n = 2), Soft tissue (n = 1), Surgical site infection (n = 2), Other (n = 4). Device-associated infections The average duration of use was 16 days per neonate for central lines and 9 days for ventilators. A total of 26 CLABSI (0.7 per 1000 device-days, 95% CI 0.4–1.0) and 24 VAP (1.2 per 1000 device-days, 95% CI 0.7–1.6) were recorded (Table 4 ), the rate of VAP exceeded that of CLABSI in this cohort. CLABSI incidence exhibited borderline significance across birthweight categories (χ² = 7.08, p = 0.059), whereas no significant birthweight-dependent variations were observed for VAP rates (χ² = 3.45, p = 0.308). Table 4 Device-Associated Outcomes by birthweight birthweight (g) Device-days n (%) Utilization ratio (%) Infections n (%) Incidence rates ‰ (95% CI) Median (IQR)* Central line 2500 5297 (14.5) 3.0 3 (11.5) 0.6 (0.1–1.2) 0 (0.0–0.0) Total 36453 11.2 26 0.7 (0.4-1.0) 0 (0.0−0.9) Mechanical ventilation 2500 6625 (32.3) 3.8 5 (20.8) 0.8 (0.1–1.4) 0 (0.0–0.0) Total 20500 6.3 24 1.2 (0.7–1.6) 0 (0.0−0.5) *Median (IQR) includes only hospitals with device use (number of hospitals per subgroup: Central line— 2500g: 19; Mechanical ventilation— 2500g: 28). Discussion This first province-wide, multicenter study of 36,957 neonates across 30 hospitals in Jiangsu Province uncovered an unexpectedly low overall prevalence of HAIs—just 1.0% in 2023. This figure stands in stark contrast to rates reported elsewhere in China (3.35%) as well as those from developed countries and regions, including U.S. NICUs (11.4%) and European neonatal care settings (5.1%)[ 2 – 4 , 6 ]. However, these comparisons require cautious interpretation. First, differences in study methods, populations, and timing may render direct cross-comparisons invalid. Our study encompassed all hospitalized neonates, not only NICU patients, and employed a period prevalence survey. Second, the lower prevalence may be attributed to Jiangsu's substantial investment in healthcare resources. As an economically developed region, all 30 participating hospitals were equipped with real-time nosocomial infection surveillance systems and implemented active surveillance. This system facilitates timely identification of infection risks and enhances the promptness of interventions[ 12 ]. Yet a deeper investigation revealed a paradox: despite technological advancement, human resource allocations lag significantly. The ratio of IP staff per 100 beds was only 0.6, below that of Guiyang (1.0) and the U.S. (1.2)[ 13 , 14 ]. Moreover, the quantity and experience of IP staff have been shown to be negatively correlated with HAI rates [ 15 ].Compounding this, 44% of hospitals reported understaffed nursing teams,which may compromise the effective implementation of infection control measures and warrants targeted improvement[ 16 ]. Consistent with other multicenter studies[ 2 – 4 ], we observed considerable inter-hospital variation in HAI rates, which was largely attributable to differences in case-mix and patient acuity. Tertiary and specialized hospitals cared for a higher proportion of high-risk neonates (birthweight < 1500 g) than secondary and general hospitals (Fig. 2). This led to a greater HAI burden in these centers, rather than indicating inferior infection control practices. As our results demonstrate, nearly half of all HAI occurred among infants with a birthweight < 1500 g, even though they constituted only 5% of the cohort. Birthweight and gestational age are among the most important risk factors for HAI development[ 17 ], underscoring the critical need to refocus prevention efforts on this vulnerable population. Although birthweight is widely used for stratifying neonatal HAI risk, we found considerable variation in infection rates even within the same birthweight category. This stark disparity underscores that traditional birth-weight stratification, while useful, masks significant internal risk heterogeneity—a point previously raised[ 17 ]. There is a clear need to incorporate more sensitive illness severity scores, such as Score for Neonatal Acute Physiology and its perinatal extension, which have been used to assess neonatal mortality risk[ 17 , 18 ]. However, their validity in predicting HAI risk requires further validation. The most common infection sites in this study were bloodstream (44.1%), lower respiratory tract (17.4%), and gastrointestinal tract (5.5%), collectively accounting for 67% of infections—a finding consistent with domestic reports[ 2 ]. While bloodstream and lower respiratory infections are also predominant in U.S. and European settings[ 3 , 4 , 6 ], ear/nose/throat and urinary tract infections are reported more frequently than gastrointestinal infections in those regions[ 3 , 4 , 6 ]. The leading pathogens identified here were CoNS (18.2%), Klebsiella pneumoniae (17.2%), and Candida albicans (6.3%), which differs from profiles in the U.S. (CoNS, enterococci, E. coli ) and Europe (CoNS, E. coli , S. aureus )[ 3 , 4 ]. Notably, CoNS accounted for 29.5% of bloodstream infections, with S. epidermidis being the most common species. The predominance of CoNS in bloodstream infections is a globally recognized phenomenon[ 3 – 6 ], necessitating tailored preventive strategies. The distinct distribution of infection sites and pathogens highlights the regional specificity of neonatal HAIs in Jiangsu and emphasizes the importance of context-specific control measures. It should be noted, however, that only 71.1% of cases underwent microbiological culture, which may have introduced bias into the pathogen spectrum; therefore, improving microbial submission rates remains essential. The incidence of CLABSI was 0.7‰, consistent with a previous multicenter study in China (0.66‰) but lower than rates reported in the U.S. (1.13‰) and the Netherlands (2.91–16.14‰) [ 19 – 21 ]. The incidence of VAP was 1.2‰, which is substantially lower than the rate reported in a Chinese multicenter study (7.23‰) but higher than that in the U.S. (0.81‰)[ 21 ]. The surveillance definition for VAP in the CDC/NHSN criteria contains subjective elements[ 22 ], which may be an important factor contributing to these discrepancies. Although CLABSI is considered the most important device-associated infection in neonates[ 22 ], the prevalence of VAP exceeded that of CLABSI in this study—an unexpected finding suggesting that prevention and control of VAP should be prioritized. Currently, there are no established optimal bundled practices for the prevention of neonatal VAP[ 23 ]. Our study found that in Jiangsu Province, measures such as elevation of the head of the bed, use of sterile water for humidification, weekly replacement of ventilator circuits and humidification devices, and daily assessment for extubation readiness are widely implemented. But only a very small number of hospitals use sterile gauze for oral care in neonates. It is important to note that these measures are primarily derived from adult VAP prevention guidelines, and their scientific validity remains questionable. In 2022, the Society for Healthcare Epidemiology of America released a guideline which indicates that only four neonatal VAP prevention strategies are supported by high-quality evidence: (1) Use non-invasive positive pressure ventilation in selected populations, (2) Use caffeine therapy to facilitate extubation; (3) Minimize the duration of mechanical ventilation; and (4) Avoid reintubation by using nasal continuous positive airway pressure, non-invasive positive pressure ventilation, or high flow nasal cannula in the post-extubation period[ 24 ]. A limitation of this study is its reliance on questionnaire-based data collection. While this approach enables rapid multicenter collaboration, it does not capture patient-level data, thus preventing adjustment for inter-hospital differences in case mix and illness severity. Conclusion This study represents the first province-wide multicenter investigation of neonatal HAI in Jiangsu Province. reveals a comparatively low overall HAI prevalence, likely reflecting substantial regional investments in healthcare quality and infection control, yet highlights significant vulnerabilities among extremely low birthweight infants and identifies device-associated infections, particularly VAP, as a key prevention target. Future efforts should prioritize prevention for infants with birthweight < 1500g and bloodstream infections, while optimizing staffing levels for both nursing and IP personnel, along with strengthening microbiological testing, is imperative. Abbreviations Abbreviation Full Term CDC/NHSN Centers for Disease Control and Prevention/National Healthcare Safety Network CI Confidence Interval CLABSI Central Line-Associated Bloodstream Infection CoNS Coagulase-negative staphylococci HAI Healthcare-associated infection IP Infection Preventionist IQR Interquartile Range JSMCHA-ICB Jiangsu Maternal and Child Health Association - Infection Control Branch NICU Neonatal Intensive Care Unit RR Relative Risk VAP Ventilator-Associated Pneumonia Declarations Ethics approval and consent to participate This retrospective study was conducted as part of a provincial public health surveillance initiative led by the Jiangsu Provincial Health Commission.The study was reviewed by the Medical Ethics Committee of The First Affiliated Hospital of Nanjing Medical University. In accordance with Article 32 of China's ‘ Regulations on Ethical Review of Biomedical Research Involving Humans ’ (2016) , which stipulates that ethical review is not required for research utilizing existing documented data, the Committee granted an exemption from ethical approval and waived the requirement for individual informed consent (Approval/Exemption Number: 2025-SR-861). All data were analyzed in an anonymized manner Consent for publication Not applicable. This manuscript does not contain any individual person's data in any form. Availability of data and materials The datasets used and/or analyzed during the current study are not publicly available due to provincial health data regulations but may be available from the corresponding author on reasonable request and with permission from JSMCHA-ICB. Competing interests The authors declare that they have no competing interests. Funding This work was supported by the Jiangsu Hospital Association [Grant numbers JSYGY-3-2020-157 and JSYGY-3-2023-363]; the Nantong Health Commission [Grant number QNZ2024057]; and the Nantong Science and Technology Bureau [Grant number MSZ2024159]. The funders had no role in the design of the study, data collection, analysis, interpretation, or in writing the manuscript. Authors' contributions WWL and LF contributed equally to this work. Conceptualization: XZ, WWL. Data curation: WWL, LF, FYW. Formal analysis: WWL, LF. Funding acquisition: XZ. Investigation: All authors. Methodology: WWL, LF, XZ. Project administration: XZ. Resources: XZ. Supervision: XZ. Validation: WWL, LF, FYW. Writing – original draft: WWL, LF. Writing – review & editing: All authors. All authors read and approved the final manuscript. Acknowledgements The authors would like to thank JSMCHA-ICB for its guidance and coordination. 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Infection preventionist staffing levels and rates of 10 types of healthcare-associated infections: A 9-year ambidirectional observation. Infect Control Hosp Epidemiol. 2022;43(11):1641–6 . https://doi.org/10.1017/ice.2021.507. Haley RW, Bregman DA. The role of understaffing and overcrowding in recurrent outbreaks of staphylococcal infection in a neonatal special-care unit. J Infect Dis. 1982;145(6):875–85 . https://doi.org/10.1093/infdis/145.6.875. Gagliardi L, Cavazza A, Brunelli A, Battaglioli M, Merazzi D, Tandoi F, et al. Assessing mortality risk in very low birthweight infants: a comparison of CRIB, CRIB-II, and SNAPPE-II. Arch Dis Child Fetal Neonatal Ed. 2004;89(5):F419–22 . https://doi.org/10.1136/adc.2003.031286. Gray JE, Richardson DK, McCormick MC, Goldmann DA. Coagulase-negative staphylococcal bacteremia among very low birth weight infants: relation to admission illness severity, resource use, and outcome. Pediatrics. 1995;95(2):225–30 . Jansen SJ, Broer SDL, Hemels MAC, Visser DH, Antonius TAJ, Heijting IE, et al. Central-line-associated bloodstream infection burden among Dutch neonatal intensive care units. J Hosp Infect. 2024;144:20–7 . https://doi.org/10.1016/j.jhin.2023.11.020. Ren J, Yin H, Wu A, Li Y, Jia H, Li R, Zhang X, Du B, Li J. Multicenter study on device-associated infection in neonatal intensive care unit. Chin J Infect Control. 2015;14(8):530–4 . Dudeck MA, Edwards JR, Allen-Bridson K, Gross C, Malpiedi PJ, Peterson KD, et al . National Healthcare Safety Network report, data summary for 2013, Device-associated Module. Am J Infect Control. 2015;43(3):206–21 . https://doi.org/10.1016/j.ajic.2014.11.014. Bierwirth NC, Cantey JB. The Newborn Nursery and the Neonatal Intensive Care Unit. In: Bennett JV, Jarvis WR, Brachman PS, editors. Bennett & Brachman's Hospital Infections. 6th ed. Philadelphia: Wolters Kluwer; 2021. p. 398. Cocoros NM, Priebe GP, Logan LK, Coffin S, Larsen G, Toltzis P, et al. A Pediatric Approach to Ventilator-Associated Events Surveillance. Infect Control Hosp Epidemiol. 2017;38(3):327–33 . https://doi.org/10.1017/ice.2016.277. Klompas M, Branson R, Cawcutt K, Crist M, Eichenwald EC, Greene LR, et al. Strategies to prevent ventilator-associated pneumonia, ventilator-associated events, and nonventilator hospital-acquired pneumonia in acute-care hospitals: 2022 Update. Infect Control Hosp Epidemiol. 2022;43(6):687–713 . https://doi.org/10.1017/ice.2022.88. Additional Declarations No competing interests reported. Supplementary Files Questionnaire.pdf Supplementary File 1: Data Collection Questionnaire. (English version) Cite Share Download PDF Status: Published Journal Publication published 28 Mar, 2026 Read the published version in BMC Infectious Diseases → Version 1 posted Editorial decision: Revision requested 21 Jan, 2026 Reviews received at journal 21 Jan, 2026 Reviewers agreed at journal 12 Jan, 2026 Reviewers agreed at journal 24 Nov, 2025 Reviewers agreed at journal 14 Oct, 2025 Reviews received at journal 07 Oct, 2025 Reviewers agreed at journal 25 Sep, 2025 Reviewers invited by journal 25 Sep, 2025 Editor assigned by journal 25 Sep, 2025 Editor invited by journal 24 Sep, 2025 Submission checks completed at journal 23 Sep, 2025 First submitted to journal 23 Sep, 2025 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. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7581104","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":526057042,"identity":"0a5c7f75-c93e-436f-b573-cac441edc6fb","order_by":0,"name":"Wei-wei Liu¹","email":"","orcid":"","institution":"Affiliated Maternity and Child Health Care Hospital of Nantong University","correspondingAuthor":false,"prefix":"","firstName":"Wei-wei","middleName":"","lastName":"Liu¹","suffix":""},{"id":526057044,"identity":"3b6f4f20-19c5-4e0d-9234-c15b3b93ddab","order_by":1,"name":"Lu Fu¹","email":"","orcid":"","institution":"Affiliated Maternity and Child Health Care Hospital of Nantong University","correspondingAuthor":false,"prefix":"","firstName":"Lu","middleName":"","lastName":"Fu¹","suffix":""},{"id":526057046,"identity":"9a3882b4-88e3-44e5-95e5-5c76006f51a5","order_by":2,"name":"Fei-ying Wang¹","email":"","orcid":"","institution":"Affiliated Maternity and Child Health Care Hospital of Nantong University","correspondingAuthor":false,"prefix":"","firstName":"Fei-ying","middleName":"","lastName":"Wang¹","suffix":""},{"id":526057049,"identity":"5ddad3f9-ebbe-4172-b20a-e218adc000c7","order_by":3,"name":"Xiang 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16:38:02","extension":"html","order_by":11,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":114424,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7581104/v1/01f44fea7f60a5e01dbdb546.html"},{"id":93062893,"identity":"4a956115-1782-4099-b862-f7ada41cb1f6","added_by":"auto","created_at":"2025-10-08 16:38:05","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1624002,"visible":true,"origin":"","legend":"\u003cp\u003eGeographic distribution of the 30 participating hospitals (This map is based on the standard map with the review number GS (2024) 0650 downloaded from the Standard Map Service website of the National Bureau of Surveying and Mapping Geographic Information. The base map has not been modified).\u003c/p\u003e","description":"","filename":"Fig.1.png","url":"https://assets-eu.researchsquare.com/files/rs-7581104/v1/92691364ae37d2f276ad5254.png"},{"id":93063231,"identity":"d7e2fd6a-98f8-41b3-a6ab-9cd64812d5e6","added_by":"auto","created_at":"2025-10-08 16:38:10","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1094939,"visible":true,"origin":"","legend":"\u003cp\u003eNeonatal HAI rates and distribution of birthweight groups. (a) HAI rates by city and the proportional distribution of neonates in different birth weight categories. (b) HAI rates by hospital type and the proportional distribution of neonates in different birth weight categories. (c) Number of neonates and HAI rates stratified by birth weight group.\u003c/p\u003e","description":"","filename":"fig.2.png","url":"https://assets-eu.researchsquare.com/files/rs-7581104/v1/7b1103cf986a7027636161a3.png"},{"id":105754856,"identity":"8aefa7ba-e67e-44a5-9c6a-b8a099a42861","added_by":"auto","created_at":"2026-03-30 16:22:32","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":4150579,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7581104/v1/e9fe49fb-fe74-4089-9ee8-0a271a81bc13.pdf"},{"id":93062731,"identity":"14444633-b57c-4539-a6f3-85a90475336c","added_by":"auto","created_at":"2025-10-08 16:38:02","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":187989,"visible":true,"origin":"","legend":"\u003cp\u003eSupplementary File 1: Data Collection Questionnaire. (English version)\u003c/p\u003e","description":"","filename":"Questionnaire.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7581104/v1/4934d0d6989a0baddd828dac.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Healthcare-Associated Infections in Chinese Neonates: A Multicenter Retrospective Period Prevalence Survey in Jiangsu Province (2023)","fulltext":[{"header":"Background","content":"\u003cp\u003eAdvances in medical technology have significantly improved survival rates for preterm infants and neonates with congenital anomalies. Yet these vulnerable patients exhibit functionally immature immune systems and organ dysfunction relative to healthy term infants, with clinical severity inversely correlated with gestational age. Prolonged hospitalization exposes them to multiple infection risks: intensive antimicrobial use, invasive procedures such as surgery, intravascular catheterization and mechanical ventilation, and environmental contact with multidrug-resistant pathogens. Such interventions disrupt microbial homeostasis and compromise mucocutaneous barrier integrity, creating synergistic conditions that predispose to healthcare-associated infections (HAI)\u0026mdash;which are associated with extended hospitalization, elevated healthcare costs, and increased mortality[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eGlobal epidemiological studies report substantial neonatal HAI burdens, with incidence rates ranging from 3.35% to 21.40% across clinical settings[\u003cspan additionalcitationids=\"CR3 CR4 CR5\" citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Recurrent outbreaks continue to challenge healthcare systems worldwide[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e], underscoring the need for updated regional surveillance. Neonatal HAI epidemiology exhibits marked geographical and temporal variation. For instance, a 1999 U.S. Neonatal Intensive Care Unit (NICU) study across 29 units reported an 11.4% infection rate, predominantly involving bloodstream, respiratory, and ear/nose/throat infections, with coagulase-negative \u003cem\u003estaphylococci\u003c/em\u003e (CoNS), \u003cem\u003eEnterococcus spp\u003c/em\u003e., and \u003cem\u003eEscherichia coli\u003c/em\u003e as primary pathogens[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Similarly, a 2011 European multicenter study documented 10.7% HAI incidence featuring primarily bloodstream infections where CoNS accounted for 58.1% of isolates[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Conversely, an Egyptian single-center study observed a substantially higher rate (21.40%) dominated by pulmonary infections[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. China\u0026rsquo;s only multicenter investigation conducted in 2013 across 17 NICUs reported a 3.35% HAI rate with bloodstream infections predominating (68.4%)[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. However, this pivotal study is now over a decade old. Given the substantial investments in healthcare infrastructure and infection control programs over the past decade, particularly in economically developed regions like Jiangsu Province\u0026mdash;a region of over 84\u0026nbsp;million people with an advanced healthcare system\u0026mdash;there is a pressing need to reassess the contemporary epidemiology of neonatal HAI.\u003c/p\u003e\u003cp\u003ePrevalence surveys typically employ point prevalence or period prevalence. While point prevalence requires fewer resources and is internationally prevalent, it may underestimate short-duration HAI (such as lower respiratory tract and urinary tract infections) and generally yields lower rates than period prevalence[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Our study therefore adopted the period prevalence approach. Under the guidance of the Jiangsu Provincial Health Commission and the Hospital Infection Control Branch of the Jiangsu Maternal and Child Health Association (JSMCHA-ICB), we conducted a multicenter, province-wide retrospective survey to assess the prevalence of neonatal HAI in Jiangsu Province for the year 2023. This study represents the first comprehensive effort of its kind in the region in recent years, aiming to address current knowledge gaps by: (1) determining the period prevalence and epidemiological characteristics of neonatal HAIs, and (2) identifying high-risk populations and predominant pathogens to guide the development of targeted, precision prevention strategies.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eStudy Design and Setting\u003c/h2\u003e\u003cp\u003eThis multicenter, retrospective period prevalence survey was conducted to determine the epidemiological characteristics of neonatal HAI in Jiangsu Province from January 1 to December 31, 2023. Invitations were extended to all of secondary-level hospitals and above that operated neonatal wards within the province. Ultimately, 30 hospitals agreed to participate and completed the survey.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eStudy population\u003c/h3\u003e\n\u003cp\u003eThe study population included all neonates (birth to 28 days of age) hospitalized for \u0026ge;\u0026thinsp;48 hours in the neonatal wards or NICUs of the participating hospitals during the 2023 calendar year. Neonates admitted solely to delivery rooms or outpatient settings, or with hospitalization duration\u0026thinsp;\u0026lt;\u0026thinsp;48 hours, were excluded. Data collection was performed between September and October 2024.\u003c/p\u003e\n\u003ch3\u003eSurvey Instrument Development and Validation\u003c/h3\u003e\n\u003cp\u003eThe structured electronic questionnaire was developed by JSMCHA-ICB in accordance with the U.S. Centers for Disease Control and Prevention/National Healthcare Safety Network (CDC/NHSN) HAI criteria and China\u0026rsquo;s National Health Commission \u003cem\u003eGuidelines for the Construction of Neonatal Wards\u003c/em\u003e[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. A multidisciplinary expert panel\u0026mdash;including HAI prevention specialists, neonatologists, clinical microbiologists, and epidemiologists\u0026mdash;designed and reviewed the instrument. The final questionnaire consisted of four modules comprising 59 key data items.The full English version of the questionnaire is available as Supplementary File 1.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eHospital Demographics\u003c/strong\u003e\u003cp\u003eName, location, type (general/maternity and child health specialty), accreditation level (Tertiary/Secondary); total bed capacity; number and qualifications of infection preventionists (IP).\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eNeonatal Ward Parameters\u003c/strong\u003e\u003cp\u003eWard type (general/NICU); approved and operational bed capacities; compliance with layout standards (area per bed\u0026thinsp;\u0026ge;\u0026thinsp;6m\u0026sup2;, bed spacing\u0026thinsp;\u0026ge;\u0026thinsp;1m); staffing levels (physicians, nurses, support staff as of December 31, 2023); Infection prevention infrastructure including isolation room availability, active HAI surveillance, high-efficiency particulate air filtration, and environmental monitoring frequency.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eHAI Surveillance Data\u003c/strong\u003e\u003cp\u003eTotal neonates admitted and patient-days in 2023; distributions by birthweight (\u0026le;\u0026thinsp;1000g, 1001\u0026ndash;1500g, 1501\u0026ndash;2500g, \u0026gt;\u0026thinsp;2500g); total HAI cases.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eDevice Utilization Data\u003c/strong\u003e\u003cp\u003eTotal device-days stratified by birthweight.\u003c/p\u003e\u003c/p\u003e\u003cp\u003eFor each HAI case, additional details were recorded: infection date, site, microbiological testing conducted, identified pathogens, birthweight, and device association.\u003c/p\u003e\u003cp\u003eAn accompanying Data Collection Guide\u0026mdash;containing standardized definitions\u0026mdash;was developed to ensure consistency. Prior to full deployment, a pilot study was conducted in three representative hospitals: a provincial tertiary specialty hospital, a prefectural tertiary general hospital, and a secondary specialty hospital. Feedback from the pilot helped refine the questionnaire and guide, improving clarity, feasibility, and completeness.\u003c/p\u003e\n\u003ch3\u003eData Collection Procedures\u003c/h3\u003e\n\u003cp\u003eData collection was performed electronically using \"Wenjuanxing\", a widely adopted online survey platform in China compliant with the Cybersecurity Law of the People's Republic of China and healthcare data security regulations. The platform ensures data security through encrypted transmission, access controls, and backups.\u003c/p\u003e\u003cp\u003eEach participating hospital designated a certified IP as the primary data collector. IP retrospectively reviewed medical records, infection surveillance logs, microbiological laboratory reports, and nursing documentation for all neonates hospitalized in the neonatal ward throughout 2023. They identified all eligible hospitalized neonates. Each neonate was screened, and all HAI meeting the predefined case definitions occurring during their 2023 hospitalization were confirmed. Following departmental head verification, data were entered into the online platform.\u003c/p\u003e\u003cp\u003ePrior to data collection, all designated IP received standardized training from the study core team (JSMCHA-ICB experts). Three experienced infection control specialists served as reviewers, performing logic consistency and plausibility checks on all submitted questionnaires. Flagged anomalous data were clarified and corrected exclusively via the platform's secure messaging system. Continuous technical support was provided throughout the data collection period.\u003c/p\u003e\n\u003ch3\u003eDefinitions\u003c/h3\u003e\n\u003cp\u003eHAI, including catheter-related bloodstream infections (CLABSI) and ventilator-associated pneumonia (VAP), were defined according to the CDC/NHSN criteria[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Key diagnostic elements included: 1) absence of infection or incubation at admission; 2) onset\u0026thinsp;\u0026ge;\u0026thinsp;48 hours post-admission; and 3) association with medical care or healthcare exposure. Infections acquired during birth canal passage were classified as HAI.\u003c/p\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eStatistical Analysis\u003c/h2\u003e\u003cp\u003eStatistical analyses were performed using SPSS Statistics (Version 26.0). Categorical variables are presented as frequencies and percentages. Continuous variables are presented as median with interquartile range (IQR). Rates were compared using the Chi-square test (\u003cem\u003eχ\u0026sup2;\u003c/em\u003e) or Fisher's exact test (when expected cell frequencies were \u0026lt;\u0026thinsp;5), with the significance level set at α\u0026thinsp;=\u0026thinsp;0.05 (two-tailed).\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\u003ch2\u003eCharacteristics of Participating Hospitals and Study Population\u003c/h2\u003e\u003cp\u003e A total of 30 hospitals from all 13 prefecture-level cities in Jiangsu Province participated in the study, ensuring broad geographic representation (Fig.\u0026nbsp;1). Among them, 20 (66.7%) were women and children's specialty hospitals and 26 (86.7%) were tertiary hospitals (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Specialty hospitals cared for a substantially larger proportion of the study population (79.4% of neonates, 81.6% of patient-days) than general hospitals. All participating hospitals employed real-time nosocomial infection surveillance systems and conducted active surveillance; the median number of IP was 0.6 (IQR 0.5\u0026ndash;0.8) per 100 beds. Furthermore, 43.3% (13/30) of institutions did not meet the recommended nurse-to-neonate ratio.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eCharacteristics of Participating Hospitals and the Study Population\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCharacteristic\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOverall\u003c/p\u003e\u003cp\u003e(N\u0026thinsp;=\u0026thinsp;30)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eWomen and Children's Hospitals (N\u0026thinsp;=\u0026thinsp;20)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eGeneral Hospitals (N\u0026thinsp;=\u0026thinsp;10)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHospital Level, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTertiary\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e26 (86.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e16 (80.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e10 (100.0)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSecondary\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4 (13.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4 (20.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0 (0.0)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e\u003cp\u003eNeonatal Ward Type, n (%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNICU\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e28 (93.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e19 (95.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e9 (90.0)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNeonatal Ward\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e30 (100)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e20 (100)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e10 (100)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIP Staffing\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMedian IP per 100 beds (IQR)*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.6 (0.5\u0026ndash;0.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.8 (0.6\u0026ndash;0.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.5 (0.4\u0026ndash;0.6)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e\u003cp\u003eStudy Population (2023)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal neonates admitted, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e36957\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e29329 (79.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7628 (21.6)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal patient-days, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e327098\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e266922 (81.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e60176 (19.4)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e*IP, infection preventionist.\u003c/p\u003e\u003cp\u003e\u003cem\u003eInsert Fig.\u0026nbsp;1 here\u003c/em\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003eHAI Prevalence and Distribution\u003c/h2\u003e\u003cp\u003eA total of 370 episodes of HAI were observed among 36,957 neonates, corresponding to a prevalence of 1.0% (95% CI: 0.9%\u0026ndash;1.1%). Considerable variation in HAI rates was observed across different birthweight categories (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Neonates with a birthweight\u0026thinsp;\u0026lt;\u0026thinsp;1500 g exhibited a substantially higher incidence of HAI, accounting for nearly half of all episodes (46.7%, 173/370). Their relative risk of HAI was 17.0 times greater (95% CI: 14.0\u0026ndash;20.8; P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) than that of neonates weighing\u0026thinsp;\u0026ge;\u0026thinsp;1500 g.\u003c/p\u003e\u003cp\u003eThe HAI prevalence was significantly higher in specialty hospitals (1.07%) than in general hospitals (0.75%) (χ\u0026sup2; = 6.253, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.012). Similarly, tertiary hospitals had a significantly higher infection rate (1.03%) compared to secondary hospitals (0.16%) (χ\u0026sup2; = 9.236, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.002). Geographically, HAI rates varied among the 13 prefecture-level cities, with three cities reporting prevalence rates above the upper confidence limit of the overall provincial rate (Fig.\u0026nbsp;2).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eDistribution of HAI by birthweight\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBirthweight (g)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePatients\u003c/p\u003e\u003cp\u003en (%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePatient-Days\u003c/p\u003e\u003cp\u003en (%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eHAI Cases\u003c/p\u003e\u003cp\u003en (%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eIncidence Rate\u003c/p\u003e\u003cp\u003e%(95% CI)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eMedian (IQR)*\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026le;\u0026thinsp;1000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e535 (1.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e18748 (5.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e56 (15.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e10.5 (7.9\u0026ndash;13.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e4.7(0.0-12.3)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1001\u0026ndash;1500\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1277 (3.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e40760 (12.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e117 (31.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e9.2 (7.6\u0026ndash;10.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e5.9 (0.0-10.3)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1501\u0026ndash;2500\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e7453 (20.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e90830 (27.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e91 (24.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1.2 (1.0-1.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.6 (0.0-1.5)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026gt;2500\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e27692 (74.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e176760 (54.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e106 (28.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.4 (0.3\u0026ndash;0.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.2 (0.1\u0026ndash;0.4)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e36957\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e327098\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e370\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1.0 (0.9\u0026ndash;1.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.5 (0.3\u0026ndash;1.8)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e*The median (IQR) calculation for each subgroup was restricted to the hospitals that reported cases (\u0026le;\u0026thinsp;1000 g: n\u0026thinsp;=\u0026thinsp;22; 1001\u0026ndash;1500 g: n\u0026thinsp;=\u0026thinsp;27; \u0026gt;1500 g: n\u0026thinsp;=\u0026thinsp;30).\u003c/p\u003e\u003cp\u003e\u003cem\u003eInsert Fig.\u0026nbsp;2 here\u003c/em\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003eDistribution of Infection Sites and Pathogens\u003c/h2\u003e\u003cp\u003eAmong 370 neonates with HAI, cultures were performed in 263 (71.1%) cases, and 192 pathogens were isolated (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e), of which multiple organisms were isolated from 7 samples. The pathogen distribution comprised 157 (81.8%; 96 Gram-negative and 61 Gram-positive) bacterial strains, 23 (12.0%) fungal isolates, and 12 (6.3%) viral agents. CoNS (18.2%) and \u003cem\u003eKlebsiella pneumoniae\u003c/em\u003e (17.2%) represented the predominant microbial groups. CoNS was particularly prominent in bloodstream infections, accounting for 29.5% of pathogens isolated from this site. \u003cem\u003eKlebsiella pneumoniae\u003c/em\u003e was a major pathogen in both bloodstream (17.1%) and lower respiratory tract (21.2%) infections. \u003cem\u003eRotavirus\u003c/em\u003e dominated gastrointestinal infections.\u003c/p\u003e\u003cp\u003eSix multidrug-resistant organisms were identified, including three strains of carbapenem-resistant \u003cem\u003eKlebsiella pneumoniae\u003c/em\u003e, two methicillin-resistant \u003cem\u003eStaphylococcus aureus\u003c/em\u003e, and one carbapenem-resistant \u003cem\u003eEnterobacter cloacae complex\u003c/em\u003e.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003ePathogen distribution by infection site among neonates with HAI (n,%)\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePathogen\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003cp\u003ePathogens\u003c/p\u003e\u003cp\u003en (%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eBloodstream\u003c/p\u003e\u003cp\u003en (%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eLower respiratory tract\u003c/p\u003e\u003cp\u003en (%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eGastrointestinal tract\u003c/p\u003e\u003cp\u003en (%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eOther sites\u003c/p\u003e\u003cp\u003en (%)*\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eCoagulase-negative staphylococci\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e35 (18.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e31 (29.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2 (3.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2 (11.8)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eKlebsiella pneumoniae\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e33 (17.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e18 (17.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e11 (21.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1 (5.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e3 (17.6)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eCandida albicans\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e12 (6.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e7 (6.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2 (3.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1 (5.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2 (11.8)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eEscherichia coli\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e15 (7.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5 (4.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7 (13.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1 (5.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2 (11.8)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eEnterobacter aerogenes\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e12 (6.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6 (5.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6 (11.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eEnterobacter cloacae complex\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e11 (5.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e7 (6.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2 (3.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1 (5.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1 (5.9)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eStaphylococcus aureus\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e10 (5.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6 (5.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3 (5.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1 (5.9)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eRotavirus\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e9 (4.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e9 (50)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eAcinetobacter baumannii\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e6 (3.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2 (1.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4 (7.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003ePseudomonas aeruginosa\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e6 (3.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2 (1.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4 (7.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eCandida parapsilosis\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e6 (3.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6 (5.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eEnterococcus faecalis\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5 (2.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4 (3.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1 (5.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eEnterococcus faecium\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5 (2.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3 (2.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1 (1.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1 (5.9)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eC.glabrata\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3 (1.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2 (1.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1 (1.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eMurivirus\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3 (1.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e3 (17.6)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eStreptococcus salivarius\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3 (1.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1 (1.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1 (5.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1 (5.9)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOther pathogens\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e18 (9.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6 (5.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e8 (15.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3 (16.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1 (5.9)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003e192\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e105\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e52\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e18\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e17\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNegative culture\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e77\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e26\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e25\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNot cultured\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e107\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e31\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e35\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e39\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMultiple organisms\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e*Other sites including Upper respiratory ,n\u0026thinsp;=\u0026thinsp;18, Central nervous system (n\u0026thinsp;=\u0026thinsp;3), Urinary tract (n\u0026thinsp;=\u0026thinsp;2), Oral cavity(n\u0026thinsp;=\u0026thinsp;2), Ear/nose/throat (n\u0026thinsp;=\u0026thinsp;2), Soft tissue (n\u0026thinsp;=\u0026thinsp;1), Surgical site infection (n\u0026thinsp;=\u0026thinsp;2), Other (n\u0026thinsp;=\u0026thinsp;4).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003eDevice-associated infections\u003c/h2\u003e\u003cp\u003eThe average duration of use was 16 days per neonate for central lines and 9 days for ventilators. A total of 26 CLABSI (0.7 per 1000 device-days, 95% CI 0.4\u0026ndash;1.0) and 24 VAP (1.2 per 1000 device-days, 95% CI 0.7\u0026ndash;1.6) were recorded (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e), the rate of VAP exceeded that of CLABSI in this cohort. CLABSI incidence exhibited borderline significance across birthweight categories (χ\u0026sup2; = 7.08, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.059), whereas no significant birthweight-dependent variations were observed for VAP rates (χ\u0026sup2; = 3.45, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.308).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eDevice-Associated Outcomes by birthweight\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"7\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003ebirthweight (g)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDevice-days\u003c/p\u003e\u003cp\u003en (%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eUtilization ratio (%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eInfections\u003c/p\u003e\u003cp\u003en (%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eIncidence rates\u003c/p\u003e\u003cp\u003e\u0026permil; (95% CI)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u003cp\u003eMedian (IQR)*\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eCentral line\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026lt;1000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e7431 (20.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e39.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e5 (19.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.7 (0.1\u0026ndash;1.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u003cp\u003e0 (0.0\u0026ndash;0.0)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1001\u0026ndash;1500\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1409 (38.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e34.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e16 (61.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.1 (0.6\u0026ndash;1.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u003cp\u003e0 (0.0\u0026minus;1.1 )\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1501\u0026ndash;2500\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e9626 (26.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e10.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2 (7.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.2 (0.1\u0026ndash;0.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u003cp\u003e0 (0.0\u0026ndash;0.0)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026gt;2500\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5297 (14.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3 (11.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.6 (0.1\u0026ndash;1.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u003cp\u003e0 (0.0\u0026ndash;0.0)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e36453\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e11.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e26\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.7 (0.4-1.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u003cp\u003e0 (0.0\u0026minus;0.9)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eMechanical ventilation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026lt;1000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5194 (25.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e27.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6 (25.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.2 (0.7\u0026ndash;2.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u003cp\u003e0 (0.0\u0026ndash;0.0)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1001\u0026ndash;1500\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4510 (22.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e11.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e9 (37.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.0 (0.7\u0026ndash;3.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u003cp\u003e0 (0.0\u0026minus;0.5 )\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1501\u0026ndash;2500\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4171 (20.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4 (16.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.0 (0.0-1.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u003cp\u003e0 (0.0\u0026ndash;0.0)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026gt;2500\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e6625 (32.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e5 (20.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.8 (0.1\u0026ndash;1.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u003cp\u003e0 (0.0\u0026ndash;0.0)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e20500\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.2 (0.7\u0026ndash;1.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u003cp\u003e0 (0.0\u0026minus;0.5)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e*Median (IQR) includes only hospitals with device use (number of hospitals per subgroup: Central line\u0026mdash;\u0026lt;1000g: 22, 1001\u0026ndash;1500g: 26, 1501\u0026ndash;2500g: 25, \u0026gt;\u0026thinsp;2500g: 19; Mechanical ventilation\u0026mdash;\u0026lt;1000g: 21, 1001\u0026ndash;1500g: 24, 1501\u0026ndash;2500g: 29, \u0026gt;\u0026thinsp;2500g: 28).\u003c/p\u003e\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis first province-wide, multicenter study of 36,957 neonates across 30 hospitals in Jiangsu Province uncovered an unexpectedly low overall prevalence of HAIs\u0026mdash;just 1.0% in 2023. This figure stands in stark contrast to rates reported elsewhere in China (3.35%) as well as those from developed countries and regions, including U.S. NICUs (11.4%) and European neonatal care settings (5.1%)[\u003cspan additionalcitationids=\"CR3\" citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. However, these comparisons require cautious interpretation. First, differences in study methods, populations, and timing may render direct cross-comparisons invalid. Our study encompassed all hospitalized neonates, not only NICU patients, and employed a period prevalence survey. Second, the lower prevalence may be attributed to Jiangsu's substantial investment in healthcare resources. As an economically developed region, all 30 participating hospitals were equipped with real-time nosocomial infection surveillance systems and implemented active surveillance. This system facilitates timely identification of infection risks and enhances the promptness of interventions[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Yet a deeper investigation revealed a paradox: despite technological advancement, human resource allocations lag significantly. The ratio of IP staff per 100 beds was only 0.6, below that of Guiyang (1.0) and the U.S. (1.2)[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Moreover, the quantity and experience of IP staff have been shown to be negatively correlated with HAI rates [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e].Compounding this, 44% of hospitals reported understaffed nursing teams,which may compromise the effective implementation of infection control measures and warrants targeted improvement[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eConsistent with other multicenter studies[\u003cspan additionalcitationids=\"CR3\" citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e], we observed considerable inter-hospital variation in HAI rates, which was largely attributable to differences in case-mix and patient acuity. Tertiary and specialized hospitals cared for a higher proportion of high-risk neonates (birthweight\u0026thinsp;\u0026lt;\u0026thinsp;1500 g) than secondary and general hospitals (Fig.\u0026nbsp;2). This led to a greater HAI burden in these centers, rather than indicating inferior infection control practices. As our results demonstrate, nearly half of all HAI occurred among infants with a birthweight\u0026thinsp;\u0026lt;\u0026thinsp;1500 g, even though they constituted only 5% of the cohort. Birthweight and gestational age are among the most important risk factors for HAI development[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e], underscoring the critical need to refocus prevention efforts on this vulnerable population.\u003c/p\u003e\u003cp\u003eAlthough birthweight is widely used for stratifying neonatal HAI risk, we found considerable variation in infection rates even within the same birthweight category. This stark disparity underscores that traditional birth-weight stratification, while useful, masks significant internal risk heterogeneity\u0026mdash;a point previously raised[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. There is a clear need to incorporate more sensitive illness severity scores, such as Score for Neonatal Acute Physiology and its perinatal extension, which have been used to assess neonatal mortality risk[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. However, their validity in predicting HAI risk requires further validation.\u003c/p\u003e\u003cp\u003eThe most common infection sites in this study were bloodstream (44.1%), lower respiratory tract (17.4%), and gastrointestinal tract (5.5%), collectively accounting for 67% of infections\u0026mdash;a finding consistent with domestic reports[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. While bloodstream and lower respiratory infections are also predominant in U.S. and European settings[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e], ear/nose/throat and urinary tract infections are reported more frequently than gastrointestinal infections in those regions[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. The leading pathogens identified here were CoNS (18.2%), \u003cem\u003eKlebsiella pneumoniae\u003c/em\u003e (17.2%), and \u003cem\u003eCandida albicans\u003c/em\u003e (6.3%), which differs from profiles in the U.S. (CoNS, enterococci, \u003cem\u003eE. coli\u003c/em\u003e) and Europe (CoNS, \u003cem\u003eE. coli\u003c/em\u003e, \u003cem\u003eS. aureus\u003c/em\u003e)[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Notably, CoNS accounted for 29.5% of bloodstream infections, with \u003cem\u003eS. epidermidis\u003c/em\u003e being the most common species. The predominance of CoNS in bloodstream infections is a globally recognized phenomenon[\u003cspan additionalcitationids=\"CR4 CR5\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e], necessitating tailored preventive strategies. The distinct distribution of infection sites and pathogens highlights the regional specificity of neonatal HAIs in Jiangsu and emphasizes the importance of context-specific control measures. It should be noted, however, that only 71.1% of cases underwent microbiological culture, which may have introduced bias into the pathogen spectrum; therefore, improving microbial submission rates remains essential.\u003c/p\u003e\u003cp\u003eThe incidence of CLABSI was 0.7\u0026permil;, consistent with a previous multicenter study in China (0.66\u0026permil;) but lower than rates reported in the U.S. (1.13\u0026permil;) and the Netherlands (2.91\u0026ndash;16.14\u0026permil;) [\u003cspan additionalcitationids=\"CR20\" citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. The incidence of VAP was 1.2\u0026permil;, which is substantially lower than the rate reported in a Chinese multicenter study (7.23\u0026permil;) but higher than that in the U.S. (0.81\u0026permil;)[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. The surveillance definition for VAP in the CDC/NHSN criteria contains subjective elements[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e], which may be an important factor contributing to these discrepancies. Although CLABSI is considered the most important device-associated infection in neonates[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e], the prevalence of VAP exceeded that of CLABSI in this study\u0026mdash;an unexpected finding suggesting that prevention and control of VAP should be prioritized.\u003c/p\u003e\u003cp\u003eCurrently, there are no established optimal bundled practices for the prevention of neonatal VAP[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Our study found that in Jiangsu Province, measures such as elevation of the head of the bed, use of sterile water for humidification, weekly replacement of ventilator circuits and humidification devices, and daily assessment for extubation readiness are widely implemented. But only a very small number of hospitals use sterile gauze for oral care in neonates. It is important to note that these measures are primarily derived from adult VAP prevention guidelines, and their scientific validity remains questionable. In 2022, the Society for Healthcare Epidemiology of America released a guideline which indicates that only four neonatal VAP prevention strategies are supported by high-quality evidence: (1) Use non-invasive positive pressure ventilation in selected populations, (2) Use caffeine therapy to facilitate extubation; (3) Minimize the duration of mechanical ventilation; and (4) Avoid reintubation by using nasal continuous positive airway pressure, non-invasive positive pressure ventilation, or high flow nasal cannula in the post-extubation period[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eA limitation of this study is its reliance on questionnaire-based data collection. While this approach enables rapid multicenter collaboration, it does not capture patient-level data, thus preventing adjustment for inter-hospital differences in case mix and illness severity.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study represents the first province-wide multicenter investigation of neonatal HAI in Jiangsu Province. reveals a comparatively low overall HAI prevalence, likely reflecting substantial regional investments in healthcare quality and infection control, yet highlights significant vulnerabilities among extremely low birthweight infants and identifies device-associated infections, particularly VAP, as a key prevention target. Future efforts should prioritize prevention for infants with birthweight\u0026thinsp;\u0026lt;\u0026thinsp;1500g and bloodstream infections, while optimizing staffing levels for both nursing and IP personnel, along with strengthening microbiological testing, is imperative.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 19.3662%;\"\u003e\n \u003cp\u003eAbbreviation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 80.6338%;\"\u003e\n \u003cp\u003eFull Term\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 19.3662%;\"\u003e\n \u003cp\u003eCDC/NHSN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 80.6338%;\"\u003e\n \u003cp\u003eCenters for Disease Control and Prevention/National Healthcare Safety Network\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 19.3662%;\"\u003e\n \u003cp\u003eCI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 80.6338%;\"\u003e\n \u003cp\u003eConfidence Interval\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 19.3662%;\"\u003e\n \u003cp\u003eCLABSI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 80.6338%;\"\u003e\n \u003cp\u003eCentral Line-Associated Bloodstream Infection\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 19.3662%;\"\u003e\n \u003cp\u003eCoNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 80.6338%;\"\u003e\n \u003cp\u003eCoagulase-negative staphylococci\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 19.3662%;\"\u003e\n \u003cp\u003eHAI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 80.6338%;\"\u003e\n \u003cp\u003eHealthcare-associated infection\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 19.3662%;\"\u003e\n \u003cp\u003eIP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 80.6338%;\"\u003e\n \u003cp\u003eInfection Preventionist\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 19.3662%;\"\u003e\n \u003cp\u003eIQR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 80.6338%;\"\u003e\n \u003cp\u003eInterquartile Range\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 19.3662%;\"\u003e\n \u003cp\u003eJSMCHA-ICB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 80.6338%;\"\u003e\n \u003cp\u003eJiangsu Maternal and Child Health Association - Infection Control Branch\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 19.3662%;\"\u003e\n \u003cp\u003eNICU\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 80.6338%;\"\u003e\n \u003cp\u003eNeonatal Intensive Care Unit\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 19.3662%;\"\u003e\n \u003cp\u003eRR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 80.6338%;\"\u003e\n \u003cp\u003eRelative Risk\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 19.3662%;\"\u003e\n \u003cp\u003eVAP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 80.6338%;\"\u003e\n \u003cp\u003eVentilator-Associated Pneumonia\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis retrospective study was conducted as part of a provincial public health surveillance initiative led by the Jiangsu Provincial Health Commission.The study was reviewed by the Medical Ethics Committee of The First Affiliated Hospital of Nanjing Medical University. In accordance with \u003cstrong\u003eArticle 32 of China\u0026apos;s \u0026lsquo;\u003cem\u003eRegulations on Ethical Review of Biomedical Research Involving Humans\u003c/em\u003e\u0026rsquo; (2016)\u003c/strong\u003e, which stipulates that ethical review is not required for research utilizing existing documented data, the Committee \u003cstrong\u003egranted an exemption from ethical approval and waived the requirement for individual informed consent\u003c/strong\u003e (Approval/Exemption Number: 2025-SR-861). All data were analyzed in an anonymized manner\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable. This manuscript does not contain any individual person\u0026apos;s data in any form.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analyzed during the current study are not publicly available due to provincial health data regulations but may be available from the corresponding author on reasonable request and with permission from JSMCHA-ICB.\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 work was supported by the Jiangsu Hospital Association [Grant numbers JSYGY-3-2020-157 and JSYGY-3-2023-363]; the Nantong Health Commission [Grant number QNZ2024057]; and the Nantong Science and Technology Bureau [Grant number MSZ2024159]. The funders had no role in the design of the study, data collection, analysis, interpretation, or in writing the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWWL and LF contributed equally to this work. Conceptualization: XZ, WWL. Data curation: WWL, LF, FYW. Formal analysis: WWL, LF. Funding acquisition: XZ. Investigation: All authors. Methodology: WWL, LF, XZ. Project administration: XZ. Resources: XZ. Supervision: XZ. Validation: WWL, LF, FYW. Writing \u0026ndash; original draft: WWL, LF. Writing \u0026ndash; review \u0026amp; editing: All authors. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors would like to thank JSMCHA-ICB for its guidance and coordination. We are also grateful to all the infection preventionists and staff at the 30 participating hospitals for their diligent work in data collection.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSupplementary Files\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSupplementary File 1: Data Collection Questionnaire. (English version)\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eMinistry of Health of the People\u0026apos;s Republic of China. Hospital infection diagnostic standards (trial). Beijing: People\u0026apos;s Medical Publishing House; \u003cstrong\u003e2001\u003c/strong\u003e. \u003c/li\u003e\n\u003cli\u003eJia H, Yin H, Wu A, Li Y, Ren J, Li R, et al. Multicenter study on the epidemiology of healthcare-associated infection in neonatal intensive care units. 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Pediatrics. \u003cstrong\u003e1995;95(2):225\u0026ndash;30\u003c/strong\u003e.\u003c/li\u003e\n\u003cli\u003e\u003cstrong\u003eJansen SJ, Broer SDL, Hemels MAC, Visser DH, Antonius TAJ, Heijting IE,\u003c/strong\u003e et al. Central-line-associated bloodstream infection burden among Dutch neonatal intensive care units. J Hosp Infect. \u003cstrong\u003e2024;144:20\u0026ndash;7\u003c/strong\u003e. https://doi.org/10.1016/j.jhin.2023.11.020.\u003c/li\u003e\n\u003cli\u003e\u003cstrong\u003eRen J, Yin H, Wu A, Li Y, Jia H, Li R, Zhang X, Du B, Li J.\u003c/strong\u003e Multicenter study on device-associated infection in neonatal intensive care unit. Chin J Infect Control. \u003cstrong\u003e2015;14(8):530\u0026ndash;4\u003c/strong\u003e.\u003c/li\u003e\n\u003cli\u003e\u003cstrong\u003eDudeck MA, Edwards JR, Allen-Bridson K, Gross C, Malpiedi PJ, Peterson KD, \u003c/strong\u003eet al\u003cstrong\u003e.\u003c/strong\u003e National Healthcare Safety Network report, data summary for 2013, Device-associated Module. Am J Infect Control. \u003cstrong\u003e2015;43(3):206\u0026ndash;21\u003c/strong\u003e. https://doi.org/10.1016/j.ajic.2014.11.014.\u003c/li\u003e\n\u003cli\u003e\u003cstrong\u003eBierwirth NC, Cantey JB. The Newborn Nursery and the Neonatal Intensive Care Unit. In: Bennett JV, Jarvis WR, Brachman PS, editors. Bennett \u0026amp; Brachman\u0026apos;s Hospital Infections. 6th ed. Philadelphia: Wolters Kluwer; 2021. p. 398.\u003c/strong\u003e\u003c/li\u003e\n\u003cli\u003e\u003cstrong\u003eCocoros NM, Priebe GP, Logan LK, Coffin S, Larsen G, Toltzis P,\u003c/strong\u003e et al. A Pediatric Approach to Ventilator-Associated Events Surveillance. Infect Control Hosp Epidemiol. \u003cstrong\u003e2017;38(3):327\u0026ndash;33\u003c/strong\u003e. https://doi.org/10.1017/ice.2016.277.\u003c/li\u003e\n\u003cli\u003e\u003cstrong\u003eKlompas M, Branson R, Cawcutt K, Crist M, Eichenwald EC, Greene LR,\u003c/strong\u003e et al. Strategies to prevent ventilator-associated pneumonia, ventilator-associated events, and nonventilator hospital-acquired pneumonia in acute-care hospitals: 2022 Update. Infect Control Hosp Epidemiol. \u003cstrong\u003e2022;43(6):687\u0026ndash;713\u003c/strong\u003e. https://doi.org/10.1017/ice.2022.88.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-infectious-diseases","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"infd","sideBox":"Learn more about [BMC Infectious Diseases](http://bmcinfectdis.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/infd","title":"BMC Infectious Diseases","twitterHandle":"#bmcinfectdis","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Neonatal, Healthcare-associated infections, Multi-center study, Device-associated infections","lastPublishedDoi":"10.21203/rs.3.rs-7581104/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7581104/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cb\u003eBackground\u003c/b\u003e\u003c/p\u003e\u003cp\u003eHealthcare-associated infections (HAI) pose a significant threat to neonates, especially preterm and critically ill infants, leading to prolonged hospitalization, increased healthcare costs, and elevated mortality. Understanding the epidemiological characteristics of neonatal HAI is of major guiding significance for the development of targeted public health policies and clinical prevention strategies. This study aimed to investigate the epidemiology of neonatal HAI in Jiangsu Province, China, in 2023.\u003c/p\u003e\u003cp\u003e\u003cb\u003eMethods\u003c/b\u003e\u003c/p\u003e\u003cp\u003eA retrospective period prevalence survey was conducted in Jiangsu Province, China, from September to October 2024. Data on neonatal HAI occurring between January and December 2023 were collected using a structured questionnaire. Thirty hospitals from 13 cities ultimately participated and completed the survey.\u003c/p\u003e\u003cp\u003e\u003cb\u003eResults\u003c/b\u003e\u003c/p\u003e\u003cp\u003eAmong 36,957 neonates (327,098 patient-days), 370 HAI episodes were identified, yielding a prevalence of 1.0% (95% CI: 0.9%\u0026ndash;1.1%). Neonates with a birth weight\u0026thinsp;\u0026lt;\u0026thinsp;1500 g faced a dramatically higher risk (RR\u0026thinsp;=\u0026thinsp;17.0, 95% CI: 14.0\u0026ndash;20.8; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). The most common infection sites were bloodstream (45.7%), lower respiratory tract (39.2%), and gastrointestinal tract (5.5%). Predominant pathogens included coagulase-negative \u003cem\u003estaphylococci\u003c/em\u003e (18.2%) and \u003cem\u003eKlebsiella pneumoniae\u003c/em\u003e (17.2%). Device-associated infection rates were 0.7\u0026permil; (95% CI: 0.4\u0026ndash;1.0) for central line-associated bloodstream infection and 1.2\u0026permil; (95% CI: 0.7\u0026ndash;1.6) for ventilator-associated pneumonia.\u003c/p\u003e\u003cp\u003e\u003cb\u003eConclusion\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThis first province-wide study reveals a relatively low overall prevalence of HAI among neonates in Jiangsu. Prevention priorities should focus on high-risk neonatal birthweight\u0026thinsp;\u0026lt;\u0026thinsp;1500 g and bloodstream infections, supported by optimized staffing levels for both nursing and infection preventionist personnel, as well as strengthened microbiological surveillance.\u003c/p\u003e","manuscriptTitle":"Healthcare-Associated Infections in Chinese Neonates: A Multicenter Retrospective Period Prevalence Survey in Jiangsu Province (2023)","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-08 16:02:53","doi":"10.21203/rs.3.rs-7581104/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-01-21T12:38:32+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-01-21T05:43:59+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"180587170332839588641944006782516036976","date":"2026-01-12T09:41:44+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"233056128827609736318819268448624819268","date":"2025-11-24T06:53:10+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"136002573080951421750817981197319162913","date":"2025-10-14T15:06:40+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-07T15:07:54+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"329377447932376624100737137804005602566","date":"2025-09-26T01:29:09+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-09-26T01:20:15+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-09-26T01:19:07+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-09-24T16:52:11+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-09-24T02:08:41+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Infectious Diseases","date":"2025-09-24T01:53:53+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-infectious-diseases","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"infd","sideBox":"Learn more about [BMC Infectious Diseases](http://bmcinfectdis.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/infd","title":"BMC Infectious Diseases","twitterHandle":"#bmcinfectdis","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"7ee79a51-da7d-49da-8539-17157bbf7177","owner":[],"postedDate":"October 8th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2026-03-30T16:17:16+00:00","versionOfRecord":{"articleIdentity":"rs-7581104","link":"https://doi.org/10.1186/s12879-026-13202-z","journal":{"identity":"bmc-infectious-diseases","isVorOnly":false,"title":"BMC Infectious Diseases"},"publishedOn":"2026-03-28 16:09:06","publishedOnDateReadable":"March 28th, 2026"},"versionCreatedAt":"2025-10-08 16:02:53","video":"","vorDoi":"10.1186/s12879-026-13202-z","vorDoiUrl":"https://doi.org/10.1186/s12879-026-13202-z","workflowStages":[]},"version":"v1","identity":"rs-7581104","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7581104","identity":"rs-7581104","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}