Evidence map›Paper›PMID 40123043›Full record

ArticleEuropean journal of clinical microbiology & infectious diseases : official publication of the European Society of Clinical Microbiology2025

Evolving patterns of healthcare-associated infections in NICU: a five-year retrospective analysis from a tertiary children's hospital in China.

Zhen Wang, Jiali Wang, Kouzhu Zhu, Yan-Jun Kang

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Article in European journal of clinical microbiology & infectious diseases : official publication of the European Society of Clinical Microbiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

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3citing papers in PubMed
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1 · What the graph read from it

What it found

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3 · Its place in the literature

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3 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Zhen WangDepartment of Infection Management, Affiliated Children's Hospital of Jiangnan University, Wuxi, China.
Jiali WangDepartment of Neonatology, Affiliated Children's Hospital of Jiangnan University, Wuxi, China.
Kouzhu ZhuDepartment of Pharmacy, Affiliated Children's Hospital of Jiangnan University, Wuxi, China.
Yan-Jun KangPediatric Laboratory, Affiliated Children's Hospital of Jiangnan University, Wuxi, China. kangyj@jiangnan.edu.cn.

Funding

Research Project of Wuxi Health Committee: General Program M202407Top Talent Support Program for young and middle-aged people of Wuxi Health HB2023090
6 · The paper itself

Abstract

backgroundNeonates in the NICU, particularly those born with very low birth weights, are at heightened risk for healthcare-associated infections (HAIs). Such infections can prolong hospitalization, increase medical costs, and potentially lead to adverse long-term outcomes. Recognizing evolving infection patterns and targeted prevention measures is essential to improving patient care.

methodsWe retrospectively collected data on neonates admitted to the NICU of our hospital between January 2019 and December 2023. Information regarding HAI incidence, site of infection, device utilization, pathogen distribution, and antibiotic use was extracted and statistically analyzed. Comparisons regarding infection rates and clinical variables were performed using chi-square or Fisher's exact tests for categorical variables and Wilcoxon rank-sum tests for continuous variables.

resultsAmong 9786 neonates (70,509 patient-days), 86 HAI cases were identified (0.88%), corresponding to 1.22‰ infections per 1000 patient-days. Neonates with extremely low birth weight had significantly higher infection rates (13.04%) than other birth weight groups (p < 0.01). Bloodstream infections (35.87%) were the most common site, followed by respiratory and gastrointestinal infections (both 18.48%). Central line-associated bloodstream infection occurred at 0.75 infections per 1000 catheter-days, while ventilator-associated pneumonia decreased from 2.76‰ to 0.73‰ over the study period. Staphylococcus epidermidis was the predominant isolate among the pathogens identified. Neonates with HAIs had significantly longer antibiotic courses and higher rates of combination antibiotic therapy (p < 0.001).

conclusionsAlthough the overall incidence of NICU HAIs declined from 2019 to 2023, infection patterns continued to evolve, particularly regarding bloodstream infections. Prevention strategies must focus on high-risk neonates, rigorous device management, punctual surveillance of pathogen resistance, and prudent antibiotic use to further reduce infection morbidity and mortality in the NICU setting.

Indexed as

Cross InfectionIntensive Care Units, NeonatalAnti-Bacterial AgentsChinaFemaleHospitals, PediatricHumansIncidenceInfant, NewbornMaleRetrospective StudiesRisk FactorsTertiary Care CentersAnti-Bacterial AgentsEvolving patternsHealthcare-associated infectionsNeonates in the Neonatal Intensive Care UnitRetrospective analysis

Identifiers

PMID40123043

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.