Análise espaço-temporal das infecções relacionadas a dispositivos em unidades de terapia intensiva neonatais do estado de São Paulo

• Ano de defesa: 2025
• Autor(a) principal: Gerios, Ludmila [UNESP]
• Tipo de documento: Tese
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Estadual Paulista (Unesp)
• Palavras-chave em Português: Sepse neonatal; Infecções relacionadas à assistência em saúde; Estudo ecológico; Vigilância epidemiológica
• Link de acesso: https://hdl.handle.net/11449/260144

Introduction: High-risk newborns (NB) are at increased risk for acquisition of healthcare-associated infections (HCAI), which are currently the main cause of inevitable death in this population. Space time models can help understand the determinants of HCAI in NB and contribute to development of prevention and control policies. Objectives: Quantify device related infections in neonatal intensive care units (NICUs) located in the State of São Paulo. Evaluate the association of time, spatial, hospital characteristics and sociodemographic factors to the rates of these infections. Identify space-time patterns to device related infections through the state. Method: Ecologic study with data from all São Paulo State Program for Infection Control (SSPIC) notifying hospitals from 2009 to 2019. Outcomes: central line bloodstream infections (CLABSI) and ventilator associated pneumonia (VAP) in all NB and in the subgroup of very low birth weight (VLBW). Variables: year, hospitals and municipality data. Univariate and multivariable models of Poisson regression were used for analysis. The annual HCAI rates were georeferenced and kernel density maps were built. The study was approved by the local committee for ethics in research. Results: A total of 294 hospitals located in 80 municipalities reported neonatal data to SPPIC, amounting 2345 year-hospitals The analysis including all NB showed median ID for: VAP 1.49 (0-3.91 between years); confirmed CLABSI 6.82 (5.9-9.4) and clinical CLABSI 2.47 (0-6.29). Rates of all HCAI declined over time. Neonatal mortality rates of the municipality were associated with higher confirmed CLABSI [Incidence rate ratio (IRR) 1.06 confidence interval (CI) 95% 1.05-1.07] and VAP (IRR 1.04 CI 95% 1.03-1.06). Municipalities with higher HDI had higher rates of confirmed CLABSI (IRR 1.02 CI 95% 1.02-1.03). The sub analysis for VLBW infants showed similar results for the univariate and multivariable. The median VLBW ID of VAP was 0 (0-3.91 between years); confirmed CLABSI 7.05 (6.34-8.60) and clinical CLABSI 2.05 (0-5.67). Conclusion: The reduction in HCAI rates over the years can be related to surveillance model. Device related infections were associated to municipality’s neonatal and child mortality. The impact of socioeconomic factors in infection rates can be associated to diagnostic resources, especially for confirmed central line associated bloodstream infections.