Background: Healthcare-associated infections (HAIs) occur frequently in intensive care units (NICUs). The aim of this study was to analyze the results of surveillance of HAIs in a III level NICU in Naples, Italy during 2013-2017 and to compare with those obtained during 2006-2010. Methods:The surveillance included 1265 neonates of all birth weight (BW) classes with > 2 days NICU stay. Infections were defined using standard Centers for Disease Control and Prevention definitions adapted to neonatal pathology.Results: A total of 125 HAIs were registered during 2013-2017 with a frequency of 9.9% and an incidence density of 3.2 per 1000 patient days. HAIs occurred in all BW classes with a decreasing trend from the lowest to the highest BW classes (p = < 0.001). Central line-associated blood stream infection (CLABSI) was the most frequent infection (69.6%), followed by ventilator associated pneumonia (VAP) (20%), urinary tract infection (UTI) (8.8%) and necrotizing enterocolitis (NEC) (1.6%). Also, CLABSI and VAP incidence density decreased from lower to highest BW classes showing a significant trend (p = 0.007). Most frequent pathogens responsible for CLABSI were: Coagulase-negative staphylococci (CONS) (25.3%), Candida parapsilosis (21.8%), Pseudomonas aeruginosa (5.7), Escherichia coli and Klebsiella pneumoniae (6.8%). No microbiological diagnosis was achieved for 20.7% of CLABSI. Pseudomonas aeruginosa (28%), Stenotrophomonas maltophilia (20%), and CONS (20%) were the most frequent pathogens responsible for VAP. CLABSI incidence density showed no differences between 2006 and 2010 and 2013-2017, while VAP incidence density for the 751-100 g BW class was higher during 2006-2010 than during 2013-2017 (p = 0.006). A higher incidence of the CLABSI caused by Gram positive bacteria (p = 0.002) or by undetermined etiology (p = 0.01) was observed during 2013-2017 than during 2006-2010, while a significant lower incidence of VAP caused by Gram-negative bacteria was found during

Antibiotic susceptibility of environmental isolates of Legionella spp. might be useful for the early detection of resistance to antibiotics that directly impacts on mortality and length of hospital stay.

Background In Rare diseases patients. difficult in diagnosis can produce inappropriate pathways of care. A correct diagnosis took almost 5 years in Europe and 7.3-7.6 y in US. The directive 2011/24/EU provides a legal regulatory asset for the European Reference Networks (ERNs). ERNs are designed to connect health care providers and centers of expertise for gaining appropriate pathways of high-quality care and to support sponsorship in order to make healthcare closer to the patients. Federico II University actually has 9 confirmed ERNs. Methods We connected the patient related activities inside the ERNs and we planned a project-based network that creates harmonization of diagnostic tools and widespread diffusion of screening activity able to drive diagnostic enrichment. The Hospital Chief Office together with the Public Health Department acts as “Knowledge brokers” (KB) defined as connectors who may crisscross the hierarchical boundaries. We scheduled interventions into the ERNs and future improvements. Interventions areas have been represented in a conceptual map. Results Brokers into the network are attended to allow better merged innovation rate and sharing data. Improvements could be directed toward: 1) sharing data and communication, 2) diagnostic enrichment 3) hospital services networking into the path. Including this model in the regional pathways may build a common platform to support appropriate care in disease-endemic regions. The designed model finally aimed at define how humanization and networking of care can be measured as gain in efficiency along the overall path. Conclusions Network potential may overload a simply specific hub focused approach. The “criss cross” knowledge brokering (could be a strategy able to support clinical and diagnostic activities. To proceed over, in orphan disease handling, we may progress from approaches centered on florid cases toward a balanced screening design, able to guarantee a diagnostic enrichment for a rare condition. Key messages Implicit and formal Networking cam help rare disease handling. Sharing data and diagnostic enrichment are the main issues.

Background Atena project involved 5,062 women aged 30 to 69 years living in the area of Naples. The purpose of this study is to investigate the causes of those chronic diseases that have a major impact on the female population. As a part of the design (scheduled in 2002-2004). After 10 years, in 228 women, some biochemical measurements were performed. Methods This systematic review and meta-analysis biomarkers were evaluated in studies nested into the Atena cohort. Studies were searched using MEDLINE/PubMed. The search was performed by entering individually or in combination: Atena, Mediterranean woman, biomarkers. The preferred reporting of systematic reviews and meta-analysis (PRISMA) guidelines were used for the review. Studies selected for this review are conducted in the Atena project Cohort and reported the study of biomarkers. Disagreements on data extractions between the two investigators were solved by consensus. The extracted data were entered and analyzed using REVMAN software. The original articles were described using forest plot and table. Heterogeneity was computed by Cochran’s Q test. Results The search strategy retrieved 13 potential articles, 11 were screened as full text articles and 6 were included in the pooled estimates. Among the articles included, biomarkers chosen as predictors were Lipids, Hcrp, as prognostic where predictive of IMT; and cycle length and LPa as predictive of an augmented LDL cholesterol mean. According to the comparability of data presented, for the first comparison we selected 3 of the 5 studies that assed IMT, for the second we selected 2 of the three studies that analyzed for LDL mean. Results were shown into forrest plots. The pooled estimates verified the potential of biomarkers as predictor of IMT, the significance seemed lower for prediction of LDL cholesterol. Conclusions Both results, consistent with the multifactor profile of the CV risk, identify the impact of secondary prevention according to biochemical profiles. Key messages Biomarkers studied in nested cohort stufies have predictive potential. pooled estimates may identify the impact of secondary prevention according to biochemical profiles.