Antimicrobial resistance is a global threat, which requires novel intervention strategies, for which priority pathogens and settings need to be determined. We evaluated pathogen-specific excess health burden of drug-resistant bloodstream infections (BSIs) in Europe. A systematic review and meta-analysis. MEDLINE, Embase, and grey literature for the period January 1990 to May 2022. Studies that reported burden data for six key drug-resistant pathogens: carbapenem-resistant (CR) Pseudomonas aeruginosa and Acinetobacter baumannii, third-generation cephalosporin or CR Escherichia coli and Klebsiella pneumoniae, methicillin-resistant Staphylococcus aureus (MRSA) and vancomycin-resistant Enterococcus faecium. Excess health outcomes compared with drug-susceptible BSIs or uninfected patients. For MRSA and third-generation cephalosporin E. coli and K. pneumoniae BSIs, five or more European studies were identified. For all others, the search was extended to high-income countries. Paediatric and adult patients diagnosed with drug-resistant BSI. Not applicable. An adapted version of the Joanna-Briggs Institute assessment tool. Random-effect models were used to pool pathogen-specific burden estimates. We screened 7154 titles, 1078 full-texts and found 56 studies on BSIs. Most studies compared outcomes of drug-resistant to drug-susceptible BSIs (46/56, 82.1%), and reported mortality (55/56 studies, 98.6%). The pooled crude estimate for excess all-cause mortality of drug-resistant versus drug-susceptible BSIs ranged from OR 1.31 (95% CI 1.03-1.68) for CR P. aeruginosa to OR 3.44 (95% CI 1.62-7.32) for CR K. pneumoniae. Pooled crude estimates comparing mortality to uninfected patients were available for vancomycin-resistant Enterococcus and MRSA BSIs (OR of 11.19 [95% CI 6.92-18.09] and OR 6.18 [95% CI 2.10-18.17], respectively). Drug-resistant BSIs are associated with increased mortality, with the magnitude of the effect influenced by pathogen type and comparator. Future research should address crucial knowledge gaps in pathogen- and infection-specific burdens to guide development of novel interventions.

To prioritize healthcare investments, ranking of infections caused by antibiotic-resistant bacteria should be based on accurate incidence data. We performed a systematic review to estimate frequency measures of antimicrobial resistance for six key bacteria causing bloodstream infections (BSI) in European countries. We searched PubMed, Web of Science, Embase databases, and the ECRAID-Base Epidemiological-Network platform. We included studies and surveillance systems assessing resistance-percentage, prevalence, or incidence-density of BSI because of carbapenem-resistant Pseudomonas aeruginosa, Acinetobacter baumannii, Klebsiella pneumoniae, and Escherichia coli, third-generation cephalosporins-resistant E. coli and K. pneumoniae, vancomycin-resistant Enterococcus faecium, and methicillin-resistant Staphylococcus aureus. Reviewers independently assessed published data and evaluated study quality with the modified Joanna Briggs Institute critical appraisal tool. Pooled estimates were determined using random effects meta-analysis. Consistency of data was assessed using random effects meta-regression (Wald test, p > 0.05). We identified 271 studies and 52 surveillance systems from 32 European countries. Forty-five studies (16%) reported on BSI, including 180 frequency measures most commonly as resistance-percentage (88, 48.9%). Among 309 frequency measures extracted from 24 (46%) surveillance systems, 278 (89%) were resistance-percentages. Frequency measures of methicillin-resistant S. aureus and vancomycin-resistant E. faecium BSI were more frequently reported from Southern Europe and Western Europe (80%), whereas carbapenem-resistant P. aeruginosa BSI from Northern Europe and Western Europe (88%). Highest resistance-percentages were detected for carbapenem-resistant A. baumannii (66% in Central Eastern Europe) and carbapenem-resistant K. pneumoniae (62.8% in Southern Europe). Pooled estimates showed lower resistance-percentages in community versus healthcare-associated infections and in children versus adults. Estimates from studies and surveillance systems were mostly consistent among European regions. The included data was of medium quality. Pathogen-specific frequency measures of antimicrobial resistance in BSI are insufficient to inform antibiotic stewardship and research and development strategies. Improving data collection and standardization of frequency measures is urgently needed.

Quantifying the resource use and cost of antimicrobial resistance establishes the magnitude of the problem and drives action. Assessment of resource use and cost associated with infections with six key drug-resistant pathogens in Europe. A systematic review and Bayesian meta-analysis. MEDLINE® (Ovid), Embase (Ovid), Econlit databases, and grey literature for the period 1st January 1990 to 21st June 2022. Resource use and cost outcomes (including excess length of stay, overall costs and other excess in/outpatient costs) were compared between patients with defined antibiotic-resistant infections caused by carbapenem resistant (CR) Pseudomonas aeruginosa and Acinetobacter baumannii, CR or third generation cephalosporin Escherichia coli (3GCREC) and Klebsiella pneumoniae, methicillin resistant Staphylococcus aureus (MRSA) and vancomycin resistant Enterococcus faecium and patients with drug-susceptible or no infection. All patients diagnosed with drug-resistant bloodstream infections (BSIs). NA. An adapted version of the Joanna-Briggs Institute assessment tool, incorporating case-control, cohort, and economic assessment frameworks. Hierarchical Bayesian meta-analyses were used to assess pathogen-specific resource use estimates. Of 5,969 screened publications, 37 were included in the review. Data were sparse and heterogeneous. Most studies estimated attributable burden, comparing resistant and susceptible pathogens (32/37). Four studies analysed the excess cost of hospitalisation attributable to 3GCREC bloodstream infections (BSIs), ranging from -€ 2,465.50 to € 6,402.81. Eight studies presented adjusted excess length of hospital stay estimates for MRSA and 3GCREC BSIs (4 each) allowing for Bayesian hierarchical analysis, estimating means of 1.26 (95% credible interval (CrI): -0.72 - 4.17) and 1.78 (95% CrI: -0.02 - 3.38) days, respectively. Evidence on most cost and resource use outcomes and across most pathogen-resistance combinations was severely lacking. Given the importance of this evidence for rational policymaking, further research is urgently needed.

Background: Healthcare-associated infections are strictly related to healthcare practices. A head nurse stimulates and motivates nurses, boosts nurses’ job performance and satisfaction, and can influence adverse event development. Aim: To explore the relationship between healthcare-associated infections and head nurse leadership style. Methods: A systematic review was conducted. The search was conducted from 1973 until March 2022 on PubMed, Cochrane Library, Scopus, CINAHL, Web of Science, Embase, and APA PsycInfo databases. The review followed the Joanna Briggs Institute Manual for Evidence Synthesis and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses. A thematic synthesis and critical appraisal of the included studies have been conducted. Results: Eight articles were included in this review. Head nurses’ leadership, supported by the organization, can positively influence the job performance and job satisfaction of nurses by reducing infection rates associated with vascular access and urinary catheters. Discussion: Authentic and transformational nurse leadership styles can foster targeted interventions and improvements tailored to preventing and controlling healthcare-associated infections. Even if there is limited evidence, the results support that the occurrence of infections can be reduced by leadership strategies implemented by head nurses.

The increasing complexity in hospital waste management requires innovative solutions that integrate sustainability and regulatory compliance. This study proposes an AI-based decision tool to support the circular management of healthcare waste. The approach combines two key elements: (i) the systematic qualitative analysis of international, European, and national regulations, scientific literature, and best practices aimed at identifying strategic actions; (ii) the prioritization of these actions through machine learning, using a Random Forest classifier. We identified 55 actions, grouped into 13 thematic areas, and used them as input variables to assess their impact on regulatory compliance. The variable importance analysis allowed us to classify actions according to their strategic relevance, guiding the structure of the tool and its user interface. Validation, conducted on four simulated case studies, demonstrated the system’s ability to improve compliance monitoring, operational efficiency, and the implementation of circular economy and Zero-Waste strategies. The proposed model represents a scalable and evidence-based solution capable of supporting the ecological transition of healthcare facilities in line with EU directives and the Sustainable Development Goals.

Background: The effective management of Healthcare-Associated Infections (HAIs) relies on the implementation of good practice across the entire multidisciplinary team. The organizational context and the role of head nurses influence the team’s performance and behavior. Understanding how decision-making processes influence healthcare professionals’ behavior in the management of HAIs could help identify alternative interventions for reducing the risk of infection in healthcare organizations. This study aims to explore how the behaviors promoted and actions implemented by the head nurse can influence healthcare professionals’ adherence to Infection Prevention and Control (IPC) programs. Methods: A multi-center qualitative study will be conducted using a Grounded Theory approach. Observations will be conducted, followed by individual interviews and/or focus groups. A constructive and representative sample of healthcare professionals who care directly for patients will be enrolled in the study. The COnsolidated criteria for REporting Qualitative research (COREQ) checklist will be followed to ensure the quality of this study protocol. A multistep inductive process will be used to analyze the data. Conclusions: The study results will provide an understanding of how nurses perceive the influence of leadership and how they modify their behaviors and activities toward patients according to IPC programs. The study will identify barriers and facilitators to IPC compliance and suggest strategies to minimize negative patient outcomes, such as the development of an HAI.