The objective of this study was to determine and compare the antimicrobial resistance profiles of clinical Staphylococcus pseudintermedius (n = 90) and Staphylococcus aureus (n = 61) isolates from different animal species in Bosnia and Herzegovina. Among S. pseudintermedius isolates from dogs (n = 86), resistance to penicillin (87.2%) was most common followed by amoxicillin (76.7%) and amoxicillin/clavulanic acid (67.4%). A total of 25 isolates were found to be resistant to oxacillin of which 21 were mecA-positive and multidrug resistant (MDR). The most frequent MDR pattern was penicillins-lincosamides-cephalosporins-macrolides-fluoroquinolones. Among the 61 methicillin-susceptible S. pseudintermedius isolates, 18 were MDR (penicillins-lincosamides-macrolides). Most of S. aureus isolates were resistant to penicillin (50.8%), followed by amoxicillin (41%) and amoxicillin/clavulanic acid (31%). Resistance to cefoxitin was detected in only two isolates. All S. aureus isolates were mecA and mecC-negative. MDR was observed in six S. aureus isolates of which five were from cattle (penicillins-lincosamides-fluoroquinolones). Isolates from red foxes (Vulpes vulpes) were sensitive to most of the antimicrobials tested. The high number of methicillin-resistant S. pseudintermedius and MDR isolates in dogs exposed in this study underlines the urgent need for establishment of national antimicrobial resistance surveillance program in animals in the country, as well as for the surveillance of veterinary antimicrobial consumption.

This paper examines possibilities for improving the existing strategies of consistency management for highly-distributed transactional database in a hybrid cloud environment. With a detailed analysis of the existing consistency models for distributed database and standard strategies including Classic, Quorum and Tree Based Consistency (TBC), it is concluded that an improved advanced model of so-called visible adaptive consistency needs to be applied in a highly-distributed cloud environment, as necessary and sufficient degree of synchronization of all replicas. Along with the proposed model, research and development of an advanced novel strategy for consistency management Rose TBC (R-TBC) approach has been conducted, by improving standard TBC approach. Regarding implementation, a specific agglomerative Rose Tree Algorithm (RTA) has been developed, based on Bayesian hierarchical clustering and Graph Partitioning Algorithm - Multidimensional Data Clustering (GPA-MDC) intelligent partitioning of transactional Cloud Database Management System (CDBMS). The final result is constructed R-TBC model that changes in accordance with dynamic changes of entire heterogeneous CDBMS environment.

Department of Clinical Microbiology, Institute for Health and Food Safety Zenica, Fra Ivana Jukića 2, 72000 Zenica, Bosnia and Herzegovina Department of Epidemiology, Institute for Health and Food Safety Zenica, Fra Ivana Jukića 2, 72000 Zenica, Bosnia and Herzegovina Autoimmune Diseases Department, Vasculitis Research Unit, IDIBAPS, CELLEX 4B, Hospital Clinic Barcelona, Spain Department of Chemistry Diagnostics, Institute for Health and Food Safety Zenica, Fra Ivana Jukića 2, 72000 Zenica, Bosnia and Herzegovina Department for Epizootiology, Institute for Health and Food Safety Zenica, Fra Ivana Jukića 2, 72000 Zenica, Bosnia and Herzegovina

Background and Aims: This study aimed to understand the use of massive transfusion (MT) for gastrointestinal bleeding (GIB). Patients and Methods: We performed a retrospective analysis of patients admitted to our medical Intensive Care Unit (ICU) with GIB for the type of bleeding, quantity of blood products transfused, and risk of transfusion-related acute lung injury (TRALI) and death. MT was defined as transfusion of 10 or more units of red blood cell (RBC) within a 24-h period in a 1-unit RBC: 1-unit fresh frozen plasma: and 1-unit platelet ratio. TRALI was defined as development of acute lung injury (ALI), within 6 h of transfusion, with new bilateral pulmonary infiltrates, absence of circulatory overload, or other explanation for ALI. Results: In a 43-month interval, 169 patients were admitted to the ICU with GIB and received blood products, of whom 13 received MT. Ten patients developed TRALI, of whom 7 (70%) had received MT. MT was associated with an increased risk of TRALI (odds ratio [OR]: 17.9, 95% confidence interval [CI]: 2.9–111.2, P = 0.002) after adjusting for age, sex, body mass index, baseline vitals, and laboratory data. Death was predicted by MT (OR: 5.6, 95% CI: 1.6–19.7, P = 0.007), TRALI (OR: 2.3, 95% CI: 1.1–4.6, P = 0.02), and Acute Physiologic Chronic Health Evaluation II score (OR: 1.17 per unit increase, 95% CI: 1.09–1.26, P < 0.001) after adjusting for age and sex. Conclusions: MT for GIB is associated with an increased risk of TRALI and death. Prospective studies assessing the use of MT in this population are needed to understand and improve outcomes.