Infecções por enterobacteriaceae resistente aos carbapenêmicos em hospital de ensino: epidemiologia e caracterização molecular

Introduction: The production of KPC (Klebsiella pneumoniae carbapenemase) has become an important mechanism of carbapenem-resistance among Enterobacteriaceae strains. In Brazil, KPC is already widespread and its incidence has increased significantly, reducing treatment options. The “perfect storm” combination of the absence of new drug developmentand the emergence of multidrug-resistant strains resulted in the need for the use of older drugs, with greater toxicity, such as polymyxins. Aims: To determine the occurrence of carbapenemase-producing strains in carbapenem-resistant Enterobacteriaceae isolated from patients with nosocomial infection/colonization during September/2014 to August/2015, to determine the risk factors associated with 30-day- mortality and the impact of inappropriate therapy. Materials and Methods: We performed a case control study to assess the risk factors (comorbidities, invasive procedures and inappropriate antimicrobial therapy) associated with 30-day-mortality, considering the first episode of infection in 111 patients. The resistance genes blaKPC, blaIMP, blaVIM and blaNDM-1 were detected by polymerase chain reaction technique. Molecular typing of the strains involved in the outbreak was performed by pulsed field gel electrophoresis technique. The polymyxin resistance was confirmed by the microdilution broth method. Results: 188 episodes of carbapenem-resistant Enterobacteriaceae infections/colonizations were detected; of these, 122 strains were recovered from the hospital laboratory. The presence of blaKPC gene were confirmed in the majority (74.59%) of these isolates. It was not found the presence of blaIMP , blaVIM and blaNDM-1 genes. K. pneumoniae was the most frequent microorganism (77,13%), primarily responsible for urinary tract infections (21,38%) and infections from patients of the Intensive Care Unit (ICU) (61,38%). Multivariate statistical analysis showed as predictors independently associated with mortality: dialysis and bloodstream infection. The Kaplan-Meier curve showed a lower probability of survival in the group of patients receiving antibiotic therapy inappropriately. Antimicrobial use in adult ICU varied during the study period, but positive correlation between increased incidence of strains and the consumption was not observed. In May and July 2015, the occurrence rates of carbapenem-resistant Enterobacteriaceae KPC-producing per 1000 patient-days were higher than the control limit established, confirming two outbreaks, the first caused by colistin-susceptible KPC-producing K. pneumoniae isolates, with a polyclonal profile and the second by a dominant clone of colistin-resistant (≥ 32 μg/mL) KPC-producing K. pneumoniae. The cross transmission between patients became clear by the temporal and spatial relationships observed in the second outbreak, since some patients occupied the same bed, showing problems in hand hygiene adherence among healthcare workers and inadequate terminal disinfection of environment. The outbreak was contained when the ICU was closed to new admissions. Conclusions: The study showed an endemicity of K. pneumoniae KPC-producing in adult ICU, progressing to an epidemic monoclonal expansion, resulted by a very high antibiotic consumption of carbapenems and polymyxins and facilitated by failures in control measures the unit.

Utilização da transformada de wavelet para detecção de variações anormais de tensão em sistemas elétricos com geração distribuída

The increasing demand in electricity and decrease forecast, increasingly, of fossil fuel reserves, as well as increasing environmental concern in the use of these have generated a concern about the quality of electricity generation, making it well welcome new investments in generation through alternative, clean and renewable sources. Distributed generation is one of the main solutions for the independent and selfsufficient generating systems, such as the sugarcane industry. This sector has grown considerably, contributing expressively in the production of electricity to the distribution networks. Faced with this situation, one of the main objectives of this study is to propose the implementation of an algorithm to detect islanding disturbances in the electrical system, characterized by situations of under- or overvoltage. The algorithm should also commonly quantize the time that the system was operating in these conditions, to check the possible consequences that will be caused in the electric power system. In order to achieve this it used the technique of wavelet multiresolution analysis (AMR) for detecting the generated disorders. The data obtained can be processed so as to be used for a possible predictive maintenance in the protection equipment of electrical network, since they are prone to damage on prolonged operation under abnormal conditions of frequency and voltage.