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Identification of the main pathogens causing blood stream infections by real-time polymerase chain reaction of patients undergoing hematopoietic stem cells transplant


The morbidity and mortality of onco-hematologic diseases is related not only to the different forms of clinical presentation, but also to complications arising from immunosuppression, especially those caused by infections and toxic drugs used for treatment. The immune recovery after the transplant and chemotherapy guide the antibacterial and antiviral prophylaxis in this population based on the prevalence of the most important infectious agents. Approximately 60% of episodes of fever in patients with neutropenia are frequently correlated with documented Blood Stream Infection (ICS). The main objective of this study is to improve the identification of the main pathogens of blood stream infections with the use of the technique of Real Time Polymerase Chain Reaction (PCR) from peripheral blood samples collected in tubes with EDTA and vials of automated blood cultures positive detected by a automated system (Bactec).The genes that encode resistance to the following antibiotics will be also searched: blaIMP, blaSPM, blaVIM that encode the metallo-beta-lactamase (MBL) and produce resistance to carbapenes; the vanA and vanB genes that confer resistance to glycopeptides; the genes blaSHV, blaTEM, blaCTX that encode the beta-lactamase extended spectrum enzymes(ESBL) and cause resistance to cephalosporin; and the mecA gene that confers resistance to methicillin. The blood samples will be collected from patients with suspicion of blood stream infections submitted to hematopoietic stem cells transplant at Hospital São Paulo, UNIFESP. Based on previous data of the hematology service of the institution we calculated to evaluate 20 patients monthly, with 2 samples for patient (120 patients/6 months). The extraction of DNA from the samples will be done by the QIAamp DNA Mini Kit (Qiagen) for the EDTA vial, and the technique of Brazil for the vials of blood positives detected by the automated systems. The screening for detection of the main pathogens will be held by the technique of Real Time PCR system by SYBR Green, using the 16S rRNA for bacteria and region D2 for fungi. The TaqMan system will be utilized for identification of the microorganism by PCR Real Time PCR system. To determine the microorganism at the specie levels the product of 16S rRNA and 28S rRNA amplification will be automated sequenced. (AU)

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