A Study on the Epidemiological-Molecular Role of Staphylococcus aureus Strains in the Development of Ventilator-Associated Pneumonia in a Tertiary Hospital in Brazil.
Mariana Fávero BonessoCarlos Magno Castelo Branco FortalezaRicardo de Souza CavalcanteMoises Teixeira SobrinhoCarlos Fernando RonchiLígia Maria AbraãoHwang-Soo JooMichael OttoMaria de Lourdes Ribeiro de Souza da CunhaPublished in: Antibiotics (Basel, Switzerland) (2023)
This study aimed to explore the molecular epidemiology of Staphylococcus aureus isolated from patients on mechanical ventilation and the participation of virulence factors in the development of ventilator-associated pneumonia (VAP). A prospective cohort study was conducted on patients under mechanical ventilation, with periodic visits for the collection of tracheal aspirates and clinical data. The S. aureus isolates were analyzed regarding resistance profile, virulence, expression of protein A and alpha-toxin using Western blot, clonal profile using PFGE, sequence type using MLST, and characterization and quantification of phenol-soluble modulins. Among the 270 patients in the study, 51 S. aureus strains were isolated from 47 patients. The incidence density of S. aureus and MRSA VAP was 2.35/1000 and 1.96/1000 ventilator days, respectively; of these, 45% (n = 5) were resistant to oxacillin, with 100% (n = 5) harboring SCC mec types II and IV. The most frequent among the tested virulence factors were ica A, hla , and hld . The clonal profile showed a predominance of sequence types originating from the community. Risk factors for VAP were the presence of solid tumors and the sea gene. In conclusion, patient-related risk factors, together with microbiological factors, are involved in the development of S. aureus VAP, which is caused by the patient's own strains.
Keyphrases
- staphylococcus aureus
- end stage renal disease
- mechanical ventilation
- escherichia coli
- risk factors
- newly diagnosed
- chronic kidney disease
- pseudomonas aeruginosa
- healthcare
- peritoneal dialysis
- biofilm formation
- prognostic factors
- poor prognosis
- machine learning
- patient reported outcomes
- antimicrobial resistance
- long non coding rna
- cystic fibrosis
- case report
- small molecule
- candida albicans
- transcription factor
- deep learning
- big data
- respiratory failure