Current state and novel approaches to the diagnosis of sepsis caused by Staphylococcus aureus

Abstract

Sepsis caused by Staphylococcus aureus sepsis remains one of the leading causes of mortality among infectious diseases and represents a serious challenge for modern clinical medicine. Methicillin-resistant strains of S. aureus (MRSA) are of particular concern due to their high virulence, antibiotic resistance, and ability to spread rapidly in healthcare settings, which significantly complicates treatment and worsens the disease prognosis. This study summarizes current scientific data regarding the diagnostic possibilities for septic conditions caused by S. aureus, with an emphasis on the advantages and limitations of traditional and emerging laboratory and molecular diagnostic methods. It has been established that blood culture, despite being considered the «gold standard» of diagnosis, demonstrates low sensitivity, requires a prolonged time to obtain results, and largely depends on prior antibiotic therapy, which may lead to false-negative results and delayed initiation of adequate treatment. Considerable attention is paid to the role of laboratory biomarkers of systemic inflammatory response, including C-reactive protein, interleukin-6, procalcitonin, and presepsin, which make it possible to assess inflammatory activity, disease severity, and prognosis. Presepsin has been identified as the most promising biomarker for early sepsis diagnosis, as its level closely correlates with the severity of the patient’s clinical condition, the risk of multiple organ failure, and mortality. Modern molecular genetic technologies, including polymerase chain reaction (PCR), multiplex PCR panels, MALDI-TOF mass spectrometry, and whole-genome sequencing, are analyzed as methods that provide rapid pathogen identification and detection of antibiotic resistance genes, particularly mecA and mecC, while also enabling optimization of antimicrobial therapy at the early stages of the disease. The prospects for the use of biosensor platforms, point-of-care rapid diagnostic methods, and artificial intelligence algorithms for early sepsis prediction, assessment of unfavorable outcomes, and clinical decision support are also highlighted. It has been shown that the integration of microbiological, molecular, and digital technologies is a key prerequisite for improving the effectiveness of early diagnosis, optimizing antimicrobial therapy, and reducing mortality in staphylococcal sepsis.