Nosocomial infections in chronic critical illness – risk assessment, personalized diagnostics and treatment
G.G. Onishchenko, А.V. Grechko, А.N. Kuzovlev
Federal Research and Clinical Center of Intensive Care Medicine and Rehabilitology, 25 Petrovka Str., build. 2, Moscow, 107031, Russian Federation
The developmental trajectory of critical illness varies and is largely determined by genetic and immunological charac-teristics. This determines significant heterogeneity of critically ill patients and necessitates fundamental research in this area to develop algorithms for personalized diagnosis, treatment, and outcome prediction.
The aim of this study was to analyze the results of basic research conducted by the Federal Research and Clinical Center of Intensive Care Medicine on assessing the risk of nosocomial infections, their personalizing diagnosis, and treating in patients with chronic critical illness.
A review of the scientific literature from leading international and Russian databases was conducted. Databases used: PubMed/MEDLINE, Scopus, and eLibrary. Search period: 2015–2026. The RICD database developed by the Federal Research and Clinical Center of Intensive Care Medicine was used for data analysis.
Further development of intensive care medicine is impossible without a fundamental study of heterogeneity of patients in critical conditions. In this work, we analyzed scientific publications devoted to the concept of chronic critical illness, the etiological structure of pathogens of nosocomial respiratory tract infections in patients in chronic critical illness, genetic and immunological markers of the course and expected outcomes of critical conditions in various categories of patients, technology of personalized phage prophylaxis and phage therapy of nosocomial infections in patients in chronic critical illness. Our research work forms the basis for developing and implementing innovative algorithms for personalized diagnosis and treatment of nosocomial infections in critical conditions in clinical practice. These algorithms are based on understanding of the pathogenesis, genetic and immunological heterogeneity of chronic critical illness, personalized application of treatment and rehabilitation methods.
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