Biomarkers for surgical sepsis. A review of foreign scientific and medical publications
- Authors: Sсherbak S.G.1,2, Sarana A.M.2,3, Vologzhanin D.A.1,2, Golota A.S.1, Rud’ A.A.4, Kamilova T.A.1
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Affiliations:
- Saint Petersburg City Hospital No 40 of Kurortny District
- Saint Petersburg State University
- Health Committee of Saint Petersburg
- Kirov Military medical academy
- Issue: Vol 14, No 2 (2023)
- Pages: 66-78
- Section: Reviews
- URL: https://journals.rcsi.science/clinpractice/article/view/142793
- DOI: https://doi.org/10.17816/clinpract346695
- ID: 142793
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Abstract
Sepsis is an unregulated host response to infection resulting in life-threatening organ dysfunction. As one of the most catastrophic surgical complications, sepsis remains a major public health problem worldwide, with increasing incidence despite sterile preoperative prophylaxis and administration of antibiotics. Sepsis mortality has remained unchanged for over a decade, and early recognition continues to be the most crucial factor in survival outcome. Early and accurate diagnosis of infection and organ dysfunction remains problematic, as evidenced by numerous interventional trials that have not resulted in improved outcomes. These failures are partly because of the belated intervention, when the patient developed multiple-organ failure and the therapeutic window of opportunity closed. The success of immunomodulatory and other therapeutic strategies, which is often achieved in preclinical models of sepsis, depends on their use in the early stages of sepsis development or even proactive action. Predicting the development of sepsis in surgical patients using laboratory analysis of plasma may be useful for doctors in the intensive care unit and resuscitation. Significant efforts are being made to develop biomarkers for the early stages of sepsis with high sensitivity and specificity. For early and accurate diagnosis, effective treatment of sepsis requires a deep understanding of the pathogenetic mechanisms. Dysregulation of the patient’s response to infection leading to sepsis and septic shock is studied using ohmic approaches: proteomics, transcriptomics, and metabolomics. Owing to the complexity and large volume of data sets, special data analysis tools, the so-called machine learning, become necessary.
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##article.viewOnOriginalSite##About the authors
Sergey G. Sсherbak
Saint Petersburg City Hospital No 40 of Kurortny District; Saint Petersburg State University
Email: b40@zdrav.spb.ru
ORCID iD: 0000-0001-5036-1259
SPIN-code: 1537-9822
Dr. Sci. (Med.), Professor
Russian Federation, Saint Petersburg; Saint PetersburgAndrey M. Sarana
Saint Petersburg State University; Health Committee of Saint Petersburg
Email: asarana@mail.ru
ORCID iD: 0000-0003-3198-8990
SPIN-code: 7922-2751
MD, PhD, Associate Professor
Russian Federation, Saint Petersburg; Saint PetersburgDmitry A. Vologzhanin
Saint Petersburg City Hospital No 40 of Kurortny District; Saint Petersburg State University
Email: volog@bk.ru
ORCID iD: 0000-0002-1176-794X
SPIN-code: 7922-7302
MD, Dr. Sci. (Med.)
Russian Federation, Saint Petersburg; Saint PetersburgAleksandr S. Golota
Saint Petersburg City Hospital No 40 of Kurortny District
Email: golotaa@yahoo.com
ORCID iD: 0000-0002-5632-3963
SPIN-code: 7234-7870
MD, PhD, Associate Professor
Russian Federation, Saint PetersburgAleksandr A. Rud’
Kirov Military medical academy
Email: wph04@mail.ru
SPIN-code: 4820-8345
Russian Federation, Saint Petersburg
Tatiana A. Kamilova
Saint Petersburg City Hospital No 40 of Kurortny District
Author for correspondence.
Email: kamilovaspb@mail.ru
ORCID iD: 0000-0001-6360-132X
SPIN-code: 2922-4404
Cand. Sci. (Biol.)
Russian Federation, Saint PetersburgReferences
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