Biomarkers for surgical sepsis. A review of foreign scientific and medical publications
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. Th...
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Format: | Article |
Language: | English |
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Eco-vector
2023-07-01
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Series: | Клиническая практика |
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Online Access: | https://journals.eco-vector.com/clinpractice/article/viewFile/346695/pdf |
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author | Sergey G. Sсherbak Andrey M. Sarana Dmitry A. Vologzhanin Aleksandr S. Golota Aleksandr A. Rud’ Tatiana A. Kamilova |
author_facet | Sergey G. Sсherbak Andrey M. Sarana Dmitry A. Vologzhanin Aleksandr S. Golota Aleksandr A. Rud’ Tatiana A. Kamilova |
author_sort | Sergey G. Sсherbak |
collection | DOAJ |
description | 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 patients 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. |
first_indexed | 2024-03-12T22:34:15Z |
format | Article |
id | doaj.art-1f7d3435dad245ec9837be11b6667c70 |
institution | Directory Open Access Journal |
issn | 2220-3095 2618-8627 |
language | English |
last_indexed | 2024-03-12T22:34:15Z |
publishDate | 2023-07-01 |
publisher | Eco-vector |
record_format | Article |
series | Клиническая практика |
spelling | doaj.art-1f7d3435dad245ec9837be11b6667c702023-07-21T13:11:49ZengEco-vectorКлиническая практика2220-30952618-86272023-07-01142667810.17816/clinpract34669578372Biomarkers for surgical sepsis. A review of foreign scientific and medical publicationsSergey G. Sсherbak0https://orcid.org/0000-0001-5036-1259Andrey M. Sarana1https://orcid.org/0000-0003-3198-8990Dmitry A. Vologzhanin2https://orcid.org/0000-0002-1176-794XAleksandr S. Golota3https://orcid.org/0000-0002-5632-3963Aleksandr A. Rud’4Tatiana A. Kamilova5https://orcid.org/0000-0001-6360-132XSaint Petersburg City Hospital No 40 of Kurortny DistrictSaint Petersburg State UniversitySaint Petersburg City Hospital No 40 of Kurortny DistrictSaint Petersburg City Hospital No 40 of Kurortny DistrictKirov Military medical academySaint Petersburg City Hospital No 40 of Kurortny Districtremained 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 patients 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.https://journals.eco-vector.com/clinpractice/article/viewFile/346695/pdfsurgical sepsisseptic shockinfectionorgan dysfunctionmultiple organ failurebiomarkerproteomicstranscriptomicsmetabolomicsmachine learning |
spellingShingle | Sergey G. Sсherbak Andrey M. Sarana Dmitry A. Vologzhanin Aleksandr S. Golota Aleksandr A. Rud’ Tatiana A. Kamilova Biomarkers for surgical sepsis. A review of foreign scientific and medical publications Клиническая практика surgical sepsis septic shock infection organ dysfunction multiple organ failure biomarker proteomics transcriptomics metabolomics machine learning |
title | Biomarkers for surgical sepsis. A review of foreign scientific and medical publications |
title_full | Biomarkers for surgical sepsis. A review of foreign scientific and medical publications |
title_fullStr | Biomarkers for surgical sepsis. A review of foreign scientific and medical publications |
title_full_unstemmed | Biomarkers for surgical sepsis. A review of foreign scientific and medical publications |
title_short | Biomarkers for surgical sepsis. A review of foreign scientific and medical publications |
title_sort | biomarkers for surgical sepsis a review of foreign scientific and medical publications |
topic | surgical sepsis septic shock infection organ dysfunction multiple organ failure biomarker proteomics transcriptomics metabolomics machine learning |
url | https://journals.eco-vector.com/clinpractice/article/viewFile/346695/pdf |
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