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Tracking longitudinal biomarkers in burn patients with sepsis and acute kidney injury: an unsupervised clustering approach
BACKGROUND: Sepsis is a grave medical disorder characterized by a systemic inflammatory response to infection. Furthermore, it is a leading cause of morbidity and mortality, especially in hospitalized patients. Acute kidney injury (AKI) is a common complication of sepsis and is associated with incre...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10464319/ https://www.ncbi.nlm.nih.gov/pubmed/37626427 http://dx.doi.org/10.1186/s40001-023-01268-3 |
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author | Kim, Myongjin Kym, Dohern Hur, Jun Park, Jongsoo Yoon, Jaechul Cho, Yong Suk Chun, Wook Yoon, Dogeon |
author_facet | Kim, Myongjin Kym, Dohern Hur, Jun Park, Jongsoo Yoon, Jaechul Cho, Yong Suk Chun, Wook Yoon, Dogeon |
author_sort | Kim, Myongjin |
collection | PubMed |
description | BACKGROUND: Sepsis is a grave medical disorder characterized by a systemic inflammatory response to infection. Furthermore, it is a leading cause of morbidity and mortality, especially in hospitalized patients. Acute kidney injury (AKI) is a common complication of sepsis and is associated with increased morbidity and mortality. Patients with burns are particularly vulnerable to developing sepsis and AKI due to the extensive tissue damage and immune suppression resulting from burn injury. In this study, unsupervised clustering algorithms were used to track longitudinal biomarkers in patients with burns and assess their impact on mortality. METHODS: This retrospective study included adult patients with burns aged ≥ 18 years, who were admitted to the burn intensive care unit of Hallym University and Hangang Sacred Heart Hospital between July 2010 and December 2021. The patients were divided into two subgroups: those with sepsis (538 patients) and those without sepsis (826 patients). The longitudinal biomarkers were grouped into three clusters using the k-means clustering algorithm. Each cluster was assigned a letter from A to C according to its mortality rate. RESULTS: The odds ratio (OR) of pH was 9.992 in the positive group and 31.745 in the negative group in cluster C. The OR for lactate dehydrogenase (LD) was 3.704 in the positive group and 6.631 in the negative group in cluster C. The OR for creatinine was 2.784 in the positive group and 8.796 in the negative group in cluster C. The OR for blood urea nitrogen (BUN) in the negative group was 0.348, indicating a negative predictor of mortality. Regarding the application of Continuous Renal Replacement Therapy (CRRT) and ventilation, ventilation was significant in both groups. In contrast, CRRT application was not significant in the sepsis-positive group. Furthermore, it was not selected as a variable in the negative group. CONCLUSIONS: The pH, LD, and creatinine were significant in both groups, while lactate and platelets were significant in the sepsis-positive group. In addition, albumin, glucose, and BUN were significant in the sepsis-negative group. Continuous renal replacement therapy was not significant in either group. However, the use of a ventilator was associated with poor prognosis. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s40001-023-01268-3. |
format | Online Article Text |
id | pubmed-10464319 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-104643192023-08-30 Tracking longitudinal biomarkers in burn patients with sepsis and acute kidney injury: an unsupervised clustering approach Kim, Myongjin Kym, Dohern Hur, Jun Park, Jongsoo Yoon, Jaechul Cho, Yong Suk Chun, Wook Yoon, Dogeon Eur J Med Res Research BACKGROUND: Sepsis is a grave medical disorder characterized by a systemic inflammatory response to infection. Furthermore, it is a leading cause of morbidity and mortality, especially in hospitalized patients. Acute kidney injury (AKI) is a common complication of sepsis and is associated with increased morbidity and mortality. Patients with burns are particularly vulnerable to developing sepsis and AKI due to the extensive tissue damage and immune suppression resulting from burn injury. In this study, unsupervised clustering algorithms were used to track longitudinal biomarkers in patients with burns and assess their impact on mortality. METHODS: This retrospective study included adult patients with burns aged ≥ 18 years, who were admitted to the burn intensive care unit of Hallym University and Hangang Sacred Heart Hospital between July 2010 and December 2021. The patients were divided into two subgroups: those with sepsis (538 patients) and those without sepsis (826 patients). The longitudinal biomarkers were grouped into three clusters using the k-means clustering algorithm. Each cluster was assigned a letter from A to C according to its mortality rate. RESULTS: The odds ratio (OR) of pH was 9.992 in the positive group and 31.745 in the negative group in cluster C. The OR for lactate dehydrogenase (LD) was 3.704 in the positive group and 6.631 in the negative group in cluster C. The OR for creatinine was 2.784 in the positive group and 8.796 in the negative group in cluster C. The OR for blood urea nitrogen (BUN) in the negative group was 0.348, indicating a negative predictor of mortality. Regarding the application of Continuous Renal Replacement Therapy (CRRT) and ventilation, ventilation was significant in both groups. In contrast, CRRT application was not significant in the sepsis-positive group. Furthermore, it was not selected as a variable in the negative group. CONCLUSIONS: The pH, LD, and creatinine were significant in both groups, while lactate and platelets were significant in the sepsis-positive group. In addition, albumin, glucose, and BUN were significant in the sepsis-negative group. Continuous renal replacement therapy was not significant in either group. However, the use of a ventilator was associated with poor prognosis. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s40001-023-01268-3. BioMed Central 2023-08-25 /pmc/articles/PMC10464319/ /pubmed/37626427 http://dx.doi.org/10.1186/s40001-023-01268-3 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Kim, Myongjin Kym, Dohern Hur, Jun Park, Jongsoo Yoon, Jaechul Cho, Yong Suk Chun, Wook Yoon, Dogeon Tracking longitudinal biomarkers in burn patients with sepsis and acute kidney injury: an unsupervised clustering approach |
title | Tracking longitudinal biomarkers in burn patients with sepsis and acute kidney injury: an unsupervised clustering approach |
title_full | Tracking longitudinal biomarkers in burn patients with sepsis and acute kidney injury: an unsupervised clustering approach |
title_fullStr | Tracking longitudinal biomarkers in burn patients with sepsis and acute kidney injury: an unsupervised clustering approach |
title_full_unstemmed | Tracking longitudinal biomarkers in burn patients with sepsis and acute kidney injury: an unsupervised clustering approach |
title_short | Tracking longitudinal biomarkers in burn patients with sepsis and acute kidney injury: an unsupervised clustering approach |
title_sort | tracking longitudinal biomarkers in burn patients with sepsis and acute kidney injury: an unsupervised clustering approach |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10464319/ https://www.ncbi.nlm.nih.gov/pubmed/37626427 http://dx.doi.org/10.1186/s40001-023-01268-3 |
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