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Sepsis subphenotyping based on organ dysfunction trajectory

BACKGROUND: Sepsis is a heterogeneous syndrome, and the identification of clinical subphenotypes is essential. Although organ dysfunction is a defining element of sepsis, subphenotypes of differential trajectory are not well studied. We sought to identify distinct Sequential Organ Failure Assessment...

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Autores principales: Xu, Zhenxing, Mao, Chengsheng, Su, Chang, Zhang, Hao, Siempos, Ilias, Torres, Lisa K., Pan, Di, Luo, Yuan, Schenck, Edward J., Wang, Fei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9250715/
https://www.ncbi.nlm.nih.gov/pubmed/35786445
http://dx.doi.org/10.1186/s13054-022-04071-4
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author Xu, Zhenxing
Mao, Chengsheng
Su, Chang
Zhang, Hao
Siempos, Ilias
Torres, Lisa K.
Pan, Di
Luo, Yuan
Schenck, Edward J.
Wang, Fei
author_facet Xu, Zhenxing
Mao, Chengsheng
Su, Chang
Zhang, Hao
Siempos, Ilias
Torres, Lisa K.
Pan, Di
Luo, Yuan
Schenck, Edward J.
Wang, Fei
author_sort Xu, Zhenxing
collection PubMed
description BACKGROUND: Sepsis is a heterogeneous syndrome, and the identification of clinical subphenotypes is essential. Although organ dysfunction is a defining element of sepsis, subphenotypes of differential trajectory are not well studied. We sought to identify distinct Sequential Organ Failure Assessment (SOFA) score trajectory-based subphenotypes in sepsis. METHODS: We created 72-h SOFA score trajectories in patients with sepsis from four diverse intensive care unit (ICU) cohorts. We then used dynamic time warping (DTW) to compute heterogeneous SOFA trajectory similarities and hierarchical agglomerative clustering (HAC) to identify trajectory-based subphenotypes. Patient characteristics were compared between subphenotypes and a random forest model was developed to predict subphenotype membership at 6 and 24 h after being admitted to the ICU. The model was tested on three validation cohorts. Sensitivity analyses were performed with alternative clustering methodologies. RESULTS: A total of 4678, 3665, 12,282, and 4804 unique sepsis patients were included in development and three validation cohorts, respectively. Four subphenotypes were identified in the development cohort: Rapidly Worsening (n = 612, 13.1%), Delayed Worsening (n = 960, 20.5%), Rapidly Improving (n = 1932, 41.3%), and Delayed Improving (n = 1174, 25.1%). Baseline characteristics, including the pattern of organ dysfunction, varied between subphenotypes. Rapidly Worsening was defined by a higher comorbidity burden, acidosis, and visceral organ dysfunction. Rapidly Improving was defined by vasopressor use without acidosis. Outcomes differed across the subphenotypes, Rapidly Worsening had the highest in-hospital mortality (28.3%, P-value < 0.001), despite a lower SOFA (mean: 4.5) at ICU admission compared to Rapidly Improving (mortality:5.5%, mean SOFA: 5.5). An overall prediction accuracy of 0.78 (95% CI, [0.77, 0.8]) was obtained at 6 h after ICU admission, which increased to 0.87 (95% CI, [0.86, 0.88]) at 24 h. Similar subphenotypes were replicated in three validation cohorts. The majority of patients with sepsis have an improving phenotype with a lower mortality risk; however, they make up over 20% of all deaths due to their larger numbers. CONCLUSIONS: Four novel, clinically-defined, trajectory-based sepsis subphenotypes were identified and validated. Identifying trajectory-based subphenotypes has immediate implications for the powering and predictive enrichment of clinical trials. Understanding the pathophysiology of these differential trajectories may reveal unanticipated therapeutic targets and identify more precise populations and endpoints for clinical trials. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13054-022-04071-4.
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spelling pubmed-92507152022-07-04 Sepsis subphenotyping based on organ dysfunction trajectory Xu, Zhenxing Mao, Chengsheng Su, Chang Zhang, Hao Siempos, Ilias Torres, Lisa K. Pan, Di Luo, Yuan Schenck, Edward J. Wang, Fei Crit Care Research BACKGROUND: Sepsis is a heterogeneous syndrome, and the identification of clinical subphenotypes is essential. Although organ dysfunction is a defining element of sepsis, subphenotypes of differential trajectory are not well studied. We sought to identify distinct Sequential Organ Failure Assessment (SOFA) score trajectory-based subphenotypes in sepsis. METHODS: We created 72-h SOFA score trajectories in patients with sepsis from four diverse intensive care unit (ICU) cohorts. We then used dynamic time warping (DTW) to compute heterogeneous SOFA trajectory similarities and hierarchical agglomerative clustering (HAC) to identify trajectory-based subphenotypes. Patient characteristics were compared between subphenotypes and a random forest model was developed to predict subphenotype membership at 6 and 24 h after being admitted to the ICU. The model was tested on three validation cohorts. Sensitivity analyses were performed with alternative clustering methodologies. RESULTS: A total of 4678, 3665, 12,282, and 4804 unique sepsis patients were included in development and three validation cohorts, respectively. Four subphenotypes were identified in the development cohort: Rapidly Worsening (n = 612, 13.1%), Delayed Worsening (n = 960, 20.5%), Rapidly Improving (n = 1932, 41.3%), and Delayed Improving (n = 1174, 25.1%). Baseline characteristics, including the pattern of organ dysfunction, varied between subphenotypes. Rapidly Worsening was defined by a higher comorbidity burden, acidosis, and visceral organ dysfunction. Rapidly Improving was defined by vasopressor use without acidosis. Outcomes differed across the subphenotypes, Rapidly Worsening had the highest in-hospital mortality (28.3%, P-value < 0.001), despite a lower SOFA (mean: 4.5) at ICU admission compared to Rapidly Improving (mortality:5.5%, mean SOFA: 5.5). An overall prediction accuracy of 0.78 (95% CI, [0.77, 0.8]) was obtained at 6 h after ICU admission, which increased to 0.87 (95% CI, [0.86, 0.88]) at 24 h. Similar subphenotypes were replicated in three validation cohorts. The majority of patients with sepsis have an improving phenotype with a lower mortality risk; however, they make up over 20% of all deaths due to their larger numbers. CONCLUSIONS: Four novel, clinically-defined, trajectory-based sepsis subphenotypes were identified and validated. Identifying trajectory-based subphenotypes has immediate implications for the powering and predictive enrichment of clinical trials. Understanding the pathophysiology of these differential trajectories may reveal unanticipated therapeutic targets and identify more precise populations and endpoints for clinical trials. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13054-022-04071-4. BioMed Central 2022-07-03 /pmc/articles/PMC9250715/ /pubmed/35786445 http://dx.doi.org/10.1186/s13054-022-04071-4 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis 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
Xu, Zhenxing
Mao, Chengsheng
Su, Chang
Zhang, Hao
Siempos, Ilias
Torres, Lisa K.
Pan, Di
Luo, Yuan
Schenck, Edward J.
Wang, Fei
Sepsis subphenotyping based on organ dysfunction trajectory
title Sepsis subphenotyping based on organ dysfunction trajectory
title_full Sepsis subphenotyping based on organ dysfunction trajectory
title_fullStr Sepsis subphenotyping based on organ dysfunction trajectory
title_full_unstemmed Sepsis subphenotyping based on organ dysfunction trajectory
title_short Sepsis subphenotyping based on organ dysfunction trajectory
title_sort sepsis subphenotyping based on organ dysfunction trajectory
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9250715/
https://www.ncbi.nlm.nih.gov/pubmed/35786445
http://dx.doi.org/10.1186/s13054-022-04071-4
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