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Risk stratification of patients with acute respiratory distress syndrome complicated with sepsis using lactate trajectories

BACKGROUND: No consensus has been reached on an optimal blood lactate evaluation system although several approaches have been reported in the literature in recent years. A group-based trajectory modeling (GBTM) method could better stratify patients with acute respiratory distress syndrome (ARDS) com...

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Autores principales: Zhang, Haoyue, Li, Ziping, Zheng, Weiqiang, Zhang, Linlin, Yang, Tianqi, Xie, Keliang, Yu, Yonghao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9451114/
https://www.ncbi.nlm.nih.gov/pubmed/36071432
http://dx.doi.org/10.1186/s12890-022-02132-6
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author Zhang, Haoyue
Li, Ziping
Zheng, Weiqiang
Zhang, Linlin
Yang, Tianqi
Xie, Keliang
Yu, Yonghao
author_facet Zhang, Haoyue
Li, Ziping
Zheng, Weiqiang
Zhang, Linlin
Yang, Tianqi
Xie, Keliang
Yu, Yonghao
author_sort Zhang, Haoyue
collection PubMed
description BACKGROUND: No consensus has been reached on an optimal blood lactate evaluation system although several approaches have been reported in the literature in recent years. A group-based trajectory modeling (GBTM) method could better stratify patients with acute respiratory distress syndrome (ARDS) complicated with sepsis in the intensive care unit (ICU). PATIENTS AND METHODS: 760 patients from the comprehensive ICU of Tianjin Medical University General Hospital with ARDS complicated with sepsis were eligible for analysis. Serial serum lactate levels were measured within 48 h of admission. In addition to the GBTM lactate groups, the initial lactate, peak lactate level, the area under the curve of serial lactate (lactate AUC), and lactate clearance were also considered for comparison. The short- and long-term outcomes were the 30- and 90-day mortality, respectively. RESULTS: Three lactate groups were identified based on GBTM, with group 3 exhibiting the worse short- [hazard ratio (HR) for 30-day mortality: 2.96, 95% confidence interval (CI) 1.79–4.87, P < 0.001] and long term (HR for 90-day mortality: 3.49, 95% CI 2.06–5.89, P < 0.001) outcomes followed by group 2 (HR for 30-day mortality: 2.05, 95% CI 1.48–2.84, P < 0.001 and HR for 90-day mortality: 1.99, 95% CI 1.48–2.67, P < 0.001). GBTM lactate groups exhibited significantly improved diagnostic performance of initial lactate + SOFA scores/APACHE II scores models. Based on the multivariable fractional polynomial interaction (MFPI) approach, GBTM lactate groups could better differentiate high-risk patients than the initial lactate groups in short- and long-term outcomes. CONCLUSIONS: To the best of our knowledge, this is the first report that GBTM-based serial blood lactate evaluations significantly improve the diagnostic capacity of traditional critical care evaluation systems and bring many advantages over previously documented lactate evaluation systems. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12890-022-02132-6.
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spelling pubmed-94511142022-09-07 Risk stratification of patients with acute respiratory distress syndrome complicated with sepsis using lactate trajectories Zhang, Haoyue Li, Ziping Zheng, Weiqiang Zhang, Linlin Yang, Tianqi Xie, Keliang Yu, Yonghao BMC Pulm Med Research BACKGROUND: No consensus has been reached on an optimal blood lactate evaluation system although several approaches have been reported in the literature in recent years. A group-based trajectory modeling (GBTM) method could better stratify patients with acute respiratory distress syndrome (ARDS) complicated with sepsis in the intensive care unit (ICU). PATIENTS AND METHODS: 760 patients from the comprehensive ICU of Tianjin Medical University General Hospital with ARDS complicated with sepsis were eligible for analysis. Serial serum lactate levels were measured within 48 h of admission. In addition to the GBTM lactate groups, the initial lactate, peak lactate level, the area under the curve of serial lactate (lactate AUC), and lactate clearance were also considered for comparison. The short- and long-term outcomes were the 30- and 90-day mortality, respectively. RESULTS: Three lactate groups were identified based on GBTM, with group 3 exhibiting the worse short- [hazard ratio (HR) for 30-day mortality: 2.96, 95% confidence interval (CI) 1.79–4.87, P < 0.001] and long term (HR for 90-day mortality: 3.49, 95% CI 2.06–5.89, P < 0.001) outcomes followed by group 2 (HR for 30-day mortality: 2.05, 95% CI 1.48–2.84, P < 0.001 and HR for 90-day mortality: 1.99, 95% CI 1.48–2.67, P < 0.001). GBTM lactate groups exhibited significantly improved diagnostic performance of initial lactate + SOFA scores/APACHE II scores models. Based on the multivariable fractional polynomial interaction (MFPI) approach, GBTM lactate groups could better differentiate high-risk patients than the initial lactate groups in short- and long-term outcomes. CONCLUSIONS: To the best of our knowledge, this is the first report that GBTM-based serial blood lactate evaluations significantly improve the diagnostic capacity of traditional critical care evaluation systems and bring many advantages over previously documented lactate evaluation systems. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12890-022-02132-6. BioMed Central 2022-09-07 /pmc/articles/PMC9451114/ /pubmed/36071432 http://dx.doi.org/10.1186/s12890-022-02132-6 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
Zhang, Haoyue
Li, Ziping
Zheng, Weiqiang
Zhang, Linlin
Yang, Tianqi
Xie, Keliang
Yu, Yonghao
Risk stratification of patients with acute respiratory distress syndrome complicated with sepsis using lactate trajectories
title Risk stratification of patients with acute respiratory distress syndrome complicated with sepsis using lactate trajectories
title_full Risk stratification of patients with acute respiratory distress syndrome complicated with sepsis using lactate trajectories
title_fullStr Risk stratification of patients with acute respiratory distress syndrome complicated with sepsis using lactate trajectories
title_full_unstemmed Risk stratification of patients with acute respiratory distress syndrome complicated with sepsis using lactate trajectories
title_short Risk stratification of patients with acute respiratory distress syndrome complicated with sepsis using lactate trajectories
title_sort risk stratification of patients with acute respiratory distress syndrome complicated with sepsis using lactate trajectories
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9451114/
https://www.ncbi.nlm.nih.gov/pubmed/36071432
http://dx.doi.org/10.1186/s12890-022-02132-6
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