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Individualized Mechanical power-based ventilation strategy for acute respiratory failure formalized by finite mixture modeling and dynamic treatment regimen

BACKGROUND: Mechanical ventilation (MV) is the key to the successful treatment of acute respiratory failure (ARF) in the intensive care unit (ICU). The study aims to formalize the concept of individualized MV strategy with finite mixture modeling (FMM) and dynamic treatment regime (DTR). METHODS: AR...

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Autores principales: Hong, Yucai, Chen, Lin, Pan, Qing, Ge, Huiqing, Xing, Lifeng, Zhang, Zhongheng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8144670/
https://www.ncbi.nlm.nih.gov/pubmed/34041461
http://dx.doi.org/10.1016/j.eclinm.2021.100898
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author Hong, Yucai
Chen, Lin
Pan, Qing
Ge, Huiqing
Xing, Lifeng
Zhang, Zhongheng
author_facet Hong, Yucai
Chen, Lin
Pan, Qing
Ge, Huiqing
Xing, Lifeng
Zhang, Zhongheng
author_sort Hong, Yucai
collection PubMed
description BACKGROUND: Mechanical ventilation (MV) is the key to the successful treatment of acute respiratory failure (ARF) in the intensive care unit (ICU). The study aims to formalize the concept of individualized MV strategy with finite mixture modeling (FMM) and dynamic treatment regime (DTR). METHODS: ARF patients requiring MV for over 48 h from 2008 to 2019 were included. FMM was conducted to identify classes of ARF. Static and dynamic mechanical power (MP_static and MP_dynamic) and relevant clinical variables were calculated/collected from hours 0 to 48 at an interval of 8 h. [Formula: see text] was calculated as the difference between actual and optimal MP. FINDINGS: A total of 8768 patients were included for analysis with a mortality rate of 27%. FFM identified three classes of ARF, namely, the class 1 (baseline), class 2 (critical) and class 3 (refractory respiratory failure). The effect size of MP_static on mortality is the smallest in class 1 (HR for every 5 Joules/min increase: 1.29; 95% CI: 1.15 to 1.45; p < 0.001) and the largest in class 3 (HR for every 5 Joules/min increase: 1.83; 95% CI: 1.52 to 2.20; p < 0.001). INTERPRETATION: MP has differing therapeutic effects for subtypes of ARF. Optimal MP estimated by DTR model may help to improve survival outcome. FUNDING: The study was funded by Health Science and Technology Plan of Zhejiang Province (2021KY745), Key Research & Development project of Zhejiang Province (2021C03071) and Yilu "Gexin" - Fluid Therapy Research Fund Project (YLGX-ZZ-2,020,005).
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spelling pubmed-81446702021-05-25 Individualized Mechanical power-based ventilation strategy for acute respiratory failure formalized by finite mixture modeling and dynamic treatment regimen Hong, Yucai Chen, Lin Pan, Qing Ge, Huiqing Xing, Lifeng Zhang, Zhongheng EClinicalMedicine Research Paper BACKGROUND: Mechanical ventilation (MV) is the key to the successful treatment of acute respiratory failure (ARF) in the intensive care unit (ICU). The study aims to formalize the concept of individualized MV strategy with finite mixture modeling (FMM) and dynamic treatment regime (DTR). METHODS: ARF patients requiring MV for over 48 h from 2008 to 2019 were included. FMM was conducted to identify classes of ARF. Static and dynamic mechanical power (MP_static and MP_dynamic) and relevant clinical variables were calculated/collected from hours 0 to 48 at an interval of 8 h. [Formula: see text] was calculated as the difference between actual and optimal MP. FINDINGS: A total of 8768 patients were included for analysis with a mortality rate of 27%. FFM identified three classes of ARF, namely, the class 1 (baseline), class 2 (critical) and class 3 (refractory respiratory failure). The effect size of MP_static on mortality is the smallest in class 1 (HR for every 5 Joules/min increase: 1.29; 95% CI: 1.15 to 1.45; p < 0.001) and the largest in class 3 (HR for every 5 Joules/min increase: 1.83; 95% CI: 1.52 to 2.20; p < 0.001). INTERPRETATION: MP has differing therapeutic effects for subtypes of ARF. Optimal MP estimated by DTR model may help to improve survival outcome. FUNDING: The study was funded by Health Science and Technology Plan of Zhejiang Province (2021KY745), Key Research & Development project of Zhejiang Province (2021C03071) and Yilu "Gexin" - Fluid Therapy Research Fund Project (YLGX-ZZ-2,020,005). Elsevier 2021-05-24 /pmc/articles/PMC8144670/ /pubmed/34041461 http://dx.doi.org/10.1016/j.eclinm.2021.100898 Text en © 2021 The Author(s) https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Research Paper
Hong, Yucai
Chen, Lin
Pan, Qing
Ge, Huiqing
Xing, Lifeng
Zhang, Zhongheng
Individualized Mechanical power-based ventilation strategy for acute respiratory failure formalized by finite mixture modeling and dynamic treatment regimen
title Individualized Mechanical power-based ventilation strategy for acute respiratory failure formalized by finite mixture modeling and dynamic treatment regimen
title_full Individualized Mechanical power-based ventilation strategy for acute respiratory failure formalized by finite mixture modeling and dynamic treatment regimen
title_fullStr Individualized Mechanical power-based ventilation strategy for acute respiratory failure formalized by finite mixture modeling and dynamic treatment regimen
title_full_unstemmed Individualized Mechanical power-based ventilation strategy for acute respiratory failure formalized by finite mixture modeling and dynamic treatment regimen
title_short Individualized Mechanical power-based ventilation strategy for acute respiratory failure formalized by finite mixture modeling and dynamic treatment regimen
title_sort individualized mechanical power-based ventilation strategy for acute respiratory failure formalized by finite mixture modeling and dynamic treatment regimen
topic Research Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8144670/
https://www.ncbi.nlm.nih.gov/pubmed/34041461
http://dx.doi.org/10.1016/j.eclinm.2021.100898
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