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Predictors of severe sepsis-related in-hospital mortality based on a multicenter cohort study: The Focused Outcomes Research in Emergency Care in Acute Respiratory Distress Syndrome, Sepsis, and Trauma study
This study aimed to identify prognostic factors for severe sepsis-related in-hospital mortality using the structural equation model (SEM) analysis with statistical causality. Sepsis data from the Focused Outcomes Research in Emergency Care in Acute Respiratory Distress Syndrome, Sepsis, and Trauma s...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Lippincott Williams & Wilkins
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7909210/ https://www.ncbi.nlm.nih.gov/pubmed/33663106 http://dx.doi.org/10.1097/MD.0000000000024844 |
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author | Hagiwara, Akiyoshi Tanaka, Noriko Inaba, Yosuke Gando, Satoshi Shiraishi, Atsushi Saitoh, Daizoh Otomo, Yasuhiro Ikeda, Hiroto Ogura, Hiroshi Kushimoto, Shigeki Kotani, Joji Sakamoto, Yuichiro Shiino, Yasukazu Shiraishi, Shin-ichiro Takuma, Kiyotsugu Tarui, Takehiko Tsuruta, Ryosuke Nakada, Taka-aki Hifumi, Toru Yamakawa, Kazuma Takeyama, Naoshi Yamashita, Norio Abe, Toshikazu Ueyama, Masashi Okamoto, Kohji Sasaki, Junichi Masuno, Tomohiko Mayumi, Toshihiko Fujishima, Seitaro Umemura, Yutaka Fujimi, Satoshi |
author_facet | Hagiwara, Akiyoshi Tanaka, Noriko Inaba, Yosuke Gando, Satoshi Shiraishi, Atsushi Saitoh, Daizoh Otomo, Yasuhiro Ikeda, Hiroto Ogura, Hiroshi Kushimoto, Shigeki Kotani, Joji Sakamoto, Yuichiro Shiino, Yasukazu Shiraishi, Shin-ichiro Takuma, Kiyotsugu Tarui, Takehiko Tsuruta, Ryosuke Nakada, Taka-aki Hifumi, Toru Yamakawa, Kazuma Takeyama, Naoshi Yamashita, Norio Abe, Toshikazu Ueyama, Masashi Okamoto, Kohji Sasaki, Junichi Masuno, Tomohiko Mayumi, Toshihiko Fujishima, Seitaro Umemura, Yutaka Fujimi, Satoshi |
author_sort | Hagiwara, Akiyoshi |
collection | PubMed |
description | This study aimed to identify prognostic factors for severe sepsis-related in-hospital mortality using the structural equation model (SEM) analysis with statistical causality. Sepsis data from the Focused Outcomes Research in Emergency Care in Acute Respiratory Distress Syndrome, Sepsis, and Trauma study (FORECAST), a multicenter cohort study, was used. Forty seven observed variables from the database were used to construct 4 latent variables. SEM analysis was performed on these latent variables to analyze the statistical causality among these data. This study evaluated whether the variables had an effect on in-hospital mortality. Overall, 1148 patients were enrolled. The SEM analysis showed that the 72-hour physical condition was the strongest latent variable affecting mortality, followed by physical condition before treatment. Furthermore, the 72-hour physical condition and the physical condition before treatment strongly influenced the Sequential Organ Failure Assessment (SOFA) score with path coefficients of 0.954 and 0.845, respectively. The SOFA score was the strongest variable that affected mortality after the onset of severe sepsis. The score remains the most robust prognostic factor and can facilitate appropriate policy development on care. |
format | Online Article Text |
id | pubmed-7909210 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Lippincott Williams & Wilkins |
record_format | MEDLINE/PubMed |
spelling | pubmed-79092102021-03-01 Predictors of severe sepsis-related in-hospital mortality based on a multicenter cohort study: The Focused Outcomes Research in Emergency Care in Acute Respiratory Distress Syndrome, Sepsis, and Trauma study Hagiwara, Akiyoshi Tanaka, Noriko Inaba, Yosuke Gando, Satoshi Shiraishi, Atsushi Saitoh, Daizoh Otomo, Yasuhiro Ikeda, Hiroto Ogura, Hiroshi Kushimoto, Shigeki Kotani, Joji Sakamoto, Yuichiro Shiino, Yasukazu Shiraishi, Shin-ichiro Takuma, Kiyotsugu Tarui, Takehiko Tsuruta, Ryosuke Nakada, Taka-aki Hifumi, Toru Yamakawa, Kazuma Takeyama, Naoshi Yamashita, Norio Abe, Toshikazu Ueyama, Masashi Okamoto, Kohji Sasaki, Junichi Masuno, Tomohiko Mayumi, Toshihiko Fujishima, Seitaro Umemura, Yutaka Fujimi, Satoshi Medicine (Baltimore) 3900 This study aimed to identify prognostic factors for severe sepsis-related in-hospital mortality using the structural equation model (SEM) analysis with statistical causality. Sepsis data from the Focused Outcomes Research in Emergency Care in Acute Respiratory Distress Syndrome, Sepsis, and Trauma study (FORECAST), a multicenter cohort study, was used. Forty seven observed variables from the database were used to construct 4 latent variables. SEM analysis was performed on these latent variables to analyze the statistical causality among these data. This study evaluated whether the variables had an effect on in-hospital mortality. Overall, 1148 patients were enrolled. The SEM analysis showed that the 72-hour physical condition was the strongest latent variable affecting mortality, followed by physical condition before treatment. Furthermore, the 72-hour physical condition and the physical condition before treatment strongly influenced the Sequential Organ Failure Assessment (SOFA) score with path coefficients of 0.954 and 0.845, respectively. The SOFA score was the strongest variable that affected mortality after the onset of severe sepsis. The score remains the most robust prognostic factor and can facilitate appropriate policy development on care. Lippincott Williams & Wilkins 2021-02-26 /pmc/articles/PMC7909210/ /pubmed/33663106 http://dx.doi.org/10.1097/MD.0000000000024844 Text en Copyright © 2021 the Author(s). Published by Wolters Kluwer Health, Inc. http://creativecommons.org/licenses/by/4.0 This is an open access article distributed under the Creative Commons Attribution License 4.0 (CCBY), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. http://creativecommons.org/licenses/by/4.0 |
spellingShingle | 3900 Hagiwara, Akiyoshi Tanaka, Noriko Inaba, Yosuke Gando, Satoshi Shiraishi, Atsushi Saitoh, Daizoh Otomo, Yasuhiro Ikeda, Hiroto Ogura, Hiroshi Kushimoto, Shigeki Kotani, Joji Sakamoto, Yuichiro Shiino, Yasukazu Shiraishi, Shin-ichiro Takuma, Kiyotsugu Tarui, Takehiko Tsuruta, Ryosuke Nakada, Taka-aki Hifumi, Toru Yamakawa, Kazuma Takeyama, Naoshi Yamashita, Norio Abe, Toshikazu Ueyama, Masashi Okamoto, Kohji Sasaki, Junichi Masuno, Tomohiko Mayumi, Toshihiko Fujishima, Seitaro Umemura, Yutaka Fujimi, Satoshi Predictors of severe sepsis-related in-hospital mortality based on a multicenter cohort study: The Focused Outcomes Research in Emergency Care in Acute Respiratory Distress Syndrome, Sepsis, and Trauma study |
title | Predictors of severe sepsis-related in-hospital mortality based on a multicenter cohort study: The Focused Outcomes Research in Emergency Care in Acute Respiratory Distress Syndrome, Sepsis, and Trauma study |
title_full | Predictors of severe sepsis-related in-hospital mortality based on a multicenter cohort study: The Focused Outcomes Research in Emergency Care in Acute Respiratory Distress Syndrome, Sepsis, and Trauma study |
title_fullStr | Predictors of severe sepsis-related in-hospital mortality based on a multicenter cohort study: The Focused Outcomes Research in Emergency Care in Acute Respiratory Distress Syndrome, Sepsis, and Trauma study |
title_full_unstemmed | Predictors of severe sepsis-related in-hospital mortality based on a multicenter cohort study: The Focused Outcomes Research in Emergency Care in Acute Respiratory Distress Syndrome, Sepsis, and Trauma study |
title_short | Predictors of severe sepsis-related in-hospital mortality based on a multicenter cohort study: The Focused Outcomes Research in Emergency Care in Acute Respiratory Distress Syndrome, Sepsis, and Trauma study |
title_sort | predictors of severe sepsis-related in-hospital mortality based on a multicenter cohort study: the focused outcomes research in emergency care in acute respiratory distress syndrome, sepsis, and trauma study |
topic | 3900 |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7909210/ https://www.ncbi.nlm.nih.gov/pubmed/33663106 http://dx.doi.org/10.1097/MD.0000000000024844 |
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