| Literature DB >> 33663106 |
Akiyoshi Hagiwara1, Noriko Tanaka2, Yosuke Inaba2, Satoshi Gando3,4, Atsushi Shiraishi5, Daizoh Saitoh6, Yasuhiro Otomo7, Hiroto Ikeda8, Hiroshi Ogura9, Shigeki Kushimoto10, Joji Kotani11, Yuichiro Sakamoto12, Yasukazu Shiino13, Shin-Ichiro Shiraishi14, Kiyotsugu Takuma15, Takehiko Tarui16, Ryosuke Tsuruta17, Taka-Aki Nakada18, Toru Hifumi19, Kazuma Yamakawa20, Naoshi Takeyama21, Norio Yamashita22, Toshikazu Abe23, Masashi Ueyama24, Kohji Okamoto25, Junichi Sasaki26, Tomohiko Masuno27, Toshihiko Mayumi28, Seitaro Fujishima29, Yutaka Umemura30, Satoshi Fujimi31.
Abstract
ABSTRACT: 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.Entities:
Mesh:
Year: 2021 PMID: 33663106 PMCID: PMC7909210 DOI: 10.1097/MD.0000000000024844
Source DB: PubMed Journal: Medicine (Baltimore) ISSN: 0025-7974 Impact factor: 1.817