Multivariate Prognostic Model for Predicting the Outcome of Critically Ill Patients Using the Aromatic Metabolites Detected by Gas Chromatography-Mass Spectrometry

Multivariate Prognostic Model for Predicting the Outcome of Critically Ill Patients Using the Aromatic Metabolites Detected by Gas Chromatography-Mass Spectrometry

A number of aromatic metabolites of tyrosine and phenylalanine have been investigated as new perspective markers of infectious complications in the critically ill patients of intensive care units (ICUs). The goal of our research was to build a multivariate model for predicting the outcome of critica...

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Bibliographic Details
Main Authors: Alisa K. Pautova, Andrey S. Samokhin, Natalia V. Beloborodova, Alexander I. Revelsky
Format: Article
Language:English
Published: MDPI AG 2022-07-01
Series:Molecules
Subjects:
sepsis
SOFA
APACHE II
4-hydroxyphenyllactic acid
SIMCA
data analysis
Online Access:https://www.mdpi.com/1420-3049/27/15/4784

Internet

https://www.mdpi.com/1420-3049/27/15/4784

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