Multivariate Prognostic Model for Predicting the Outcome of Critically Ill Patients Using the Aromatic Metabolites Detected by Gas Chromatography-Mass Spectrometry
Abstract
:1. Introduction
2. Results
2.1. Characteristics of the Critically Ill Patients
2.2. Multivariate Classification Model Based on Eight Aromatic Metabolites
2.3. Univariate Classification Models
2.4. Multivariate Classification Model Based on Seven Aromatic Metabolites
2.5. ROC Analysis
3. Discussion
4. Materials and Methods
4.1. Reagents and Standards
4.2. Sample Preparation and GC-MS Analysis
4.3. Serum Samples
4.4. Data Processing
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
Sample Availability
References
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Amino Acid | Metabolites, Acids | ||||
---|---|---|---|---|---|
Phenylalanine | | | | ||
Benzoic | Phenylpropionic | Phenyllactic | |||
Tyrosine | | | | | |
p-Hydroxy-benzoic | p-Hydroxyphenylpropionic | p-Hydroxyphenyllactic (p-HPhLA) | p-Hydroxyphenylacetic | Homovanillic |
Parameters | Normal Values | Patients | 2-Tailed p | |
---|---|---|---|---|
Survivors (n = 44) | Non-Survivors (n = 35) | |||
APACHE II, points | 0 | 7 (5–11) n = 43 | 20 (16–26) n = 33 | <0.0001 |
SOFA, points | 0 | 2 (1–5) n = 43 | 10 (8–13) n = 33 | <0.0001 |
Glasgow Coma Scale, points | 15 | 15 (13–15) n = 44 | 15 (13–15) n = 33 | 0.578 |
Oxygenation PaO2/FiO2, mmHg | ≥400 | 305 (267–385) n = 31 | 282 (152–361) n = 31 | 0.141 |
Platelets, ×103/μL | ≥150 | 241 (175–313) n = 44 | 166 (89–208) n = 33 | 0.0052 |
Bilirubin, μmol/L | <20 | 12.5 (8.4–14.9) n = 42 | 19.0 (13.1–31.4) n = 28 | 0.0082 |
Creatinine, μmol/L | <110 | 80 (67–113) n = 43 | 191 (151–263) n = 31 | <0.0001 |
Vasopressors, % | No | 13.6% n = 44 | 91.4% n = 35 | Not available |
Aromatic Acid, μmol/L | LOD/ LOQ Values * | Healthy Volunteers (n = 52) | Patients | 2-Tailed p | |
---|---|---|---|---|---|
Survivors (n = 44) | Non-Survivors (n = 35) | ||||
Benzoic | **/0.7 | 1.3 (0.8–1.8) n (c > LOD) = 52 n (c > LOQ) = 44 | 1.9 (1.2–2.7) n (c > LOD) = 44 n (c > LOQ) = 40 | 2.5 (1.5–5.1) n (c > LOD) = 35 n (c > LOQ) = 31 | 0.0002 |
Phenylpropionic | 0.01/ 0.59 | <LOQ (<LOD–0.73) n (c > LOD) = 37 n (c > LOQ) = 19 | <LOD (<LOD–<LOQ) n (c > LOD) = 19 n (c > LOQ) = 2 | <LOD (<LOD–<LOQ) n (c > LOD) = 16 n (c > LOQ) = 2 | 0.0001 |
Phenyllactic | 0.4/ 0.5 | 0.6 (<LOD–0.8) n (c > LOD) = 34 n (c > LOQ) = 29 | 1.1 (<LOD–1.7) n (c > LOD) = 32 n (c > LOQ) = 32 | 4.0 (2.5–7.0) n (c > LOD) = 35 n (c > LOQ) = 35 | <0.0001 |
p-Hydroxybenzoic | 0.2/ 0.6 | <LOD (<LOD–<LOD) n (c > LOD) = 0 n (c > LOQ) = 0 | <LOD (<LOD–<LOD) n (c > LOD) = 4 n (c > LOQ) = 2 | <LOQ (<LOD–1.9) n (c > LOD) = 20 n (c > LOQ) = 16 | <0.0001 |
Homovanillic | 0.1/ 0.5 | <LOD (<LOD–<LOD) n (c > LOD) = 1 n (c > LOQ) = 0 | <LOD (<LOD–<LOD) n (c > LOD) = 9 n (c > LOQ) = 6 | 1.7 (<LOQ–6.3) n (c > LOD) = 26 n (c > LOQ) = 21 | <0.0001 |
p-Hydroxyphenylacetic | 0.1/ 0.6 | <LOQ (<LOD–<LOQ) n (c > LOD) = 28 n (c > LOQ) = 2 | <LOQ (<LOD–1.9) n (c > LOD) = 32 n (c > LOQ) = 21 | 9.6 (2.8–18.5) n (c > LOD) = 33 n (c > LOQ) = 29 | <0.0001 |
p-Hydroxyphenylpropionic | 0.1/ 0.5 | <LOD (<LOD–<LOD) n (c > LOD) = 0 n (c > LOQ) = 0 | <LOD (<LOD–<LOD) n (c > LOD) = 2 n (c > LOQ) = 1 | <LOD (<LOD–<LOQ) n (c > LOD) = 9 n (c > LOQ) = 5 | 0.0002 |
p-HPhLA | **/0.5 | 2.1 (1.6–2.6) n (c > LOD) = 52 n (c > LOQ) = 51 | 2.9 (2.2–3.4) n (c > LOD) = 43 n (c > LOQ) = 43 | 14.8 (6.5–32.6) n (c > LOD) = 35 n (c > LOQ) = 35 | <0.0001 |
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Pautova, A.K.; Samokhin, A.S.; Beloborodova, N.V.; Revelsky, A.I. Multivariate Prognostic Model for Predicting the Outcome of Critically Ill Patients Using the Aromatic Metabolites Detected by Gas Chromatography-Mass Spectrometry. Molecules 2022, 27, 4784. https://doi.org/10.3390/molecules27154784
Pautova AK, Samokhin AS, Beloborodova NV, Revelsky AI. Multivariate Prognostic Model for Predicting the Outcome of Critically Ill Patients Using the Aromatic Metabolites Detected by Gas Chromatography-Mass Spectrometry. Molecules. 2022; 27(15):4784. https://doi.org/10.3390/molecules27154784
Chicago/Turabian StylePautova, Alisa K., Andrey S. Samokhin, Natalia V. Beloborodova, and Alexander I. Revelsky. 2022. "Multivariate Prognostic Model for Predicting the Outcome of Critically Ill Patients Using the Aromatic Metabolites Detected by Gas Chromatography-Mass Spectrometry" Molecules 27, no. 15: 4784. https://doi.org/10.3390/molecules27154784