Metabolic Fingerprinting for the Diagnosis of Clinically Similar Long COVID and Fibromyalgia Using a Portable FT-MIR Spectroscopic Combined with Chemometrics
Abstract
:1. Introduction
2. Materials and Methods
2.1. Patient Sample Recruitment and Sample Storage
2.2. Sample Preparation
2.3. Spectral Data Acquisition
2.4. Chemometrics Analysis
2.5. Spectra Deconvolution Analysis
3. Results
3.1. Clinical Characteristics of Subjects
3.2. IR Spectroscopy
4. Discussion
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Age | N(M/F) [%M/%F] | BMI | FIRST | SIQR | FIQR | BDI | |
---|---|---|---|---|---|---|---|
LC | 49.5 ± 14.59 | 50 (18/32) [36/64] | 29.47 ± 8.3 | 18/50 | 44.63 ± 21.4 | ||
FM | 44.9.0 ± 12.8 | 50 (0/50) [0/100] | 31.57 ± 8.0 | 49.52 ± 21.5 | 18.31 ± 9.9 | ||
HC | 45.8 ± 19.1 | 6(4/2) [67/33] | 25.3 ± 2.4 | 13.95 ± 27.0 | 0.5 ± 0.5 |
LC | Age | BMI | SIQR |
---|---|---|---|
Male | 51.8 ± 11.6 | 28.9 ± 4.8 | 41.1 ± 15.9 |
Female | 48.6 ± 16.0 | 29.6 ± 10.0 | 44.8 ± 23.0 |
p value | 0.232 | 0.389 | 0.301 |
Shapiro–Wilk normality test | p = 0.319 |
FIQR/SIQR | Age | BMI | |
---|---|---|---|
p value | 0.158 | 0.055 | 0.140 |
Medications a | Medications a | Medications a | ||||||
---|---|---|---|---|---|---|---|---|
Subject No. | LC | FM | Subject No. | LC | FM | Subject No. | LC | FM |
1 | 1, 3, 8, 10, 12 | 2, 4, 17, 18, 21 | 21 | 2, 7, 8, 10, 15 | 23, 26, 31 | 41 | 1 | 1 |
2 | 2, 5, 22 | 10, 26 | 22 | 2, 6, 13 | 4 | 42 | 2, 14, 15, 26 | 3, 18, 20, 21 |
3 | 8, 14, 23, 24 | 29 | 23 | 14, 17, 20, 24 | 2, 4, 26 | 43 | X | X |
4 | 7, 13, 25 | 1, 2, 10 | 24 | 7 | X | 44 | X | 4, 21 |
5 | 4, 26 | 3 | 25 | 2, 5, 18, 20, 22 | X | 45 | 2, 9, 14, 27, 30 | 4 |
6 | 13, 15, 18, 19, 27 | 1, 8, 12, 15, 21 | 26 | 1, 2, 13, 15, 26 | 4, 12 | 46 | 10, 13, 14 | 3, 4, 16 |
7 | 2, 10, 18, 21, 23 | X | 27 | X | 2, 4, 5, 16, 30 | 47 | 4, 15, 21 | 21, 26 |
8 | 9, 19, 23 | 18, 24 | 28 | 12, 13, 14, 20, 23 | X | 48 | 7, 9, 20 | 2, 4, 26, 29 |
9 | 14, 16, 29 | 2, 5, 18 | 29 | 19 | 1, 4 | 49 | X | 2, 4, 7, 10, 20 |
10 | 15 | 2, 29 | 30 | 10 | 1, 2, 21, 27 | 50 | 2 | X |
11 | 6 | 26, 29 | 31 | 1, 15 | 1, 5, 10 | |||
12 | 4, 15 | 2, 7, 15 | 32 | 8 | 1, 3 | |||
13 | 7, 13, 22 | 2, 4, 21 | 33 | 2, 9, 15, 20 | 1, 3, 18 | |||
14 | 2, 13, 18, 19, 20 | 15 | 34 | 2, 9, 16 | 4 | |||
15 | 7, 12, 14, 20 | 2, 18 | 35 | X | 4, 7, 14, 20 | |||
16 | 21, 26 | X | 36 | 2, 13, 18, 19 | 11 | |||
17 | X | 4 | 37 | 8, 10, 18, 22, 23 | 17 | |||
18 | 8, 19, 29 | 3, 7, 12, 19, 20, 21 | 38 | 15, 19, 20, 21, 23, 24 | 12, 13, 26 | |||
19 | 15 | 3 | 39 | X | 2, 12, 14 | |||
20 | 5, 23, 26, 27 | 4, 10 | 40 | 24 | 9 |
Wavenumber (cm−1) | Area (%) | Wavenumber (cm−1) | Area (%) | Wavenumber (cm−1) | Area (%) | Wavenumber (cm−1) | Area (%) | |
---|---|---|---|---|---|---|---|---|
FM | * 1565 a ± 3 # | 36.1 A ± 18.1 | 1588 b ± 4 | 38.2 A ± 15.6 | 1639 d ± 5 | 4.7 C ± 1.6 | 1670 f ± 2 | 21.3 D ± 7.5 |
LC | - | - | 1581 B ± 2 | 70.3 B ± 8.9 | 1635 e ± 7 | 9.9 C ± 9.2 | 1670 f ± 2 | 23.9 D ± 5.3 |
Figures of Merit | Calibration Set n = 80 Samples | Prediction Set n = 20 Samples |
---|---|---|
SECV/SEP | 0.10 | 0.18 |
R2 | 0.98 | 0.96 |
Sensitivity (%) | 100 | 100 |
Specificity (%) | 100 | 100 |
Accuracy (%) | 100 | 100 |
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Hackshaw, K.V.; Yao, S.; Bao, H.; de Lamo Castellvi, S.; Aziz, R.; Nuguri, S.M.; Yu, L.; Osuna-Diaz, M.M.; Brode, W.M.; Sebastian, K.R.; et al. Metabolic Fingerprinting for the Diagnosis of Clinically Similar Long COVID and Fibromyalgia Using a Portable FT-MIR Spectroscopic Combined with Chemometrics. Biomedicines 2023, 11, 2704. https://doi.org/10.3390/biomedicines11102704
Hackshaw KV, Yao S, Bao H, de Lamo Castellvi S, Aziz R, Nuguri SM, Yu L, Osuna-Diaz MM, Brode WM, Sebastian KR, et al. Metabolic Fingerprinting for the Diagnosis of Clinically Similar Long COVID and Fibromyalgia Using a Portable FT-MIR Spectroscopic Combined with Chemometrics. Biomedicines. 2023; 11(10):2704. https://doi.org/10.3390/biomedicines11102704
Chicago/Turabian StyleHackshaw, Kevin V., Siyu Yao, Haona Bao, Silvia de Lamo Castellvi, Rija Aziz, Shreya Madhav Nuguri, Lianbo Yu, Michelle M. Osuna-Diaz, W. Michael Brode, Katherine R. Sebastian, and et al. 2023. "Metabolic Fingerprinting for the Diagnosis of Clinically Similar Long COVID and Fibromyalgia Using a Portable FT-MIR Spectroscopic Combined with Chemometrics" Biomedicines 11, no. 10: 2704. https://doi.org/10.3390/biomedicines11102704