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Rapid Classification of COVID-19 Severity by ATR-FTIR Spectroscopy of Plasma Samples

傅里叶变换红外光谱 2019年冠状病毒病(COVID-19) 糖尿病 内科学 接收机工作特性 医学 急诊分诊台 化学 胃肠病学 疾病 医疗急救 传染病(医学专业) 物理 量子力学 内分泌学
作者
Arghya Banerjee,Abhiram Gokhale,Renuka Bankar,Viswanthram Palanivel,Akanksha Salkar,Harley Robinson,Jayanthi Shastri,Sachee Agrawal,Günter Härtel,Michelle M. Hill,Sanjeeva Srivastava
出处
期刊:Analytical Chemistry [American Chemical Society]
卷期号:93 (30): 10391-10396 被引量:37
标识
DOI:10.1021/acs.analchem.1c00596
摘要

The coronavirus disease 2019 (COVID-19) pandemic continues to ravage the world, with many hospitals overwhelmed by the large number of patients presenting during major outbreaks. A rapid triage for COVID-19 patient requiring hospitalization and intensive care is urgently needed. Age and comorbidities have been associated with a higher risk of severe COVID-19 but are not sufficient to triage patients. Here, we investigated the potential of attenuated total reflectance Fourier-transform infrared (ATR-FTIR) spectroscopy as a rapid blood test for classification of COVID-19 disease severity using a cohort of 160 COVID-19 patients. A simple plasma processing and ATR-FTIR data acquisition procedure was established using 75% ethanol for viral inactivation. Next, partial least-squares-discriminant analysis (PLS-DA) models were developed and tested using data from 130 and 30 patients, respectively. Addition of the ATR-FTIR spectra to the clinical parameters (age, sex, diabetes mellitus, and hypertension) increased the area under the ROC curve (C-statistics) for both the training and test data sets, from 69.3% (95% CI 59.8-78.9%) to 85.7% (78.6-92.8%) and 77.8% (61.3-94.4%) to 85.1% (71.3-98.8%), respectively. The independent test set achieved 69.2% specificity (42.4-87.3%) and 94.1% sensitivity (73.0-99.0%). Diabetes mellitus was the strongest predictor in the model, followed by FTIR regions 1020-1090 and 1588-1592 cm-1. In summary, this study demonstrates the potential of ATR-FTIR spectroscopy as a rapid, low-cost COVID-19 severity triage tool to facilitate COVID-19 patient management during an outbreak.

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