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气相色谱-离子迁移谱法鉴别新型冠状病毒肺炎住院患者及预测预后的能力

Discriminatory Ability of Gas Chromatography-Ion Mobility Spectrometry to Identify Patients Hospitalized With COVID-19 and Predict Prognosis.

作者信息

Nazareth Joshua, Pan Daniel, Kim Jee Whang, Leach Jack, Brosnan James G, Ahmed Adam, Brodrick Emma, Bird Paul, Wicaksono Alfian, Daulton Emma, Tang Julian W, Williams Caroline, Haldar Pranabashis, Covington James A, Pareek Manish, Sahota Amandip

机构信息

Department of Respiratory Sciences, University of Leicester, Leicester, United Kingdom.

Department of Infectious Diseases and HIV Medicine, University Hospitals of Leicester NHS Trust, Leicester, United Kingdom.

出版信息

Open Forum Infect Dis. 2022 Oct 1;9(11):ofac509. doi: 10.1093/ofid/ofac509. eCollection 2022 Nov.

Abstract

BACKGROUND

Rapid diagnostic and prognostic tests for coronavirus disease (COVID-19) are urgently required. We aimed to evaluate the diagnostic and prognostic ability of breath analysis using gas chromatography-ion mobility spectrometry (GC-IMS) in hospitalized patients with COVID-19.

METHODS

Between February and May 2021, we took 1 breath sample for analysis using GC-IMS from participants who were admitted to the hospital for COVID-19, participants who were admitted to the hospital for other respiratory infections, and symptom-free controls, at the University Hospitals of Leicester NHS Trust, United Kingdom. Demographic, clinical, and radiological data, including requirement for continuous positive airway pressure (CPAP) ventilation as a marker for severe disease in the COVID-19 group, were collected.

RESULTS

A total of 113 participants were recruited into the study. Seventy-two (64%) were diagnosed with COVID-19, 20 (18%) were diagnosed with another respiratory infection, and 21 (19%) were healthy controls. Differentiation between participants with COVID-19 and those with other respiratory tract infections with GC-IMS was highly accurate (sensitivity/specificity, 0.80/0.88; area under the receiver operating characteristics curve [AUROC], 0.85; 95% CI, 0.74-0.96). GC-IMS was also moderately accurate at identifying those who subsequently required CPAP (sensitivity/specificity, 0.62/0.80; AUROC, 0.70; 95% CI, 0.53-0.87).

CONCLUSIONS

GC-IMS shows promise as both a diagnostic tool and a predictor of prognosis in hospitalized patients with COVID-19 and should be assessed further in larger studies.

摘要

背景

迫切需要针对冠状病毒病(COVID-19)的快速诊断和预后测试。我们旨在评估气相色谱-离子迁移谱法(GC-IMS)呼吸分析对COVID-19住院患者的诊断和预后评估能力。

方法

2021年2月至5月期间,在英国莱斯特大学医院国民保健服务信托基金,我们对因COVID-19入院的参与者、因其他呼吸道感染入院的参与者以及无症状对照者采集了1份呼吸样本,使用GC-IMS进行分析。收集了人口统计学、临床和放射学数据,包括COVID-19组中作为严重疾病标志物的持续气道正压通气(CPAP)需求。

结果

共有113名参与者纳入研究。72名(64%)被诊断为COVID-19,20名(18%)被诊断为其他呼吸道感染,21名(19%)为健康对照者。使用GC-IMS区分COVID-19患者和其他呼吸道感染患者的准确率很高(敏感性/特异性,0.80/0.88;受试者工作特征曲线下面积[AUROC],0.85;95%CI,0.74-0.96)。GC-IMS在识别随后需要CPAP的患者方面也具有中等准确性(敏感性/特异性,0.62/0.80;AUROC,0.70;95%CI,0.53-0.87)。

结论

GC-IMS作为COVID-19住院患者的诊断工具和预后预测指标显示出前景,应在更大规模的研究中进一步评估。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3ecd/9636851/c9c6e007612f/ofac509f1.jpg

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