| Title: | Medical diagnosis at the point-of-care by portable high-field asymmetric waveform ion mobility spectrometry: a systematic review and meta-analysis |
| Author(s): | Zhang JD; Baker MJ; Liu Z; Kabir KMM; Kolachalama VB; Yates DH; Donald WA; |
| Address: | "School of Chemistry, University of New South Wales, Sydney, Australia. Stats Central, University of New South Wales, Sydney, Australia. Section of Computational Biomedicine, Department of Medicine, Boston University School of Medicine, Boston, MA, USA; Department of Computer Science and Faculty of Computing and Data Sciences, Boston University, Boston, MA, United States of America. Department of Thoracic Medicine, St Vincent's Hospital and St Vincent's Clinical School, UNSW Sydney, Sydney, Australia" |
| ISSN/ISBN: | 1752-7163 (Electronic) 1752-7155 (Print) 1752-7155 (Linking) |
| Abstract: | "Non-invasive medical diagnosis by analysing volatile organic compounds (VOCs) at the point-of-care is becoming feasible owing to recent advances in portable instrumentation. A number of studies have assessed the performance of a state-of-the-art VOC analyser (micro-chip high-field asymmetric waveform ion mobility spectrometry, FAIMS) for medical diagnosis. However, a comprehensive meta-analysis is needed to investigate the overall diagnostic performance of these novel methods across different medical conditions. An electronic search was performed using the CAplus and MEDLINE database through the SciFinder platform. The review identified a total of 23 studies and 2312 individuals. Eighteen studies were used for meta-analysis. A pooled analysis found an overall sensitivity of 80% (95% CI, 74%-85%,I(2)= 62%), and specificity of 78% (95% CI, 70%-84%,I(2)= 80%), which corresponds to the overall diagnostic performance of micro-chip FAIMS across many different medical conditions. The diagnostic accuracy was particularly high for coeliac and inflammatory bowel disease (sensitivity and specificity from 74% to 97%). The overall diagnostic performance was similar across breath, urine, and faecal matrices with sparse logistic regression and random forests algorithms resulting in higher diagnostic accuracy. Sources of variability likely arise from differences in sample storage, sampling protocol, method of data analysis, type of disease, sample matrix, and potentially to clinical and disease factors. The results of this meta-analysis indicate that micro-chip FAIMS is a promising candidate for disease screening at the point-of-care, particularly for gastroenterology diseases. This review provides recommendations that should improve the techniques relevant to diagnostic accuracy of future VOC and point-of-care studies" |
| Keywords: | Breath Tests Humans *Ion Mobility Spectrometry Point-of-Care Systems Sensitivity and Specificity *Volatile Organic Compounds Faims VOC analysis disease diagnosis ion mobility machine learning point-of-care testing; |
| Notes: | "MedlineZhang, J Diana Baker, Merryn J Liu, Zhixin Kabir, K M Mohibul Kolachalama, Vijaya B Yates, Deborah H Donald, William A eng R01 HL159620/HL/NHLBI NIH HHS/ R21 CA253498/CA/NCI NIH HHS/ R43 DK134273/DK/NIDDK NIH HHS/ RF1 AG062109/AG/NIA NIH HHS/ Meta-Analysis Research Support, Non-U.S. Gov't Systematic Review England 2021/07/13 J Breath Res. 2021 Jul 28; 15(4):10.1088/1752-7163/ac135e. doi: 10.1088/1752-7163/ac135e" |
