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An electronic nose in the discrimination of patients with asthma and controls
Abstract
BACKGROUND Exhaled breath contains thousands of volatile organic compounds (VOCs) that could serve as biomarkers of lung disease. Electronic noses can distinguish VOC mixtures by pattern recognition. OBJECTIVE We hypothesized that an electronic nose can discriminate exhaled air of patients with asthma from healthy controls, and between patients with different disease severities. METHODS Ten young patients with mild asthma (25.1 +/- 5.9 years; FEV(1), 99.9 +/- 7.7% predicted), 10 young controls (26.8 +/- 6.4 years; FEV(1), 101.9 +/- 10.3), 10 older patients with severe asthma (49.5 +/- 12.0 years; FEV(1), 62.3 +/- 23.6), and 10 older controls (57.3 +/- 7.1 years; FEV(1), 108.3 +/- 14.7) joined a cross-sectional study with duplicate sampling of exhaled breath with an interval of 2 to 5 minutes. Subjects inspired VOC-filtered air by tidal breathing for 5 minutes, and a single expiratory vital capacity was collected into a Tedlar bag that was sampled by electronic nose (Cyranose 320) within 10 minutes. Smellprints were analyzed by linear discriminant analysis on principal component reduction. Cross-validation values (CVVs) were calculated. RESULTS Smellprints of patients with mild asthma were fully separated from young controls (CVV, 100%; Mahalanobis distance [M-distance], 5.32), and patients with severe asthma could be distinguished from old controls (CVV, 90%; M-distance, 2.77). Patients with mild and severe asthma could be less well discriminated (CVV, 65%; M-distance, 1.23), whereas the 2 control groups were indistinguishable (CVV, 50%; M-distance, 1.56). The duplicate samples replicated these results. CONCLUSION An electronic nose can discriminate exhaled breath of patients with asthma from controls but is less accurate in distinguishing asthma severities. CLINICAL IMPLICATION These findings warrant validation of electronic noses in diagnosing newly presented patients with asthma.
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Cites
Smoothing and Differentiation of Data by Simplified Least Squares Procedures.
Savitzky, A., & Golay, M. J. E. (1964) · Analytical Chemistry · doi:10.1021/ac60214a047 · Cited by 21,904
Miller, M. R., Hankinson, J., Brusasco, V., Burgos, F., Casaburi, R., Coates, A., Crapo, R., Enright, P., van der Grinten, C. P. M., Gustafsson, P., et al. (2005) · European Respiratory Journal · doi:10.1183/09031936.05.00034805 · Cited by 15,627
Wold, S., Esbensen, K., & Geladi, P. (1987) · Chemometrics and Intelligent Laboratory Systems · doi:10.1016/0169-7439(87)80084-9 · Cited by 11,606
A novel multigene family may encode odorant receptors: A molecular basis for odor recognition
Buck, L., & Axel, R. (1991) · Cell · doi:10.1016/0092-8674(91)90418-x · Cited by 4,987
(2005) · American Journal of Respiratory and Critical Care Medicine · doi:10.1164/rccm.200406-710st · Cited by 3,203
De Maesschalck, R., Jouan-Rimbaud, D., & Massart, D. L. (2000) · Chemometrics and Intelligent Laboratory Systems · doi:10.1016/s0169-7439(99)00047-7 · Cited by 2,325
The STARD Statement for Reporting Studies of Diagnostic Accuracy: Explanation and Elaboration
Bossuyt, P. M., Reitsma, J. B., Bruns, D. E., Gatsonis, C. A., Glasziou, P. P., Irwig, L. M., Moher, D., Rennie, D., de Vet, H. C. W., & Lijmer, J. G. (2003) · Annals of Internal Medicine · doi:10.7326/0003-4819-138-1-200301070-00012-w1 · Cited by 1,124
Standardized challenge testing with pharmacological, physical and sensitizing stimuli in adults
Sterk, P. J., Fabbri, L. M., Quanjer, P. H., Cockcroft, D. W., O'Byrne, P. M., Anderson, S. D., Juniper, E. F., & Malo, J.-L. (1993) · European Respiratory Journal · doi:10.1183/09041950.053s1693 · Cited by 1,049
Self-citationQuantitative Analysis of Urine Vapor and Breath by Gas-Liquid Partition Chromatography
Pauling, L., Robinson, A. B., Teranishi, R., & Cary, P. (1971) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.68.10.2374 · Cited by 1,025
Volatile organic compounds in breath as markers of lung cancer: a cross-sectional study
Phillips, M., Gleeson, K., Hughes, J. M. B., Greenberg, J., Cataneo, R. N., Baker, L., & McVay, W. P. (1999) · The Lancet · doi:10.1016/s0140-6736(98)07552-7 · Cited by 918
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Fens, N., Zwinderman, A. H., van der Schee, M. P., de Nijs, S. B., Dijkers, E., Roldaan, A. C., Cheung, D., Bel, E. H., & Sterk, P. J. (2009) · American Journal of Respiratory and Critical Care Medicine · doi:10.1164/rccm.200906-0939oc · Cited by 364
Self-citationBreath Analysis as a Potential and Non-Invasive Frontier in Disease Diagnosis: An Overview
Pereira, J., Porto-Figueira, P., Cavaco, C., Taunk, K., Rapole, S., Dhakne, R., Nagarajaram, H., & Câmara, J. (2015) · Metabolites · doi:10.3390/metabo5010003 · Cited by 301
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Sun, J., Lu, Y., He, L., Pang, J., Yang, F., & Liu, Y. (2020) · TrAC Trends in Analytical Chemistry · doi:10.1016/j.trac.2019.115754 · Cited by 299
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Ibrahim, W., Carr, L., Cordell, R., Wilde, M. J., Salman, D., Monks, P. S., Thomas, P., Brightling, C. E., Siddiqui, S., & Greening, N. J. (2021) · Thorax · doi:10.1136/thoraxjnl-2020-215667 · Cited by 115
The smell of lung disease: a review of the current status of electronic nose technology
van der Sar, I. G., Wijbenga, N., Nakshbandi, G., Aerts, J. G. J. V., Manintveld, O. C., Wijsenbeek, M. S., Hellemons, M. E., & Moor, C. C. (2021) · Respiratory Research · doi:10.1186/s12931-021-01835-4 · Cited by 87
Metadata
- Authors
- Dragonieri, S., Schot, R., Mertens, B. J. A., Le Cessie, S., Gauw, S. A., Spanevello, A., Resta, O., Willard, N. P., Vink, T. J., Rabe, K. F., Bel, E. H., & Sterk, P. J.
- Venue
- Journal of Allergy and Clinical Immunology
- Publisher
- Elsevier BV
- Published
- 2007-10
- Volume
- 120
- Issue
- 4
- Pages
- 856-862
- ISSN
- 0091-6749 (ISSN-L)
- OpenAlex
- W2074325744
- Cited by
- 451
- References
- 30
- FWCI
- 10.97
- Type
- journal article
- Language
- en
- Open access
- closed
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- Dragonieri, S., Schot, R., Mertens, B. J. A., Le Cessie, S., Gauw, S. A., Spanevello, A., Resta, O., Willard, N. P., Vink, T. J., Rabe, K. F., Bel, E. H., & Sterk, P. J. (2007). An electronic nose in the discrimination of patients with asthma and controls. Journal of Allergy and Clinical Immunology. https://doi.org/10.1016/j.jaci.2007.05.043
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