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Introduction. To end the tuberculosis (TB) epidemic, efficient diagnostic tools are needed. In a previous calibration study, a portable 'point of care' electronic nose device (Aeonose TM ) proved to be a promising tool in a hospital setting. We evaluated this technology to detect TB in an indigenous population in Paraguay.Methods. A total of 131 participants were enrolled. eNose results were compared with anamnesis, physical examinations, chest radiography and mycobacterial cultures in individuals with signs and symptoms compatible with TB. The eNose analysis was performed in two stages: first, the training with a combination of a previous study population plus 47 participants from the new cohort (total n = 153), and second, the 'blind prediction' of 84 participants.Results. 21% of all participants (n = 131) showed symptoms and/or chest radiography abnormalities suspicious of TB. No sputum samples resulted culture positive for Mycobacterium tuberculosis complex. Only one patient had a positive smell print analysis. In the training model, the specificity was 92% (95% confidence interval (CI): 85%-96%) and the negative predictive value (NPV) was 95%.In the blind prediction model, the specificity and the NPV were 99% (95% CI: 93%-99%) and 100%, respectively. Although the sensitivity and positive predictive value of the eNose could not be assessed in this cohort due to the small sample size, no active TB cases were found during a one year of follow-up period. Conclusion.The eNose showed promising specificity and negative predictive value and might therefore be developed as a rule-out test for TB in vulnerable populations.

Introduction An electronic nose (eNose) device has shown a high specificity and sensitivity to diagnose or rule out tuberculosis (TB) in the past. The aim of this study was to evaluate its performance in patients referred to INERAM. Methods Patients aged ≥15 years were included. A history, physical examination, chest radiography (CRX) and microbiological evaluation of a sputum sample were performed in all participants, as well as a 5-minute breath test with the eNose. TB diagnosis was preferably established by the gold standard and compared to the eNose predictions. Univariate and multivariate logistic regression analyses were performed to assess potential risk factors for erroneous classification results by the eNose. Results 107 participants with signs and symptoms of TB were enrolled of which 91 (85.0%) were diagnosed with TB. The blind eNose predictions resulted in an accuracy of 50%; a sensitivity of 52.3% (CI 95%: 39.6–64.7%) and a specificity of 36.4% (CI 95%: 12.4–68.4%). Risk factors for erroneous classifications by the eNose were older age (multivariate analysis: OR 1.55, 95% CI 1.10–2.18, p = 0.012) and antibiotic use (multivariate analysis: OR 3.19, 95% CI 1.06–9.66, p = 0.040). Conclusion In this study, the accuracy of the eNose to diagnose TB in a tertiary referral hospital was only 50%. The use of antibiotics and older age represent important factors negatively influencing the diagnostic accuracy of the eNose. Therefore, its use should probably be restricted to screening in high-risk communities in less complex healthcare settings.

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