National Institute of Respiratory Diseases and the Environment (INERAM), Asunción, Paraguay.
Department of Respiratory Diseases, Radboud University Medical Centre -TB Expert Centre Dekkerswald, Nijmegen-Groesbeek, The Netherlands.
PLoS One. 2023 Feb 7;18(2):e0276045. doi: 10.1371/journal.pone.0276045. eCollection 2023.
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.
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.
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).
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.
过去,电子鼻(eNose)设备在诊断或排除结核病(TB)方面表现出了很高的特异性和敏感性。本研究旨在评估其在 INERAM 就诊患者中的性能。
纳入年龄≥15 岁的患者。所有参与者均进行了病史、体格检查、胸部 X 线摄影(CRX)和痰标本的微生物学评估,以及 5 分钟的 eNose 呼吸测试。TB 诊断最好通过金标准建立,并与 eNose 的预测结果进行比较。进行单变量和多变量逻辑回归分析,以评估 eNose 分类结果错误的潜在危险因素。
共纳入了 107 例有 TB 症状和体征的患者,其中 91 例(85.0%)被诊断为 TB。盲法 eNose 预测的准确率为 50%;敏感性为 52.3%(95%CI:39.6-64.7%),特异性为 36.4%(95%CI:12.4-68.4%)。eNose 分类错误的危险因素包括年龄较大(多变量分析:OR 1.55,95%CI 1.10-2.18,p=0.012)和使用抗生素(多变量分析:OR 3.19,95%CI 1.06-9.66,p=0.040)。
在这项研究中,eNose 诊断三级转诊医院 TB 的准确率仅为 50%。抗生素的使用和年龄较大是对 eNose 诊断准确性产生负面影响的重要因素。因此,它的使用可能应仅限于在较简单医疗环境下高危社区进行筛查。