Julius Matthias Weinrich1, Roland Diel2, Markus Sauer3, Frank Oliver Henes3, Karen Meywald-Walter4, Gerhard Adam3, Gerhard Schön5, Peter Bannas3. 1. Department of Diagnostic and Interventional Radiology and Nuclear Medicine, University Medical Center Hamburg-Eppendorf, Martinistraße 52, 20251, Hamburg, Germany. j.weinrich@uke.de. 2. Institute for Epidemiology, University Medical Hospital Schleswig-Holstein, Airway Research Center North (ARCN), Kiel, Germany. 3. Department of Diagnostic and Interventional Radiology and Nuclear Medicine, University Medical Center Hamburg-Eppendorf, Martinistraße 52, 20251, Hamburg, Germany. 4. Public Health Department Hamburg Central, Hamburg, Germany. 5. Department of Medical Biometry and Epidemiology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.
Abstract
OBJECTIVE: Our aim was to determine the prevalence of tuberculosis (TB), the number needed to screen (NNS), and the diagnostic accuracy of chest X-ray (CXR) screening to detect active pulmonary TB during the 2015 European refugee crisis. MATERIALS AND METHODS: We evaluated data of all refugees who underwent CXR screening in a single-centre of one German metropolitan area in 2015. We determined the prevalence of TB, NNS, and accuracy of CXR to detect active pulmonary TB. Reference method for active TB was the database of all definite TB cases registered at the Department of Public Health. RESULTS: A total of 17,487 immigrants underwent single-centre CXR screening in 2015; prevalence of definite pulmonary TB was 0.103%. The NNS for detecting one case of active pulmonary TB was 1749. CXR had a sensitivity of 55.6% [95% confidence interval (CI) 30.8-78.5%) and a specificity 98.3% (CI 98.1-98.5%) to reveal one case of active TB. CONCLUSION: Our single-centre study indicates that chest X-ray screening for TB during the 2015 European refugee crisis was of low yield due the low prevalence of TB and high number needed to screen, thus implicating the need for improved screening algorithms adapted to the overwhelming number of refugees. KEY POINTS: • Prevalence of pulmonary tuberculosis (TB) among refugees in 2015 was low (0.103%). • The number needed to screen to detect one case of active pulmonary TB was 1749. • Tuberculosis X-ray screening resulted in a low sensitivity and high specificity. • Tuberculosis X-ray screening during the European refugee crisis is of low yield. • Improved screening algorithms are needed due to the overwhelming the number of refugees.
OBJECTIVE: Our aim was to determine the prevalence of tuberculosis (TB), the number needed to screen (NNS), and the diagnostic accuracy of chest X-ray (CXR) screening to detect active pulmonary TB during the 2015 European refugee crisis. MATERIALS AND METHODS: We evaluated data of all refugees who underwent CXR screening in a single-centre of one German metropolitan area in 2015. We determined the prevalence of TB, NNS, and accuracy of CXR to detect active pulmonary TB. Reference method for active TB was the database of all definite TB cases registered at the Department of Public Health. RESULTS: A total of 17,487 immigrants underwent single-centre CXR screening in 2015; prevalence of definite pulmonary TB was 0.103%. The NNS for detecting one case of active pulmonary TB was 1749. CXR had a sensitivity of 55.6% [95% confidence interval (CI) 30.8-78.5%) and a specificity 98.3% (CI 98.1-98.5%) to reveal one case of active TB. CONCLUSION: Our single-centre study indicates that chest X-ray screening for TB during the 2015 European refugee crisis was of low yield due the low prevalence of TB and high number needed to screen, thus implicating the need for improved screening algorithms adapted to the overwhelming number of refugees. KEY POINTS: • Prevalence of pulmonary tuberculosis (TB) among refugees in 2015 was low (0.103%). • The number needed to screen to detect one case of active pulmonary TB was 1749. • Tuberculosis X-ray screening resulted in a low sensitivity and high specificity. • Tuberculosis X-ray screening during the European refugee crisis is of low yield. • Improved screening algorithms are needed due to the overwhelming the number of refugees.
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