This article aims to detect lung cavitations using lung ultrasound (LUS) in a cohort of patients with pulmonary tuberculosis (TB) and correlate the findings with chest computed tomography (CT) and chest X-ray (CXR) to obtain LUS diagnostic sensitivity. Patients with suspected TB were enrolled after being evaluated with CXR and chest CT. A blinded radiologist performed LUS within 3 days after admission at the Infectious Diseases Department. Finally, 82 patients were enrolled in this study. Bronchoalveolar lavage (BAL) confirmed TB in 58/82 (71%). Chest CT showed pulmonary cavitations in 38/82 (43.6%; 32 TB patients and 6 non-TB ones), LUS in 15/82 (18.3%; 11 TB patients and 4 non-TB ones) and CXR in 27/82 (33%; 23 TB patients and 4 non-TB ones). Twelve patients with multiple cavitations were detected with CT and only one with LUS. LUS sensitivity was 39.5%, specificity 100%, PPV 100% and NPV 65.7%. CXR sensitivity was 68.4% and specificity 97.8%. No false positive cases were found. LUS sensitivity was rather low, as many cavitated consolidations did not reach the pleural surface. Aerated cavitations could be detected with LUS with relative confidence, highlighting a thin air crescent sign towards the pleural surface within a hypoechoic area of consolidation, easily distinguishable from a dynamic or static air bronchogram.
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http://dx.doi.org/10.3390/diagnostics14050522 | DOI Listing |
Public Health
January 2025
Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Third Hospital of Shanxi Medical University, Tongji Shanxi Hospital, Taiyuan, 030032, China; Department of Allergy, Immunology & Rheumatology, Chung Shan Medical University Hospital, Taichung, Taiwan; Graduate Institute of Integrated Medicine, China Medical University, Taichung, Taiwan; Institute of Medicine/Department of Nursing, Chung Shan Medical University, Taichung, Taiwan. Electronic address:
Objectives: Limited data are available to assess breakthrough SARS-CoV-2 infections, medical utilization, and mortality in patients with tuberculosis (TB). The aim of this study was to examine the risk of COVID-19 and severe outcomes in patients with TB between January 2020 and March 2022.
Study Design: US electronic medical records were used to identify TB and non-TB patients who completed the primary series of vaccination and had no prior COVID-19.
PLoS One
January 2025
Centre for International Health, Department of Global Public Health and Primary Care, University of Bergen, Bergen, Norway.
Background: With the proportion of tuberculosis cases that are extrapulmonary tuberculosis (EPTB) increasing in recent years, understanding and addressing factors contributing to the prolonged time to diagnosis (TTD) of EPTB patients is vital.
Methods: We enrolled presumptive EPTB patients for a cohort study from 2018-2020 in Ujjain, India. Based on a structured questionnaire, the patients were interviewed for socio-demographic and clinical information, including previously visited health facilities (HF) for this illness.
Eye (Lond)
January 2025
Department of Ophthalmology, Erasmus University Medical Center, Rotterdam, The Netherlands.
Objective: To describe clinical features, treatment strategies and visual acuity changes of eyes with uveitic macular oedema (UMO) in ocular tuberculosis (OTB) patients from a non-TB-endemic country.
Methods: This retrospective study was conducted using a 10-year period registry of OTB patients diagnosed in Erasmus MC, Rotterdam. Longitudinal analysis of visual acuity trajectory in eyes with and without UMO was performed using linear mixed effect model.
Nanotheranostics
January 2025
Translational Research Laboratory, Department of Experimental Medicine and Biotechnology, Post Graduate Institute of Medical Education and Research (PGIMER), Chandigarh, India.
IJTLD Open
December 2024
Division of Infectious Disease and Tropical Medicine, Heidelberg University Hospital, Heidelberg, Germany.
Background: Computer-aided detection (CAD) tools for TB detection have the potential to enable screening programmes and reduce the diagnostic gap in settings where access to radiologists is limited. However, there are concerns that other common chest X-ray (CXR) abnormalities not due to TB may be missed.
Methods: We assessed the performance of three commercialised CAD tools (qXR, INSIGHT CXR and DrAID TB XR) to detect common non-TB abnormalities against readings with a standardised annotation guide by an expert radiologist.
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