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Background: Development of a non-sputum test using readily-obtainable biospecimens remains a global priority for tuberculosis (TB) control. We quantified lipoarabinomannan (LAM) concentrations, a pathogen biomarker for Mycobacterium tuberculosis, in urine, plasma and serum for real-world diagnostic accuracy of pulmonary TB among people living with and without HIV.
Methods: We conducted a prospective diagnostic study among adults with TB symptoms in South Africa. We measured LAM concentrations in time-matched urine, plasma and serum with an electrochemiluminescence immunoassay using two capture antibodies (FIND 28 and S4-20). From the completed cohort, we randomly selected 210 participants (2 cases: 1 control) based on sensitivity estimates, and we compared diagnostic accuracy of LAM measurements against the microbiological reference standard.
Findings: Urine and blood specimens from 210 of 684 adults enrolled were tested for LAM. Among 138 TB-positive adults (41% female), median urine LAM was 137 pg/mL and 52 pg/mL by FIND 28 and S4-20, respectively. Average LAM concentrations were highest in HIV-positive participants with CD4+ T cells <200 cells/mm. Urine LAM by S4-20 achieved diagnostic sensitivity of 62% (95% CI: 53%-70%) and specificity of 99% (95% CI: 96%-100%). Plasma and serum LAM by FIND 28 showed similar sensitivity (70%, 95% CI: 62%-78%) and comparable specificities (90%, 95% CI: 82%-97%; 94%, 95% CI: 88%-99%). Diagnostic sensitivity of urine LAM by S4-20 was higher among participants without HIV (41%, 95% CI: 24%-61%) compared to HIV-positive participants with CD4 ≥200 cells/mm (20%, 95% CI: 8%-39%).
Interpretation: Detection of LAM was achievable in non-sputum specimens for pulmonary TB, but additional analyte concentration or signal amplification may be required to achieve diagnostic accuracy targets.
Funding: Bill and Melinda Gates Foundation.
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http://dx.doi.org/10.1016/j.ebiom.2024.105353 | DOI Listing |
JMIR Med Inform
September 2025
Departments of Radiology, The Third Affiliated Hospital, Sun Yat-Sen University, 600 Tianhe Road, Guangzhou, Guangdong, 510630, China, 86 18922109279, 86 20852523108.
Background: Despite the Coronary Artery Reporting and Data System (CAD-RADS) providing a standardized approach, radiologists continue to favor free-text reports. This preference creates significant challenges for data extraction and analysis in longitudinal studies, potentially limiting large-scale research and quality assessment initiatives.
Objective: To evaluate the ability of the generative pre-trained transformer (GPT)-4o model to convert real-world coronary computed tomography angiography (CCTA) free-text reports into structured data and automatically identify CAD-RADS categories and P categories.
JMIR Res Protoc
September 2025
Department of Urology, Faculty of Medicine, Universitas Indonesia - Cipto Mangunkusumo Hospital, Jakarta, Indonesia.
Background: Circumcision is a widely practiced procedure with cultural and medical significance. However, certain penile abnormalities-such as hypospadias or webbed penis-may contraindicate the procedure and require specialized care. In low-resource settings, limited access to pediatric urologists often leads to missed or delayed diagnoses.
View Article and Find Full Text PDFJ Craniofac Surg
September 2025
Department of Oral and Maxillofacial Surgery, University of Ulsan Hospital, University of Ulsan College of Medicine.
This study aimed to develop a deep-learning model for the automatic classification of mandibular fractures using panoramic radiographs. A pretrained convolutional neural network (CNN) was used to classify fractures based on a novel, clinically relevant classification system. The dataset comprised 800 panoramic radiographs obtained from patients with facial trauma.
View Article and Find Full Text PDFJMIR Cancer
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Cancer Patients Europe, Rue de l'Industrie 24, Brussels, 1000, Belgium.
Background: Breast cancer is the most common cancer among women and a leading cause of mortality in Europe. Early detection through screening reduces mortality, yet participation in mammography-based programs remains suboptimal due to discomfort, radiation exposure, and accessibility issues. Thermography, particularly when driven by artificial intelligence (AI), is being explored as a noninvasive, radiation-free alternative.
View Article and Find Full Text PDFJMIR Med Inform
September 2025
College of Medical Informatics, Chongqing Medical University, 1 Yixueyuan Road, Yuzhong District, Chongqing, 400016, China, 86 13500303273.
Background: Cirrhosis is a leading cause of noncancer deaths in gastrointestinal diseases, resulting in high hospitalization and readmission rates. Early identification of high-risk patients is vital for proactive interventions and improving health care outcomes. However, the quality and integrity of real-world electronic health records (EHRs) limit their utility in developing risk assessment tools.
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