As Cameroon scales up its national HIV/AIDS control program, evaluating the performance of commercially available tests for accurate and cost effective diagnostics becomes essential. A cross-sectional study assessed the performance of an HIV oral rapid test. A total of 1520 participants consented to participate in the study. After counselling, they were tested for HIV using the national algorithm followed by OraQuick. Results of the national algorithm were compared to those of OraQuick, for sensitivity, specificity, positive predictive and negative predictive values. 62% of participants were male, and 1% was reported HIV-positive following the national algorithm. The OraQuick test had 93% sensitivity, 99% specificity, 99.93% NPV and 90% PPV (95% CI, Kappa 0.965). Though more expensive (2-6x) compared to the national algorithm tests, oral mucosal transudate-based test demonstrated good performance. Therefore, it could be implemented in resource-constrained settings if subsidized and could increase participation since less invasive with no blood accident exposure.
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http://dx.doi.org/10.4314/ajid.v7i2.2 | DOI Listing |
AIDS
January 2025
Botswana Harvard Health Partnership, 1836 Northring Road, Gaborone, Botswana.
Objective: To evaluate the impact of ART duration and CD4 count on risk for high grade cervical dysplasia in women with HIV (WWH) compared to women without HIV in the treat-all era with integrase strand inhibitors (INSTIs).
Design: Prospective longitudinal cohort study in Botswana.
Methods: From February 2021 to August 2022, baseline HPV self-sampling was offered to women with and without HIV.
Updates Surg
January 2025
Department of Radiation Oncology, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, 330006, People's Republic of China.
Whether primary lesion surgery improves survival in patients with de novo metastatic breast cancer (dnMBC) is inconclusive. We aimed to establish a prognostic prediction model for patients with de novo metastatic breast invasive ductal carcinoma (dnMBIDC) based on machine learning algorithms and to investigate the value of primary site surgery. The data used in our study were obtained from the Surveillance, Epidemiology, and End Results database (SEER, 2010-2021) and the First Affiliated Hospital of Nanchang University (1st-NCUH, June 2013-June 2023).
View Article and Find Full Text PDFEur Radiol Exp
January 2025
Computational Clinical Imaging Group (CCIG), Champalimaud Research, Champalimaud Foundation, Lisbon, Portugal.
Good practices in artificial intelligence (AI) model validation are key for achieving trustworthy AI. Within the cancer imaging domain, attracting the attention of clinical and technical AI enthusiasts, this work discusses current gaps in AI validation strategies, examining existing practices that are common or variable across technical groups (TGs) and clinical groups (CGs). The work is based on a set of structured questions encompassing several AI validation topics, addressed to professionals working in AI for medical imaging.
View Article and Find Full Text PDFDiscov Oncol
January 2025
Department of Orthopedics, Shanghai Tenth People's Hospital, School of Medicine, Tongji University, Shanghai, 200072, China.
Sarcoma (SARC), a diverse group of stromal tumors arising from mesenchymal tissues, is often associated with a poor prognosis. Emerging evidence indicates that senescent cells within the tumor microenvironment (TME) significantly contribute to cancer progression and metastasis. Although the influence of senescence on SARC has been partially acknowledged, it has yet to be fully elucidated.
View Article and Find Full Text PDFNeuroradiology
January 2025
Department of Radiology, Jinling Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, 210002, Jiangsu, China.
Purpose: We aimed to validate a clinically available artificial intelligence (AI) model to assist general radiologists in the detection of intracranial aneurysm (IA) in a multi-reader multi-case (MRMC) study, and to explore its performance in routine clinical settings.
Methods: Two distinct cohorts of head CT angiography (CTA) data were assembled to validate an AI model. Cohort 1, comprising gold-standard consecutive CTA cases, was used in an MRMC study involving six board-certified general radiologists.
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