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Men have higher rates of attrition from antiretroviral therapy (ART) programs than women. In Khayelitsha, a high HIV prevalence area in South Africa, two public sector primary healthcare clinics offer services, including HIV testing and treatment, exclusively to men. We compared attrition from ART care among men initiating ART at these clinics with male attrition in six general primary healthcare clinics in Khayelitsha. We described baseline characteristics of patients initiating ART at the male and general clinics from 1 January 2014 to 31 March 2018. We used exposure propensity scores (generated based on baseline health and age) to match male clinic patients 1:1 to males at other clinics. The association between attrition (death or loss to follow-up, defined as no visits for nine months) and clinic type was estimated using Cox proportional hazards regression. Follow-up time began at ART initiation and ended at attrition, clinic transfer, or dataset closure. Before matching, patients from male clinics (n = 784) were younger than males from general clinics (n = 2726), median age: 31.2 vs 35.5 years. Those initiating at male clinics had higher median CD4 counts at ART initiation [Male Clinic 1: 329 (IQR 210-431), Male Clinic 2: 364 (IQR 260-536), general clinics 258 (IQR 145-398), cells/mm]. In the matched analysis (1451 person-years, 1568 patients) patients initiating ART at male clinics had lower attrition (HR 0.71; 95% CI 0.60-0.85). In separate analyses for each of the two male clinics, only the more established male clinic showed a protective effect. Male-only clinics reached younger, healthier men, and had lower ART attrition than general services. These findings support clinic-specific adaptations to create more male-friendly environments.
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http://dx.doi.org/10.1007/s10461-022-03772-9 | DOI Listing |
Int J STD AIDS
September 2025
Centre for Communicable Diseases Control and Research, Federal Medical Centre, Asaba, Nigeria.
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View Article and Find Full Text PDFBrief Bioinform
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School of Computer Science, Xi'an Polytechnic University, 710048, Xi'an, China.
Cancer, with its inherent heterogeneity, is commonly categorized into distinct subtypes based on unique traits, cellular origins, and molecular markers specific to each type. However, current studies primarily rely on complete multi-omics datasets for predicting cancer subtypes, often overlooking predictive performance in cases where some omics data may be missing and neglecting implicit relationships across multiple layers of omics data integration. This paper introduces Multi-Layer Matrix Factorization (MLMF), a novel approach for cancer subtyping that employs multi-omics data clustering.
View Article and Find Full Text PDFFront Immunol
September 2025
Institute of Human Virology, University of Maryland School of Medicine, Baltimore, MD, United States.
Innate-like T cells (ILT), including γδ T cells (Vδ2s), Natural Killer T cells (NKTs) and Mucosal-associated Invariant T cells (MAITs), integrate innate and adaptive immunity, playing important roles in homeostatic conditions as well as during infection or inflammation. ILT are present on both sides of the fetal-maternal interface, but our knowledge of their phenotypical and functional features in neonates is limited. Using spectral flow cytometry we characterized cord blood ILT in neonates born to healthy women and women living with HIV.
View Article and Find Full Text PDFHealthc Technol Lett
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Lab of Medical Physics and Digital Innovation, School of Medicine Aristotle University of Thessaloniki Thessaloniki Greece.
Healthcare systems across Europe and globally are increasingly challenged by the need to deliver high-quality, coordinated care for complex patient populations, such as those living with chronic heart failure (CHF). Many national healthcare policies consider the adoption and implementation of patient-centred and interoperable information communication technologies-enabled solutions offered in a single digital platform as a key facilitator towards the transition to integrated and coordinated care. Aiming to support CHF patients and to assist their management, in this paper, we present CareCardia, a modular digital solution designed to support the comprehensive management of CHF.
View Article and Find Full Text PDFJ Chem Inf Model
September 2025
Faculty of Pharmacy, University of Medicine and Pharmacy at Ho Chi Minh City, 41 Dinh Tien Hoang, District 1, Ho Chi Minh City 700000, Vietnam.
Molecular property prediction has become essential in accelerating advancements in drug discovery and materials science. Graph Neural Networks have recently demonstrated remarkable success in molecular representation learning; however, their broader adoption is impeded by two significant challenges: (1) data scarcity and constrained model generalization due to the expensive and time-consuming task of acquiring labeled data and (2) inadequate initial node and edge features that fail to incorporate comprehensive chemical domain knowledge, notably orbital information. To address these limitations, we introduce a Knowledge-Guided Graph (KGG) framework employing self-supervised learning to pretrain models using orbital-level features in order to mitigate reliance on extensive labeled data sets.
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