As antiretroviral therapy (ART) is scaled up in resource-limited countries, surveillance for HIV drug resistance (DR) is vital to ensure sustained effectiveness of first-line ART. We have developed and applied a broadly sensitive dried-blood-spot (DBS)-based genotyping assay for surveillance of HIV-1 DR in international settings. In 2005 and 2006, 171 DBS samples were collected under field conditions from newly diagnosed HIV-1-infected individuals from Malawi (n = 58), Tanzania (n = 60), and China (n =53). In addition, 30 DBS and 40 plasma specimens collected from ART patients in China and Cameroon, respectively, were also tested. Of the 171 DBS analyzed at the protease and RT regions, 149 (87.1%) could be genotyped, including 49 (81.7%) from Tanzania, 47 (88.7%) from China, and 53 (91.4%) from Malawi. Among the 70 ART patient samples analyzed, 100% (30/30) of the Chinese DBS and 90% (36/40) of the Cameroonian plasma specimens were genotyped, including 8 samples with a viral load of <400 copies/ml. The results of phylogenetic analyses indicated that the subtype, circulating recombinant form (CRF), and unique recombinant form (URF) distribution was as follows: 73 strains were subtype C (34%), 37 were subtype B (17.2%), 24 each were CRF01_AE or CRF02_AG (11.2% each), 22 were subtype A1 (10.2%), and 9 were unclassifiable (UC) (4.2%). The remaining samples were minor strains comprised of 6 that were CRF07_BC (2.8%), 5 that were CRF10_CD (2.3%), 3 each that were URF_A1C and CRF08_BC (1.4%), 2 each that were G, URF_BC, and URF_D/UC (0.9%), and 1 each that were subtype F1, subtype F2, and URF_A1D (0.5%). Our results indicate that this broadly sensitive genotyping assay can be used to genotype DBS collected from areas with diverse HIV-1 group M subtypes and CRFs. Thus, the assay is likely to become a useful screening tool in the global resistance surveillance and monitoring of HIV-1 where multiple subtypes and CRFs are found.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2937690 | PMC |
http://dx.doi.org/10.1128/JCM.00564-10 | DOI Listing |
BMC Med Inform Decis Mak
December 2024
Department of Respiration, Peking Union Medical College Hospital, No.1, Shuaifuyuan, Dongcheng District, Beijing, 100730, China.
Background: Inpatients with high risk of venous thromboembolism (VTE) usually face serious threats to their health and economic conditions. Many studies using machine learning (ML) models to predict VTE risk overlook the impact of class-imbalance problem due to the low incidence rate of VTE, resulting in inferior and unstable model performance, which hinders their ability to replace the Padua model, a widely used linear weighted model in clinic. Our study aims to develop a new VTE risk assessment model suitable for Chinese medical inpatients.
View Article and Find Full Text PDFAnn Clin Epidemiol
October 2024
Center of Medical Statistics, Minato-Ku, Tokyo, Japan.
Background: Large electronic databases have been widely used in recent years; however, they can be susceptible to bias due to incomplete information. To address this, validation studies have been conducted to assess the accuracy of disease diagnoses defined in databases. However, such studies may be constrained by potential misclassification in references and the interdependence between diagnoses from the same data source.
View Article and Find Full Text PDFPsychol Med
December 2024
Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Background: Motivated behaviors vary widely across individuals and are controlled by a range of environmental and intrinsic factors. However, due to a lack of objective measures, the role of intrinsic extrinsic control of motivation in psychiatric disorders remains poorly understood.
Methods: We developed a novel multi-factorial behavioral task that separates the distinct contributions of intrinsic extrinsic control, and determines their influence on motivation and outcome sensitivity in a range of contextual environments.
J Infect Dis
December 2024
The National Institute for Health Research Oxford Biomedical Research Centre, University of Oxford, Oxford, UK.
Background: Current guidelines recommend combining a macrolide with a β-lactam antibiotic for the empirical treatment of moderate-to-high severity community-acquired pneumonia (CAP); however macrolide use is associated with potential adverse events and antimicrobial resistance.
Methods: We analysed electronic health data from 8,872 adults in Oxfordshire, UK, hospitalised with CAP between 01-January-2016 and 19-March-2024, who received either amoxicillin or co-amoxiclav as initial treatment. We examined the effects of adjunctive macrolides on 30-day all-cause mortality, time to hospital discharge, and changes in Sequential Organ Failure Assessment (SOFA) score, using inverse probability treatment weighting to address confounding by baseline severity.
Front Digit Health
December 2024
Aesculab Medical Solutions, Black Horse Group Ltd., Debrecen, Hungary.
Introduction: The integration of AI into healthcare is widely anticipated to revolutionize medical diagnostics, enabling earlier, more accurate disease detection and personalized care.
Methods: In this study, we developed and validated an AI-assisted diagnostic support tool using only routinely ordered and broadly available blood tests to predict the presence of major chronic and acute diseases as well as rare disorders.
Results: Our model was tested on both retrospective and prospective datasets comprising over one million patients.
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!