Literature DB >> 20225942

Quantifying HIV for monitoring antiretroviral therapy in resource-poor settings.

Wendy S Stevens1, Lesley E Scott, Suzanne M Crowe.   

Abstract

There is increasing evidence to support the inability of CD4 cell count monitoring to predict virological failure in human immunodeficiency virus-infected individuals receiving antiretroviral therapy. There is renewed interest in improving access to viral load monitoring in resource-constrained regions to monitor adherence to treatment and to switch therapy. The field is rapidly changing as new technology platforms are made available for evaluation. This article presents an up to date summary of the assays available for viral load monitoring and suggests approaches for their implementation.

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Year:  2010        PMID: 20225942     DOI: 10.1086/650392

Source DB:  PubMed          Journal:  J Infect Dis        ISSN: 0022-1899            Impact factor:   5.226


  31 in total

1.  Heterosexual HIV-1 transmission after initiation of antiretroviral therapy: a prospective cohort analysis.

Authors:  Deborah Donnell; Jared M Baeten; James Kiarie; Katherine K Thomas; Wendy Stevens; Craig R Cohen; James McIntyre; Jairam R Lingappa; Connie Celum
Journal:  Lancet       Date:  2010-05-26       Impact factor: 79.321

2.  Perspectives on introduction and implementation of new point-of-care diagnostic tests.

Authors:  Kara M Palamountain; Jeff Baker; Elliot P Cowan; Shaffiq Essajee; Laura T Mazzola; Mutsumi Metzler; Marco Schito; Wendy S Stevens; Gloria J Young; Gonzalo J Domingo
Journal:  J Infect Dis       Date:  2012-03-07       Impact factor: 5.226

3.  Performance of NucliSens HIV-1 EasyQ Version 2.0 compared with six commercially available quantitative nucleic acid assays for detection of HIV-1 in China.

Authors:  Sihong Xu; Aijing Song; Jianhui Nie; Xiuhua Li; Youchun Wang
Journal:  Mol Diagn Ther       Date:  2010-10-01       Impact factor: 4.074

4.  2018 update to the HIV-TRePS system: the development of new computational models to predict HIV treatment outcomes, with or without a genotype, with enhanced usability for low-income settings.

Authors:  Andrew D Revell; Dechao Wang; Maria-Jesus Perez-Elias; Robin Wood; Dolphina Cogill; Hugo Tempelman; Raph L Hamers; Peter Reiss; Ard I van Sighem; Catherine A Rehm; Anton Pozniak; Julio S G Montaner; H Clifford Lane; Brendan A Larder
Journal:  J Antimicrob Chemother       Date:  2018-08-01       Impact factor: 5.790

5.  Computational models can predict response to HIV therapy without a genotype and may reduce treatment failure in different resource-limited settings.

Authors:  A D Revell; D Wang; R Wood; C Morrow; H Tempelman; R L Hamers; G Alvarez-Uria; A Streinu-Cercel; L Ene; A M J Wensing; F DeWolf; M Nelson; J S Montaner; H C Lane; B A Larder
Journal:  J Antimicrob Chemother       Date:  2013-03-13       Impact factor: 5.790

6.  An update to the HIV-TRePS system: the development and evaluation of new global and local computational models to predict HIV treatment outcomes, with or without a genotype.

Authors:  Andrew D Revell; Dechao Wang; Robin Wood; Carl Morrow; Hugo Tempelman; Raph L Hamers; Peter Reiss; Ard I van Sighem; Mark Nelson; Julio S G Montaner; H Clifford Lane; Brendan A Larder
Journal:  J Antimicrob Chemother       Date:  2016-06-20       Impact factor: 5.790

7.  Laboratory evaluation of the Liat HIV Quant (IQuum) whole-blood and plasma HIV-1 viral load assays for point-of-care testing in South Africa.

Authors:  Lesley Scott; Natasha Gous; Sergio Carmona; Wendy Stevens
Journal:  J Clin Microbiol       Date:  2015-03-04       Impact factor: 5.948

8.  Efficient on-chip isolation of HIV subtypes.

Authors:  ShuQi Wang; Matin Esfahani; Umut A Gurkan; Fatih Inci; Daniel R Kuritzkes; Utkan Demirci
Journal:  Lab Chip       Date:  2012-03-06       Impact factor: 6.799

Review 9.  Tackling HIV through robust diagnostics in the developing world: current status and future opportunities.

Authors:  Darash Desai; Grace Wu; Muhammad H Zaman
Journal:  Lab Chip       Date:  2010-12-01       Impact factor: 6.799

10.  Low-cost tools for diagnosing and monitoring HIV infection in low-resource settings.

Authors:  Grace Wu; Muhammad H Zaman
Journal:  Bull World Health Organ       Date:  2012-10-19       Impact factor: 9.408

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