The place of raltegravir in the clinical management of HIV-1 infection

2013 ◽  
Vol 10 (4) ◽  
pp. 427-438 ◽  
Author(s):  
Ruxandra Calin ◽  
Christine Katlama
Keyword(s):  
Clinical Management ◽  
Hiv 1

scholarly journals Clinical management of tuberculosis and HIV-1 co-infection

2010 ◽  
Vol 36 (6) ◽  
pp. 1460-1481 ◽  
Author(s):  
C. Schutz ◽  
G. Meintjes ◽  
F. Almajid ◽  
R. J. Wilkinson ◽  
A. Pozniak
Keyword(s):  
Clinical Management ◽  
Hiv 1

scholarly journals HIV-1 Tropism Testing and Clinical Management of CCR5 Antagonists: Quebec Review and Recommendations

2013 ◽  
Vol 24 (4) ◽  
pp. 202-208 ◽  
Author(s):  
Cécile Tremblay ◽  
Isabelle Hardy ◽  
Richard Lalonde ◽  
Benoit Trottier ◽  
Irina Tsarevsky ◽  
...  
Keyword(s):  
Clinical Trials ◽  
Clinical Management ◽  
Crucial Role ◽  
Alternative Strategies ◽  
Limited Access ◽  
Ccr5 Receptor ◽  
Treatment Naïve ◽  
Ccr5 Antagonists ◽  
Phenotypic Tests ◽  
Hiv 1

HIV-1 tropism assays play a crucial role in determining the response to CCR5 receptor antagonists. Initially, phenotypic tests were used, but limited access to these tests prompted the development of alternative strategies. Recently, genotyping tropism has been validated using a Canadian technology in clinical trials investigating the use of maraviroc in both experienced and treatment-naive patients. The present guidelines review the evidence supporting the use of genotypic assays and provide recommendations regarding tropism testing in daily clinical management.

scholarly journals sierra-local: A lightweight standalone application for secure HIV-1 drug resistance prediction

2018 ◽  
Author(s):  
Jasper C Ho ◽  
Garway T Ng ◽  
Mathias Renaud ◽  
Art FY Poon
Keyword(s):  
Clinical Management ◽  
Data Provenance ◽  
Genotypic Resistance ◽  
Web Based ◽  
Network Connection ◽  
Legal Obligations ◽  
Drug Resistance Prediction ◽  
Development And Validation ◽  
Hiv 1 ◽  
Interpretation Systems

AbstractGenotypic resistance interpretation systems for the prediction and interpretation of HIV-1 antiretroviral resistance are an important part of the clinical management of HIV-1 infection. Current interpretation systems are generally hosted on remote webservers that enable clinical laboratories to generate resistance predictions easily and quickly from patient HIV-1 sequences encoding the primary targets of modern antiretroviral therapy. However they also potentially compromise a health provider’s ethical, professional, and legal obligations to data security, patient information confidentiality, and data provenance. Furthermore, reliance on web-based algorithms makes the clinical management of HIV-1 dependent on a network connection. Here, we describe the development and validation of sierra-local, an open-source implementation of the Stanford HIVdb genotypic resistance interpretation system for local execution, which aims to resolve the ethical, legal, and infrastructure issues associated with remote computing. This package reproduces the HIV-1 resistance scoring by the web-based Stanford HIVdb algorithm with a high degree of concordance (99.997%) and a higher level of performance than current methods of accessing HIVdb programmatically.

scholarly journals Tropism testing in the clinical management of HIV-1 infection

2009 ◽  
Vol 4 (6) ◽  
pp. 481-487 ◽  
Author(s):  
Nina H Lin ◽  
Daniel R Kuritzkes
Keyword(s):  
Clinical Management ◽  
Hiv 1

scholarly journals European guidelines on the clinical management of HIV-1 tropism testing

2011 ◽  
Vol 11 (5) ◽  
pp. 394-407 ◽  
Author(s):  
LPR Vandekerckhove ◽  
AMJ Wensing ◽  
R Kaiser ◽  
F Brun-Vézinet ◽  
B Clotet ◽  
...  
Keyword(s):  
Clinical Management ◽  
European Guidelines ◽  
Hiv 1

HIV-1 dynamics after transient antiretroviral therapy: Implications for pathogenesis and clinical management

1997 ◽  
Vol 53 (3) ◽  
pp. 261-265 ◽  
Author(s):  
Andrew N. Phillips ◽  
Angela McLean ◽  
Margaret A. Johnson ◽  
Mervyn Tyrer ◽  
Vince Emery ◽  
...  
Keyword(s):  
Antiretroviral Therapy ◽  
Clinical Management ◽  
Hiv 1
Sign in / Sign up

Export Citation Format

Share Document