English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

The authors assessed the predictive capacity of 3 rule-based algorithms (Bergamo, Stanford University, Rega Institute) for HIV genotypic interpretation. A total of 1132 postgenotypic regimens in 533 patients were considered. The genotypic sensitivity score (GSS) was strongly associated (P &lt; .0001) with the virologic outcome (1 log HIV-RNA reduction). The 3 algorithms had a highly significant prediction efficiency. The Bergamo algorithm receiver-operating characteristic curve area under the curve (AUC) for the prediction of &gt;/=1 log HIV-RNA reduction was 0.753 (95% confidence interval, 0.725-0.781), testifying that the prediction was significantly different (P &lt; .0001) from simple chance. The AUCs obtained by the 2 other systems were similar (0.752 Stanford; 0.741 Rega). The predictive capacity of the algorithms was not influenced by the type of antiviral drugs used. The 3 considered rule-based algorithms for the interpretation of HIV genotypic resistance yield congruent results and may effectively predict the virologic outcome of rescue therapy. Their use may help clinicians in interpreting mutational patterns and in making therapeutic choices.

Prediction of Virologic Outcome of Salvage Antiretroviral Treatment by Different Systems for Interpreting Genotypic HIV Drug Resistance