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Amplifying and Quantifying HIV-1 RNA in HIV Infected Individuals with Viral Loads Below the Limit of Detection by Standard Clinical Assays
Published on: September 26, 2011
HIV-2 Infection: Where Are We Today?
Nayana A Ingole1, Purva P Sarkate, Supriya M Paranjpe
1Department of Microbiology, Seth G. S. Medical College and KEM Hospital, Mumbai, Maharashtra, India.
Differentiating between Human Immunodeficiency Virus type 1 (HIV-1) and HIV type 2 (HIV-2) is crucial for effective treatment. This study found the current diagnostic algorithm has limitations in distinguishing HIV types, necessitating algorithm modification.
Area of Science:
- Medical Diagnostics
- Infectious Diseases
- Virology
Background:
- Antiretroviral therapy (ART) choices differ significantly between Human Immunodeficiency Virus type 1 (HIV-1) and HIV type 2 (HIV-2).
- Accurate differentiation between HIV-1 and HIV-2 is essential for appropriate patient management and treatment selection.
Purpose of the Study:
- To determine the prevalence of HIV-2 infection within the study center.
- To evaluate the effectiveness of the existing diagnostic algorithm in correctly identifying HIV types (HIV-1, HIV-2, or co-infection).
Main Methods:
- Retrospective analysis of HIV-infected patients over three years at a tertiary care teaching institute.
- Patients were classified as HIV-1, HIV-2, or HIV-1 and HIV-2 co-infected based on NACO/WHO HIV testing strategy III results.
- Immunoblotting at a National Reference Laboratory was used to resolve discordant results.
Main Results:
- Out of 66,708 tested patients, 5,238 (7.9%) were HIV positive.
- HIV-1 accounted for 7.62%, HIV-2 for 0.14%, and co-infection for 0.08%.
- The diagnostic algorithm failed to differentiate HIV types in 1.2% of cases.
Conclusions:
- The current diagnostic algorithms require modification to accurately diagnose and confirm HIV-2 infections, especially in regions with ongoing epidemics of both HIV-1 and HIV-2.
- Improved diagnostic strategies are needed to ensure correct identification of HIV types for optimal patient care.
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