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African Journal of Laboratory Medicine

On-line version ISSN 2225-2010
Print version ISSN 2225-2002

Abstract

AUDU, Rosemary A. et al. Potential for false-positive HIV test results using rapid HIV testing algorithms. Afr. J. Lab. Med. [online]. 2015, vol.4, n.1, pp.1-8. ISSN 2225-2010.  http://dx.doi.org/10.4102/ajlm.v4i1.178.

BACKGROUND: In order to scale up access to HIV counselling and testing in Nigeria, an HIV diagnostic algorithm based on rapid testing was adopted. However, there was the need to further evaluate the testing strategy in order to better assess its performance, because of the potential for false positivity OBJECTIVES: The objective of this study was to compare positive HIV test results obtained from the approved rapid testing algorithm with results from western blot tests performed on samples from the same patient METHODOLOGY: A retrospective review was conducted of HIV screening and confirmatory results for patients seen between 2007 and 2008. Rapid test and western blot results were extracted and compared for concordance. Discordant results were further reviewed using a combination of HIV-1 RNA viral load and CD4+ cell count test results and clinical presentation from medical records RESULTS: Analysis of 2228 western blot results showed that 98.3% (n = 2191) were positive for HIV-1, 0.4% (n = 8) were positive for HIV-2 and 0.3% (n = 7) were dual infections (positive for both HIV-1 and HIV-2); 0.6% (n = 13) were indeterminate and 0.4% (n = 9) were negative. Further investigation of the 13 indeterminate results showed nine to be HIV-1 positive and four to be HIV-negative, for a total of 13 negative results. The positive predictive value of the HIV counselling and testing algorithm was 99.4% CONCLUSION: Using the rapid testing algorithm alone, false positives were detected. Therefore, effective measures such as training and retraining of staff should be prioritised in order to minimise false-positive diagnoses and the associated potential for long-term psychological and financial impact on the patients

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