Literature DB >> 23033518

Rapid HIV testing using Determine™ HIV 1/2 antibody tests: is there a difference between the visual appearance of true- and false-positive tests?

R Sacks1, A Omodele-Lucien, N Whitbread, D Muir, A Smith.   

Abstract

HIV point-of-care tests (POCTs) give occasional false positive results, causing unnecessary patient anxiety. We aimed to elicit whether false- and true-positive POCTs differed visually. Seventeen false- and 17 true-positive serum samples were randomized into pairs, comprising one false- and one true-positive sample. Two independent readers identified each POCT as negative or positive and compared line strength between pairs. Six further readers graded line strength, 0-5, from POCT photographs. All true-positive samples were identified positive and 8/17 false-positive samples negative, on repeat testing of stored sera. Eight out of the 9 remaining false-positive tests were described as having weaker pigment uptake than their paired true-positive POCT. Mean grade of line strength was 4.2 in true- and 0.9 in false-positive samples, on photographic evaluation. These results suggest false-positive POCTs may differ visually from true-positive POCTs. If larger studies confirm these findings, we may be able to alleviate anxiety in low risk patients with faintly positive POCTs awaiting their confirmatory laboratory result, where the possibility of a false-positive result could be emphasized.

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Year:  2012        PMID: 23033518     DOI: 10.1258/ijsa.2012.011422

Source DB:  PubMed          Journal:  Int J STD AIDS        ISSN: 0956-4624            Impact factor:   1.359


  5 in total

1.  Discordant rapid HIV tests: lessons from a low-resource community.

Authors:  A A Adetunji; M A Kuti; R A Audu; S A Muyibi; M Imhansoloeva; O A Mosuro; E A Solanke; O M Akpa; A E Irabor; Mma Ladipo; B Berzins; K Robertson; A Ogunniyi; I F Adewole; B O Taiwo
Journal:  HIV Med       Date:  2017-07-31       Impact factor: 3.180

Review 2.  To err is human, to correct is public health: a systematic review examining poor quality testing and misdiagnosis of HIV status.

Authors:  Cheryl C Johnson; Virginia Fonner; Anita Sands; Nathan Ford; Carla Mahklouf Obermeyer; Sharon Tsui; Vincent Wong; Rachel Baggaley
Journal:  J Int AIDS Soc       Date:  2017-08-29       Impact factor: 5.396

3.  Towards more accurate HIV testing in sub-Saharan Africa: a multi-site evaluation of HIV RDTs and risk factors for false positives.

Authors:  Cara S Kosack; Anne-Laure Page; Greet Beelaert; Tumwesigye Benson; Aboubacar Savane; Anne Ng'ang'a; Bita Andre; Jean-Paul Bn Zahinda; Leslie Shanks; Katrien Fransen
Journal:  J Int AIDS Soc       Date:  2017-03-24       Impact factor: 5.396

4.  Deep learning of HIV field-based rapid tests.

Authors:  Valérian Turbé; Carina Herbst; Thobeka Mngomezulu; Sepehr Meshkinfamfard; Nondumiso Dlamini; Thembani Mhlongo; Theresa Smit; Valeriia Cherepanova; Koki Shimada; Jobie Budd; Nestor Arsenov; Steven Gray; Deenan Pillay; Kobus Herbst; Maryam Shahmanesh; Rachel A McKendry
Journal:  Nat Med       Date:  2021-06-17       Impact factor: 53.440

5.  Evaluation of HIV testing algorithms in Ethiopia: the role of the tie-breaker algorithm and weakly reacting test lines in contributing to a high rate of false positive HIV diagnoses.

Authors:  Leslie Shanks; M Ruby Siddiqui; Jarmila Kliescikova; Neil Pearce; Cono Ariti; Libsework Muluneh; Erwan Pirou; Koert Ritmeijer; Johnson Masiga; Almaz Abebe
Journal:  BMC Infect Dis       Date:  2015-02-03       Impact factor: 3.090

  5 in total

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