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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

Overview of attention for article published in BMC Infectious Diseases, February 2015
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (83rd percentile)
  • High Attention Score compared to outputs of the same age and source (88th percentile)

Mentioned by

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2 policy sources
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3 X users
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1 Facebook page

Citations

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35 Dimensions

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72 Mendeley
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Title
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
Published in
BMC Infectious Diseases, February 2015
DOI 10.1186/s12879-015-0769-3
Pubmed ID
Authors

Leslie Shanks, M Ruby Siddiqui, Jarmila Kliescikova, Neil Pearce, Cono Ariti, Libsework Muluneh, Erwan Pirou, Koert Ritmeijer, Johnson Masiga, Almaz Abebe

Abstract

BackgroundIn Ethiopia a tiebreaker algorithm using 3 rapid diagnostic tests (RDTs) in series is used to diagnose HIV. Discordant results between the first 2 RDTs are resolved by a third `tiebreaker¿ RDT. Médecins Sans Frontières uses an alternate serial algorithm of 2 RDTs followed by a confirmation test for all double positive RDT results. The primary objective was to compare the performance of the tiebreaker algorithm with a serial algorithm, and to evaluate the addition of a confirmation test to both algorithms. A secondary objective looked at the positive predictive value (PPV) of weakly reactive test lines.MethodsThe study was conducted in two HIV testing sites in Ethiopia. Study participants were recruited sequentially until 200 positive samples were reached. Each sample was re-tested in the laboratory on the 3 RDTs and on a simple to use confirmation test, the Orgenics Immunocomb Combfirm® (OIC). The gold standard test was the Western Blot, with indeterminate results resolved by PCR testing.Results2620 subjects were included with a HIV prevalence of 7.7%. Each of the 3 RDTs had an individual specificity of at least 99%. The serial algorithm with 2 RDTs had a single false positive result (1 out of 204) to give a PPV of 99.5% (95% CI 97.3%-100%). The tiebreaker algorithm resulted in 16 false positive results (PPV 92.7%, 95% CI: 88.4%-95.8%). Adding the OIC confirmation test to either algorithm eliminated the false positives. All the false positives had at least one weakly reactive test line in the algorithm. The PPV of weakly reacting RDTs was significantly lower than those with strongly positive test lines.ConclusionThe risk of false positive HIV diagnosis in a tiebreaker algorithm is significant. We recommend abandoning the tie-breaker algorithm in favour of WHO recommended serial or parallel algorithms, interpreting weakly reactive test lines as indeterminate results requiring further testing except in the setting of blood transfusion, and most importantly, adding a confirmation test to the RDT algorithm. It is now time to focus research efforts on how best to translate this knowledge into practice at the field level.Trial registrationClinical Trial registration #: NCT01716299.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 72 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 1%
Sweden 1 1%
Belgium 1 1%
Unknown 69 96%

Demographic breakdown

Readers by professional status Count As %
Student > Master 13 18%
Researcher 12 17%
Student > Ph. D. Student 12 17%
Student > Postgraduate 4 6%
Lecturer 3 4%
Other 8 11%
Unknown 20 28%
Readers by discipline Count As %
Medicine and Dentistry 21 29%
Nursing and Health Professions 6 8%
Immunology and Microbiology 5 7%
Social Sciences 5 7%
Biochemistry, Genetics and Molecular Biology 3 4%
Other 12 17%
Unknown 20 28%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 8. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 10 August 2021.
All research outputs
#4,117,174
of 23,743,910 outputs
Outputs from BMC Infectious Diseases
#1,300
of 7,930 outputs
Outputs of similar age
#57,714
of 356,037 outputs
Outputs of similar age from BMC Infectious Diseases
#18
of 154 outputs
Altmetric has tracked 23,743,910 research outputs across all sources so far. Compared to these this one has done well and is in the 82nd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,930 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.5. This one has done well, scoring higher than 83% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 356,037 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 83% of its contemporaries.
We're also able to compare this research output to 154 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 88% of its contemporaries.