Evaluation of 9 rapid diagnostic tests for screening HIV infection, in Lomé, Togo
Bibliographic record
Abstract
HIV rapid diagnostic tests (RDT) could be greatly contributive for a universal access to HIV diagnosis. However, according to the WHO, these tests need to be assessed before they can be used in routine. We assessed 9 RDT in routine clinical use between 2009 and 2013. The sensitivity and specificity observed for 7 tests were ≥ 99% and ≥ 98%, respectively: FIRST RESPONSE HIV1-2-O PMC Medical, India, GENIE Fast HIV 1-2 and GENIE™ III HIV1/2 Bio-Rad, France, HIV TRI-DOT + Ag; J. Mitra, INDIA; SD BIOLINE HIV1/2 3.0 and SD BIOLINE HIV/SYPHILIS DUO Standard Diagnostic, Korea; and VIKIA HIV1/2; BioMérieux, France. Two tests had performances inferior to WHO recommendations: INSTI HIV1/2 Biolytical Canada; sensitivity = 97.8% and HEXAGON HIV HUMAN GmbH Germany; specificity = 94.8%. Seven of 9 RDT had excellent performances. Nevertheless, they can be used only after training staff, and taking into account national algorithm for their safe use. L'utilisation des tests de diagnostic rapide (TDR) du virus de l'immunodéficience humaine (VIH) est importante pour l'accès universel au diagnostic du VIH. Cependant, selon l'Organisation Mondiale de la santé, leur évaluation est indispensable avant la mise à disposition des prestataires. Nous avons évalué en routine 9 TDR entre 2009–2013. La sensibilité et la spécificité observées pour 7 tests (FIRST RESPONSE HIV1-2-O PMC Medical, India, GENIE FAST HIV 1-2 et GENIE™ III HIV1/2 Bio-Rad, France, HIV TRI-DOT + Ag ; J. Mitra, INDIA ; SD BIOLINE HIV-1/2 3.0 et SD BIOLINE HIV/SYPHILIS DUO Standard Diagnostic, Korea ; et VIKIA HIV1/2 ; Bio Mérieux, France) étaient respectivement ≥ 99 % et ≥ 98 %. Deux tests avaient des performances en dessous de celles recommandées par l'OMS (INSTI HIV1/2 Biolytical Canada ; sensibilité = 97,8 % et HEXAGON HIV HUMAN GmbH Germany ; spécificité = 94,8 %) La performance observée pour 7 des 9 TDR est excellente. Cependant, leur utilisation nécessite la formation des prestataires et le respect de l'algorithme national.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".