HIV-2 drug resistance genotyping and viral load among HIV-2 infected adults inBurkina Faso, West Africa
Bibliographic record
Abstract
HIV-2 infection although less virulent compared to HIV-1 is endemic in many parts of West Africa. In Burkina Faso, few data exist on HIV-2 genotypic resistance. The objective of this study was to assess HIV-2 genotypic resistance and viral load in adult patients infected with HIV-2 in Burkina Faso. This was a cross-sectional study that ran from February 2017 to March 2019. This study included 91 HIV-infected adult patients on ARV treatment. HIV and hepatitis B and C status were confirmed by serological tests. HIV-2 viral load and HIV-2 clusters were determined by in-house tests. The mean age was 58.99 ±8.66 years. Of the patients, 12.1% were HIV-1, 73.6% were HIV-2 and 14.3% were co-infected with HIV-1/HIV-2. Only 15% had a high viral load (more than 1000 copies/mL). Groups A and B were detected in this study with the majority being group A (23.75%). HIV-2 subtype CRF01_AB was found in 3.75% of HIV-2 patients. Of the 34 HIV-2 patients whose subtypes were determined, only 7 had reverse transcriptase and 3 had protease resistance mutations. The M184V mutation was the most detected. This study revealed recent data on the status of HIV-2 genotypic resistance in Burkina Faso. Although few HIV-2 infected patients on ARV treatment have developed resistance, it is important to establish a surveillance system for HIV-2 genotypic resistance.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".