Dolutegravir response in antiretroviral therapy naïve and experienced patients with M184V/I: Impact in low-and middle-income settings
Bibliographic record
Abstract
BACKGROUND: Dolutegravir (DTG) is now recommended to all HIV infected adults, adolescents, and children of right age by WHO. The low cost of $75 per year for generic DTG-based combination, has allowed 3.9 million people living with HIV (PLWH) in low and middle-income countries (LMICs) access to DTG. Lamivudine and emtricitabine associated M184V/I mutation is highly prevalent in PLWH and the majority of HIV infected individuals receiving DTG regimens may already be carrying M184V/I mutation. DISCUSSION: Despite high prevalence of M184V/I in antiretroviral therapy (ART) experienced patients, DTG treatment outcomes will likely not be adversely affected by this mutation. The use of DTG in ART naïve has been largely characterised by rare emergence of resistance and virological failure. DTG-based regimens have to great extent been effective at maintaining viral suppression in treatment experienced PLWH carrying M184V/I. CONCLUSIONS: Initiating patients on DTG may help preserve more treatment options for HIV infected individuals living in LMICs. High genetic barrier to the development of resistance associated with DTG and progressive viral suppression in patients switched to DTG-based therapy with M184V/I, may encourage better DTG outcomes and help in curbing increasing levels of HIV drug resistance in LMICs.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".