High resistance to antiretroviral drugs: the Indian experience
Bibliographic record
Abstract
Effective antiretroviral treatment (ART) has significantly reduced the morbidity and mortality among people living with HIV/AIDS. The emergence of drug resistance is the major obstacle to the successful implementation of long-term treatment strategy of HIV disease. Hence, monitoring the resistance to ART is an essential task. The MGM Medical College in Navi Mumbai is the only national facility with the capacity to monitor ART resistance using tissue culture technique. The main objective of the study was to determine the prevalence of primary and secondary resistance between May 1997 and April 2003. Four hundred and sixty viral isolates of 74 individuals were tested for ART resistance using tissue culture-based protocol (McGill University, Canada). These included 287 primary and 173 follow-up viral isolates. Following activation of tissue culture, a panel of 12 antiretroviral drugs in concentrations from 0.038 mg/mL to 0.090 mg/mL was tested. The resistance was determined on the basis of the production of p24 antigen at the end of 72 and 144 hours of incubation. The overall resistance against reverse transcriptase inhibitors (RTIs) was 33.7% and that to protease inhibitors (PIs) was 21.5%. However, prevalence of primary resistance among ART näive to RTIs was 14/208 (6.7%) of isolates and that to (PIs) was 2/79(2.5%) of isolates. The incidence of resistance to RTI was 22/500 years (4.4/100 years) and that to PIs was 8/253.6 years (3.2/100 years). It is possible that non-B subtypes of HIV-1 that are prevalent in most developing countries are likely to develop resistance rapidly after ART. However, common factors that influence development of resistance such as poor adherence, inadequate 'wild' doses and regimens, and poor monitoring were not validated in the study. Unless active surveillance is instituted, these factors can pose major challenge for the management of people on ART in developing countries.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".