Antiretroviral-induced adverse drug reactions in HIV-infected patients in Mali: a resource-limited setting experience
Bibliographic record
Abstract
BACKGROUND: There are few reports in the literature from sub-Saharan Africa (SSA) regarding antiretroviral-induced adverse drug reactions (ADRs). Antiretroviral therapy (ART) is now widely available in SSA, and ADRs during HIV infection are also frequent. In this study, we reported the frequency and risk factors of ART-induced ADRs in a Malian population. METHODS: This prospective cohort study was performed in the HIV Care and Counseling Centre (CESAC) of Mali from 2011 to 2012. Adult patients infected with HIV and who had recently started ART were included and followed-up clinically Were included in this study, adult patients living with HIV and had recently started ART who were followed up for at least 6 months to determine the incidence of ADRs using Naranjo's classification scale. RESULTS: During this study, 357 (42.3%) patients presented ADRs (40.1% of our patients (n=338) experienced at least one ADR, and 2.2% (n=19) experienced at least two ADRs). The prevalence of ADRs by organ system was: 45.9% neurological (n=164); 29.4% metabolic (blood chemistry) (n=105); 15.4% hematological (n=55). High probable rate of ADR was observed as indicated by the Naranjo score in 83.7% of the cases. Zidovudine (AZT) and stavudine (d4T) use was identified as a risk factor for either anaemia or peripheral neuropathy whereas nevirapine (NVP) and female gender were risk factors for skin reactions. Patients with advance disease had the highest rate of ADRs compared to the others. CONCLUSIONS: Based on the Naranjo probability scale, our data show that ADRs such as peripheral neuropathy and anemia are very frequent. These ADR was linked to AZT and D4T. Our findings highlight the need for active monitoring, continuous pharmacovigilance of ART and change of some ART drug in this population.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".