CLINICALLY SIGNIFICANT DRUG-DRUG INTERACTION IN A LARGE ANTIRETROVIRAL TREATMENT CENTRE IN LAGOS, NIGERIA
Bibliographic record
Abstract
Background: An important cause of treatment failure to antiretroviral therapy (ART) is the potential interaction between the antiretroviral (ARV) drugs and co-prescribed drugs used concomitantly for the treatment of opportunistic infections and co-morbid ailments in HIV-infected patients. Objectives: The study evaluated potential clinically significant drug interactions (CSDIs) occurring between recommended ART regimens and their co-prescribed non-antiretroviral drugs (CPD) Method: This study was carried out in a large HIV treatment centre (APIN clinic) in a Nigerian teaching hospital, in Lagos Nigeria, caring for over 20,000 registered patients. Electronic Medical Records (EMR) of 500 patients who received treatment between 2005 and 2015, were selected using systematic random sampling, reviewed retrospectively, and evaluated for potential CSDIs using Liverpool HIV Pharmacology Database and other similar databases. Results: Majority of patients, 421 (84%) were at risk of CSDIs, of which 410, (82%) were moderate and frequently involved co-trimoxazole + zidovudine (or stavudine) /lamivudine (386, 77.2%) and NNRTIs or PIs + artemisinin-based combination therapies (ACTs) [296, 59.2%]. Age (p=0.131), sex (p=0.316) and baseline CD4+ cell counts (p>0.05) were not significantly associated with CSDIs. The interactions, however, were significantly associated with the development of antiretroviral treatment failure (p <0.001) which occurred in nearly a third (139; 27.8%) of the patients. Conclusion: There is a high prevalence of CSDIs between ART and CPDs most of which were categorized as moderate. Further studies are required to evaluate the pharmacokinetic and clinical relevance of these interactions.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".