The Implications and Management of Drug Interactions with Itraconazole, Fluconazole and Terbinafine
Bibliographic record
Abstract
The efficacy and safety of many pharmacological agents can be adversely affected by drug interactions. However, an appreciation of the mechanisms and incidence of these interactions, together with a knowledge of the patient's medical history, means that the majority are predictable and can be managed successfully. Drug interactions involving oral antifungal agents such as itraconazole, fluconazole and terbinafine have been studied extensively and are well understood. When problems are known to arise, they can often be overcome or minimised by varying the dosage regimens, or by drug monitoring. Where certain drugs are definitely contraindicated with antifungal agents, suitable alternatives can usually be found. Clinical trials and surveillance monitoring have demonstrated that when viewed in a wider context, drug interactions do not represent a particular safety problem for the newer oral antifungal agents. An improved understanding of the drug interaction processes and appropriate control measures mean that the high benefit-to-risk ratio of these medications can be maintained.
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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".