Possible Interaction Between Lopinavir/Ritonavir And Valproic Acid Exacerbates Bipolar Disorder
Bibliographic record
Abstract
OBJECTIVE: To describe a case of exacerbated mania potentially related to an interaction between lopinavir/ritonavir and valproic acid (VPA) and propose a mechanism of action for this interaction. CASE SUMMARY: A 30-year-old man with bipolar disorder and HIV initiated treatment with lopinavir/ritonavir, zidovudine, and lamivudine. Prior to beginning therapy with these antiretrovirals, he was receiving VPA 250 mg 3 times daily, with his most recent VPA concentration measured at 495 micromol/L. Twenty-one days after starting antiretroviral treatment, he became increasingly manic. His VPA concentration at admission was 238 micromol/L, a 48% decrease. The daily VPA dose was increased to 1500 mg, and olanzapine was introduced. The VPA concentration following this dose escalation was 392 micromol/L, and the patient improved clinically. DISCUSSION: Fifty percent of VPA is metabolized by glucuronidation, 40% undergoes mitochondrial beta-oxidation, and less than 10% is eliminated by the cytochrome P450 isoenzymes. Ritonavir can induce glucuronidation of several medications including ethinyl estradiol, levothyroxine, and lamotrigine. We believe that ritonavir-mediated induction of VPA glucuronidation resulted in a decrease in VPA concentrations and efficacy. An objective causality assessment suggested that the increased mania was probably related to the decrease in VPA concentration and that a possible interaction exists between lopinavir/ritonavir and VPA. CONCLUSIONS: A potential interaction exists between VPA and all ritonavir-boosted antiretroviral regimens. Clinicians should monitor patients closely for a decreased VPA effect when these medications are given concomitantly.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".