Topiramate-Induced Suicidal Ideation and Olfactory Hallucinations: A Case Report
Bibliographic record
Abstract
Antiepileptic drugs prescribed in the context of migraine have been reported to be potentially linked with an increased risk of suicidal ideation and behavior. Meta-analyses support the evidence that amongst antiepileptic drugs, Topiramate has the greatest potential for facilitating the occurrence of suicidal ideation and behavior. Studies indicate that this occurs via the increased incidence of mood disorders amongst the population with migraines using Topiramate as a treatment, with a slow and progressive onset of suicidal ideation (if any). We discuss the unique case of a 43-year-old man known to have chronic migraines, who presented with intense rapid-onset suicidal ideation and olfactory hallucinations, three weeks after the introduction of Topiramate for chronic migraines. After a negative extensive investigation panel to rule out common organic diseases, Topiramate was ceased. The suicidal ideation and olfactory hallucinations resolved in less than 24 h without further interventions. This case report highlights that rapid-onset suicidal ideation and olfactory hallucinations could be linked as an unusual side effect to the introduction of Topiramate. The removal of Topiramate from the patient’s pharmacological treatments prevented further psychological distress linked to ego-dystonic suicidal ideation and a resolution of olfactory hallucinations. He was discharged 48 h later.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.006 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".