Onset of Transient Sadness Following the Concomitant Use of a Triptan and Selective Serotonin Reuptake Inhibitor/Serotonin Norepinephrine Reuptake Inhibitors Therapy: A Case Report
Bibliographic record
Abstract
Background: Migraine and depression have a bi-directional, positive association. The likelihood of these conditions being comorbidities is high, thus, the possibility of concomitant use of an antidepressant and a triptan is also increased. Case Presentation: We present a case of a 39-year-old female with a history of migraine with aura and depression who had brief episodes of exacerbated depressive symptoms following oral administration of sumatriptan 100 mg daily as needed while taking various selective serotonin reuptake inhibitor (SSRI) and serotonin and norepinephrine reuptake inhibitor (SNRI) medications on different occasions. The patient experienced 30-minute episodes of sweating and subjective increase in temperature approximately 2–3 hours after administration of sumatriptan 100 mg. This was followed by a transient exacerbation of sadness described by the patient as unhappiness, hopelessness, and tearfulness, which lasted 1 to 2 hours. To date, there are no other published case reports that have described this particular presentation. Several studies have reported possible serotonin syndrome as a result of the combination. Current evidence and known pharmacological actions of SSRIs/SNRIs and triptans are not well-defined enough to explain how one can experience episodic worsening depression. Conclusion: This case illustrates that clinicians should consider other potential adverse effects of the combined use of triptans and SSRIs/SNRIs beyond serotonin syndrome.
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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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".