The use of tirzepatide to successfully treat persistent genital arousal disorder/genitopelvic dysesthesia: a case report
Bibliographic record
Abstract
Introduction: Persistent genital arousal disorder/genitopelvic dysesthesia (PGAD/GPD) is associated with poor quality of life. Due to social stigma and its heterogeneous nature, many patients suffer without treatment. Aims: This case presents the first example of the successful use of a glucagon-like peptide 1 and glucose-dependent insulinotropic polypeptide receptor agonist (GLP1/GIP RA) medication for the treatment of PGAD/GPD. Methods: The patient was identified by the Sexual Medicine Research Team, retained as a patient at a sexual medicine clinic, and interviewed for the purposes of this case report. Results: This case presents a 44-year-old woman with a lifelong history of PGAD/GPD symptoms that caused extreme distress and depression who experienced 95% resolution of her symptoms within 2 days of starting tirzepatide, a GLP1/GIPRA medication, for weight loss. Conclusion: Increasing benefits of GLP1/GIPRAs are being uncovered, and further studies must investigate the potential for these medications to be used in patients with PGAD/GPD. This study also provides a potential mechanism for decreased arousal resulting from GLP1/GIP receptor activation in attention/reward pathways in the brain.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.002 |
| 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".