Recurrent idiopathic high-flow priapism treated with selective arterial embolization after repeated initial treatments for low-flow priapism
Bibliographic record
Abstract
High-flow priapism is most often seen following perineal andpenile trauma. We report the case of a 32-year-old man whopresented with recurrent idiopathic priapism initially treated aslow-flow priapism on 8 previous emergency department visits.Pelvic angiography revealed an abnormal communication betweenthe left cavernosal artery and the left corpus cavernosum andled to the diagnosis of high-flow priapism. Treatment involvedembolization of the left common penile artery, which resultedin successful resolution of the recurrent priapism. Our patient’scase highlights the importance of an appropriate work-up, includingimaging, to distinguish high- and low-flow priapism and toprovide appropriate care.Le priapisme à haut débit est le plus souvent observé après untraumatisme périnéal et pénien. Nous décrivons le cas d’un hommede 32 ans atteint de priapisme idiopathique récurrent traité audépart comme un priapisme à bas débit lors de 8 visites antérieuresau service des urgences. Une angiographie pelvienne a révéléun passage anormal entre l’artère caverneuse gauche et le corpscaverneux gauche et a mené au diagnostic de priapisme à hautdébit. Un traitement par embolisation de l’artère pénienne gauchea été réalisé, entraînant la disparition complète du priapisme récurrent.Ce cas illustre l’importance d’une analyse approfondie, notammentà l’aide d’épreuves d’imagerie, afin de distinguer les cas àhaut débit des cas à bas débit et de choisir les soins appropriés.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".