Sleep-related painful erections: a survey-based analysis of patient-reported experiences with diagnosis and management
Bibliographic record
Abstract
Abstract Sleep-related painful erection (SRPE) is a condition characterized by painful nocturnal erections and frequent nighttime awakenings. The pathophysiology of SRPE is not well understood and existing literature consists mainly of case reports. We aimed to investigate the causes, treatments, and impact on quality of life among individuals affected by SRPE. A questionnaire comprising 30 items was administered to a group of men with SRPE. The survey collected information on demographics, clinical and social history, symptomatology, interventions and quality of life. 44 patients with SRPE responded to the survey, with a mean age of 43.3 years. Most respondents had no relevant medical history related to erectile function disorders. 43% of subjects reported sleep apnea, and 27% reported a mental health disorder or psychiatric medication use. Baclofen was the most common medication, but only 25% of patients found it beneficial. Sleep repositioning, oxygen device use and pelvic floor therapy were interventions that provided the most relief. Most patients did not require emergency department visits (93%); only a small number needed penile aspiration (n=2). As reported by most respondents, SRPE significantly impacted patients' quality of life. The findings highlight the need for further research to understand SRPE better and develop effective treatment options.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".