Sexual function in women receiving maintenance dialysis
Bibliographic record
Abstract
While substantial attention has been paid to the issue of sexual dysfunction in men on chronic dialysis, less is known about this problem in women with end-stage renal disease. We sought to assess sexual dysfunction in women on chronic dialysis and determine whether patients discuss this problem with their providers and receive treatment. We prospectively enrolled women receiving chronic hemodialysis or peritoneal dialysis in Pittsburgh, PA. We asked patients to complete the 19-item Female Sexual Function Index (FSFI) to assess sexual function and a 5-item survey that assessed whether patients had discussed sexual dysfunction with their providers and/or received treatment for this problem in the past. We enrolled 66 patients; 59 (89%) on hemodialysis and 7 (11%) on peritoneal dialysis. All patients completed the FSFI, of whom 53 (80%) had FSFI scores <26.55, consistent with the presence of sexual dysfunction. Of 37 patients who were married or residing with a significant other, 27 (73%) had sexual dysfunction. Among 24 participants who reported having been sexually active over the previous 4 weeks, 11 (46%) had sexual dysfunction. Only 21% of patients with sexual dysfunction had discussed this problem with their gynecologist, renal or primary provider, and 3 (6%) reported having received treatment. Sexual dysfunction is common in women on dialysis, even among patients who are married or residing with a significant other and those who are sexually active. However, few women discuss this issue with their providers or receive treatment.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".