Effects of pioglitazone on erectile dysfunction in sildenafil poor-responders: a randomized, controlled study
Bibliographic record
Abstract
PURPOSE: The effects of pioglitazone on sildenafil responsiveness in men with erectile dysfunction(ED) and a history of poor response to sildenafil were assessed. METHODS: In a double-blinded study,38 men aged 47 +/- 1.5 years with moderate-to severe ED and poor response to sildenafil were randomly assigned to take a premedication of pioglitazone 30 mg (n=19) or placebo (n=19) once daily for 9 weeks along with on-demand use of sildenafil during the last month of pioglitazone treatment.Erectile function (EF) scores, assessed by EF domain of International Index of Erectile Function (IIEF), along with responses to Global Assessment Questions (GAQs) were major outcome measures. Serum levels of total testosterone (T),dehydroepiandrosterone sulfate (DHEAS), glucose,lipid profile and liver function test were minor outcome measures. RESULTS: Pioglitazone significantly improved major outcome measures compared with placebo. The decrease from baseline of total cholesterol level was more in pioglitazone than in placebo-treated groups. In 84% (32 out of 38) of the sildenafil poor-responders, at least one of the associated risk factors of ED was found. There was undiagnosed hypercholesterolemia in 34% of the subjects. Serum levels of T, DHEAS, glucose and other parameters remained unchanged in both groups. The intervention was well tolerated. CONCLUSIONS: Pioglitazone increased sildenafil response to improve ED of men with prior sildenafil failure and seems to be safe based on the present preliminary study. This improvement is likely regardless of fasting glucose and sex hormones levels.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".