Cardiovascular Risk Factors Determine Erectile and Arterial Function Response to Sildenafil
Bibliographic record
Abstract
BACKGROUND: Erectile dysfunction is related to endothelial function. Cardiovascular risk factors determine endothelial function. Sildenafil is effective in treatment of erectile dysfunction but shows variable results. This study investigated the relationship of cardiovascular risk factors to acute and chronic responses to sildenafil. METHODS: Cardiovascular risk factors and acute and chronic pulse wave responses to a single 50-mg dose of sildenafil were assessed in 45 patients with erectile dysfunction confirmed by low international index of erectile function (IIEF) score before and after chronic therapy with sildenafil. RESULTS: On recruitment all patients showed evidence of erectile dysfunction with an IIEF score of 5 points (1 to 20 points). Chronic sildenafil therapy resulted in an increase of IIEF score of 13 points (range -1 to +24 points) and 24 patients (53%) achieved an IIEF score>or=21 points. Improvement in erectile function in response to sildenafil (rn=0.79; P<.001) was dependent on initial erectile function (P=.002) and baseline apolipoprotein B (P=.01). Vascular responses to acute treatment with sildenafil were assessed using pulse wave analysis. Acute changes in stiffness index induced by sildenafil (rn=0.65; P<.001) were related to apolipoprotein A-1 (P=.006), B (P=.02), and lipoprotein(a) (P=.008) concentrations, whereas reflection index (rn=0.69; P<.001) was related to pulse pressure (P<.001), albumin-to-creatinine ratio (P=.007), and lipoprotein(a) (P=.02). CONCLUSIONS: The extent of acute and chronic effects of sildenafil on erectile function and pulse wave profiles is determined by metabolic cardiovascular risk factors. Improved cardiovascular risk factor control is likely to increase the efficacy of phosphodiesterase-5 inhibitor therapy in the treatment of erectile dysfunction.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".