Global experiences with vardenafil in men with erectile dysfunction and underlying conditions
Bibliographic record
Abstract
OBJECTIVE: Vardenafil has demonstrated efficacy for the pharmacological management of erectile dysfunction (ED). Accumulating evidence suggests that ED is frequently associated with underlying cardiovascular and metabolic conditions which are thought to be involved in the aetiology of ED. The present review aims to summarise and discuss the available evidence for the efficacy, safety and tolerability of vardenafil in patients with underlying conditions including diabetes, hypertension and dyslipidaemia. METHODS: Relevant articles were identified through a PubMed search of clinical trials and postmarketing surveillance studies of vardenafil in patients with ED including those with diabetes, hypertension and dyslipidaemia. RESULTS: Across all trials, vardenafil showed good efficacy for the treatment of ED in patients with diabetes, hypertension and dyslipidaemia. Vardenafil also showed a favourable safety and tolerability profile. The concomitant use of medication to treat hypertension or dyslipidaemia was not associated with an increase in adverse events following vardenafil treatment. CONCLUSIONS: The prevalence of both diagnosed and undiagnosed underlying conditions is high among men with ED. The evidence presented in this review suggests that vardenafil is efficacious and well tolerated in patients with ED and diabetes, hypertension and/or dyslipidaemia and can be recommended as first-line treatment for ED in patients with these conditions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".