Toward a new ‘EPOCH’: optimising treatment outcomes with phosphodiesterase type 5 inhibitors for erectile dysfunction
Bibliographic record
Abstract
Despite the marked adverse impacts of erectile dysfunction (ED) on quality of life and well-being, many patients (and/or their partners) do not seek medical attention for this problem, do not receive treatment or discontinue such treatment even when it has effectively restored erectile responses to sexual stimulation. Phosphodiesterase type 5 (PDE5) inhibitors are considered first-line therapies for men with ED. To help physicians maximise the likelihood of treatment success with these agents, we conducted an English-language PubMed search of articles involving approved PDE5 inhibitors dating from 1 January 1998 (the year in which sildenafil citrate was introduced), through 31 August 2008. In addition to sildenafil, tadalafil and vardenafil, search terms included 'adhere*', 'couple*', 'effect*', 'effic*', 'partner*', 'satisf*', 'succe*' and 'treatment outcome.' Based on our analysis, physician activities to promote favourable treatment outcomes may be captured under the mnemonic 'EPOCH': (i) Evaluating and educating patients and partners to ensure realistic expectations of therapy; (ii) Prescribing a treatment individualised to the couple's lifestyle needs and other preferences; (iii) Optimising treatment outcomes by scheduling follow-up visits with the patient to 'fine-tune' dosages and revisit key educational messages; (iv) Controlling comorbidities via lifestyle counselling, medications and/or referrals and (v) Helping patients and their partners to meet their health and psychosocial needs, potentially referring them to a specialist for other forms of therapy if they are not satisfied with PDE5 inhibitors.
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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 | 0.011 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".