Routine cardiac assessment is not necessary for all patients with erectile dysfunction
Bibliographic record
Abstract
rectile dysfunction (ED) is defined as the persistent inability to achieve and/or maintain an erection sufficient for satisfactory sexual performance.The combined prevalence of minimal, moderate and complete ED was reported as high as 52% from the Massachusetts Male Aging Study. 1 At age 40, there is an about a 40% prevalence rate, increasing to almost 70% in men at age 70. 1 In Canada, a similar overall prevalence of ED was reported (49.4%). 2 In addition, ED been shown to have a negative impact on a patient's quality of life, sexual relationships and overall well-being.3 The etiology of ED fits in one of 3 categories: organic, psychogenic or, most commonly, a combination of both.Phophodiesterase-5 (PDE) inhibitors revolutionized ED treatment and is the first-line treatment.These agents have been shown to be effective with good safety profiles in a comorbid population of men with ED, including patients with vascular disease, coronary artery disease (CAD), hypertension and diabetes.[4][5][6] Treatment options for patients not responding to oral drugs (or contraindicated) include intracavernous injections, intraurethral alprostadil, vacuum-constriction devices and penile prosthesis.7
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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.018 | 0.006 |
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".