An Evidence-Based Perspective to Commonly Performed Erectile Dysfunction Investigations
Bibliographic record
Abstract
INTRODUCTION: Currently there is no universally accepted gold standard diagnostic test to differentiate psychogenic from physical erectile dysfunction (ED). Instead, sexual health specialists rely on a detailed history, a focused physical examination, and specialized diagnostic tests, to decide if the etiology of the ED is mainly psychogenic or organically caused. Aim. In this review we point out the status of evidence-based principles in the area of diagnosis in Sexual Medicine. METHODS: We review the concepts of evidence-based medicine (EBM) in the area of medical diagnostic tests. We highlight four of the well-known diagnostic tests (penile duplex, pharmacoarteriography, pharmacocavernosometry/cavernosography [PHCAS/PHCAG], and nocturnal penile tumescence [NPT monitoring]) for ED evaluation within an evidence-based perspective. MAIN OUTCOME MEASURES: Assessment of diagnostic tests for ED using principles of EBM. RESULTS: Several good diagnostic tests are useful in the evaluation of men with ED. However, modern evidence-based concepts-mainly the likelihood ratio-have not yet been applied to these tests to obtain their maximum clinical benefits. CONCLUSIONS: While penile duplex/color Doppler has good evidence of supporting its use in the diagnosis of arteriogenic ED, data supporting its diagnosis of a physical disorder associated with cavernous venous occlusion dysfunction are lacking. PHCAS/PHCAG's main drawback is an unknown positive predictive value and a possibility of frequent false-positive results. NPT has many advantages when differentiating psychogenic from organic ED, however, several questions related to its physiological mechanisms do exist. Ghanem H, and Shamloul R. An evidence-based perspective to commonly performed erectile dysfunction investigations.
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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 | 0.031 | 0.070 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.015 | 0.008 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.007 | 0.008 |
| Insufficient payload (model declined to judge) | 0.003 | 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".