Erectile dysfunction in spinal cord injury: a cost-utility analysis
Bibliographic record
Abstract
BACKGROUND: There is a high incidence of erectile dysfunction after spinal cord injury. This can have a profound effect on quality of life. Treatment options for erectile dysfunction include sildenafil, intracavernous injections of papaverine/alprostadil (Caverject), alprostadil/papaverine/phentolamine ("Triple Mix"), transurethral suppository (MUSE), surgically implanted prosthetic device and vacuum erection devices. However, physical impairments and accessibility may preclude patient self-utilization of non-oral treatments. METHODS: The costs and utilities of oral and non-oral erectile dysfunction treatments in a spinal cord injury population were examined in a cost-utility analysis conducted from a government payer perspective. Subjects with spinal cord injury (n=59) reported health preferences using the standard gamble technique. RESULTS: There was a higher health preference for oral therapy. The cost-effectiveness results indicated that sildenafil was the dominant economic strategy when compared with surgically implanted prosthetic devices, MUSE(R) and Caverject. The incremental cost-utility ratios comparing sildenafil with triple mix and vacuum erection devices favoured sildenafil, with ratios less than CAN$20,000 per quality adjusted life year gained. CONCLUSION: Based on this study, we conclude that sildenafil is a cost-effective treatment for erectile dysfunction in the spinal cord injury population.
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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 | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 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".