063 Influential Factors for Penile Implant Patient Satisfaction at 1 Year from the Propper Registry
Bibliographic record
Abstract
We previously reported an overall dissatisfaction rate of 12% for patients with penile prostheses from the PROPPER study of AMS penile implants. Here we further analyze which variables influence satisfaction. This is a retrospective analysis of prospectively collected data as part of the PROPPER penile prosthesis patient registry. Men with at least 1-year patient satisfaction data were included. Univariable analyses were performed with ANOVA or Chi-square tests as indicated with significance set to a P-value ≤0.001 after Bonferroni correction. Stepwise Multivariable logistic regression analysis was then performed with variables with a P value <.05 retained in the model. As of June 2015, 615 subjects had at least 1 year of evaluable data. 84% were satisfied/very satisfied, 6% were neutral, and 10% were dissatisfied/very dissatisfied. Variables that did not influence satisfaction included age, ethnicity, implant model, surgical approach, concurrent curvature correction, primary ED category, duration of ED, baseline depression status, concomitant ED diagnoses such as peyronies or diabetes, anti-coagulant use, IIEF baseline score or severity, UCLA sexual function bother or baseline, concurrent procedures, drain use, hospital admission status, foley at time of discharge and reservoir type or placement approach. Factors that were associated with satisfaction included surgery type (virgin/salvage/revision), use of device at 1 year, device problem reported at 1 year, AUA SI total score and baseline category, baseline UCLA bowel function and urinary bother. Data regarding baseline penile size largely did not influence patient satisfaction (total device length, pre-op penile flaccid and stretched length, penile length and girth difference between pre and post op, total length of RTE per cylinder), but penile length with device inflated trended toward significance (p=0.006). The stepwise logistic regression model selection indicated that only baseline UCLA bowel function, AUA SI total score, and penile length with device inflated were significantly associated with satisfaction.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".