Prediction of sexual function after radical prostatectomy
Bibliographic record
Abstract
Radical prostatectomy (RP) is a commonly used procedure in the treatment of clinically localized prostate cancer. For this report, the authors critically analyzed the factors associated with recovery of erectile function after surgery. A systematic review of the literature using the Medline and CancerLit databases was conducted. Keywords for the literature search included prostate cancer, radical prostatectomy, erectile dysfunction, impotence, treatment, and prophylaxis. Accurate patient selection (based on patient age, preoperative erectile function, and comorbidity profile) and adequate surgical technique (ie, the preservation of neurovascular bundles) were the major determinants of postoperative erectile function. Moreover, better results were achieved when an appropriate pharmacologic treatment using either oral or local approaches was given. Therefore, the authors concluded that, if patients are stratified correctly according to preoperative, intraoperative, and postoperative factors, then a satisfactory functional recovery may be expected after surgery. For these reasons, an ideal multivariate model predicting the restoration of erectile function after surgery should include patient, surgeon, and postsurgical treatment variables. The authors also concluded that the stratification of patients with regard to their risk of developing erectile dysfunction after surgery was feasible based on several parameters, which should be taken into account for correct patient treatment and counseling. To address this objective, accurate tools for predicting the likelihood of complete functional recovery after surgery are needed. Cancer 2009;115(13 suppl):3150-9. (c) 2009 American Cancer Society.
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 | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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 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".