Erectile Dysfunction Is Common after Rectal Cancer Surgery: A Cohort Study
Bibliographic record
Abstract
Erectile dysfunction is a known late complication following surgery for rectal cancer. We aimed to determine the prevalence of erectile dysfunction after rectal cancer surgery and characterize it. This was a prospective observational cohort study. Data from men after surgery for rectal cancer were collected between October 2019 and April 2023. The primary outcome was the prevalence of erectile dysfunction following surgery based on the International Index of Erectile Function questionnaires, IIEF-5 and 15. Secondary outcomes were prevalence in subgroups and self-perceived erectile function. In total, 101 patients agreed to participate, while 67 patients (67%) responded after a median six-month follow-up after surgery. Based on IIEF-15, 84% of the patients had erectile dysfunction. For subgroups, 74% of patients who underwent robot-assisted surgery had erectile dysfunction, whereas all patients who underwent either laparoscopic or open surgery had erectile dysfunction (p = 0.031). Furthermore, half of the patients rated their self-perceived ability to obtain and keep an erection as very low. In conclusion, in our cohort, erectile dysfunction was common after rectal cancer surgery, and half of the patients were unconfident that they could obtain and keep an erection. Information regarding this finding should be given so that patients feel comfortable discussing therapeutic solutions if needed.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".