The Frequency of Urination Dysfunction in Patients Operated on for Rectal Cancer: A Systematic Review with Meta-Analyses
Bibliographic record
Abstract
The frequency of long-term urination dysfunction after surgery for rectal cancer remains unclear, yet it is essential to establish this to improve treatment strategies. Randomized controlled trials (RCTs), non-RCTs, and cohort studies were included with patients having undergone sphincter-preserving total (TME) or partial mesorectal excision (PME) for the treatment of primary rectal cancer in this review. The outcome was urination dysfunction reported at least three months postoperatively, both overall urination dysfunction and subdivided into specific symptoms. The online databases PubMed, Embase, and Cochrane CENTRAL were searched, bias was assessed using the Newcastle-Ottawa scale, and results were synthesized using one-group frequency meta-analyses. A total of 55 studies with 15,072 adults were included. The median follow-up was 29 months (range 3-180). The pooled overall urination dysfunction was 21% (95% confidence interval (CI) 12%-30%) 3-11 months postoperatively and 25% (95% CI 19%-32%) ≥12 months postoperatively. Retention and incontinence were common 3-11 months postoperatively, with pooled frequencies of 11% and 14%, respectively. Increased urinary frequency, retention, and incontinence seemed even more common ≥12 months postoperatively, with pooled frequencies of 37%, 20%, and 23%, respectively. In conclusion, one in five patients experienced urination dysfunction more than a year following an operation for rectal cancer.
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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 | 0.011 | 0.030 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.014 | 0.032 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".