Does prophylactic ureteric stenting at the time of colorectal surgery reduce the risk of ureteric injury? A systematic review and meta‐analysis
Bibliographic record
Abstract
Abstract Aim Cystoscopic placement of ureteric stents during colorectal surgery (CRS) may aid in the intraoperative identification of the ureters and thus prevent ureteric injury, but may also be associated with prolonged operating time, increased cost and adverse events. No formal recommendations exist regarding the use of ureteric stents prior to CRS. Our aim was to determine the effect of prophylactic ureteric stent insertion on the risk of ureteric injury among adult patients undergoing CRS. Method A systematic search using the Ovid platform was completed. The primary outcome was risk of ureteric injury. Secondary outcomes included the risk of acute kidney injury (AKI), urinary tract infection (UTI), sepsis, length of stay (LOS) and mortality. The Paule–Mandel pooling and a random effects model was used to produce odds ratios (ORs) with 95% confidence intervals (CIs) for binary outcomes. Standardized mean differences (MD) were reported for continuous variables. Analyses were completed using R3.5. Results Nine retrospective cohort studies evaluating 98 507 patients were included. The incidence of ureteric injury was 0.6%. Overall, 5.1% of patients underwent ureteric stenting. There was no change in the odds of ureteric injury among stented patients compared with controls (OR 1.30, 95% CI 0.39‐4.29, I 2 = 25%). Operating time was significantly longer (MD 49.3 min, 95% CI 35.3–63.4, I 2 = 96%) in the intervention group. There was no difference in rates of AKI, UTI, sepsis, LOS or mortality between groups. Conclusion Given the retrospective nature of the identified studies, the benefit of prophylactic ureteric stenting remains uncertain. Prophylactic ureteric stenting was not associated with increased patient morbidity but did significantly increase operating time.
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 | 0.007 | 0.022 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.018 | 0.026 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".