Robotic ureteral reimplantation: systematic review and pooled analysis of comparative outcomes in adults
Bibliographic record
Abstract
INTRODUCTION: The surgical treatment of ureteral strictures in adults represents a challenging procedure for the variability of location, extension, and etiology of the disease. Open ureteral reimplantation (OUR) offered high success rates even when considering complex ureteral disease. The debate for defining the role of robotic in the treatment of adult ureteral disease is still ongoing. The aim of the current systematic review is to provide an updated analysis of the comparative outcomes of robot-assisted UR (RAUR) versus OUR based on the available literature. EVIDENCE ACQUISITION: An independent systematic review of the literature was performed from 2010 to 2021. Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) recommendations were followed to design search strategies, selection criteria, and evidence reports. The quality of the included studies was determined using the Newcastle-Ottawa scale for non-randomized controlled trials. Pooled analysis of demographics and clinical characteristics, as well as surgical and postoperative outcomes, was performed. EVIDENCE SYNTHESIS: After an initial screening and full-text review, five studies published between 2002 and 2021 were identified and included in the analysis. All the studies were observational retrospective case-control studies. Among the 225 patients included in the pooled analysis, 94 (41.8%) and 131 (58.2%) were RAUR and OUR, respectively. There was no difference between groups in terms of baseline characteristics. No differences in surgical approach and operative time were reported among the groups. Estimated blood loss was lower for robotic approach (WMD: -121.71 mL; P=0.0006). There were no significant differences between groups in overall (OR: 0.85; P=0.69) and major (OR: 0.69; P=0.52) complication. RAUR group reported shorter length of stay (WMD: -2.39 days; P<0.00001), catheter (WMD: -5.26 days; P=0.004) and stent (WMD: -11.9 days; P=0.001) time. CONCLUSIONS: Available evidence shows that RAUR offers similar surgical outcomes if compared to OUR, and potential advantages in terms of lower blood loss, shorter hospital stay, catheter, and stent time. The adoption of one approach over the other is likely to be mainly dictated by the surgeon's preference and expertise.
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 | 0.028 | 0.070 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.022 | 0.031 |
| Bibliometrics | 0.010 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| 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".