Systematic Review and Meta-Analysis of Pediatric Robot-Assisted Laparoscopic Pyeloplasty
Bibliographic record
Abstract
Introduction: To perform a systematic review (SR) and meta-analysis (MA) of outcomes of robot-assisted laparoscopic pyeloplasty (RALP) for ureteropelvic junction (UPJ) obstruction in children. Evidence Acquisition: A SR of the English-language literature on surgical techniques and perioperative outcomes of RALP for UPJ obstruction in children was performed without time filters using the MEDLINE (through PubMed), EMBASE, and Cochrane databases in July 2020 according to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis statement recommendations. Evidence Synthesis: Overall, 58 studies were selected for qualitative analysis, 46 of which were included in the MA. Nearly all studies included were observational and retrospective, either cohort or case–control. The quality of evidence was assessed using Modified Newcastle–Ottawa Scoring, with the majority of studies scoring medium or high quality. The mean success rate was 95.4% (confidence interval 91.0%–99.3%), over a wide age range. There was a noticeable heterogeneity in reported follow-up length and definitions of success rate. The majority of studies reported length of stay of ∼1 day. The mean overall complication rate was 12%. For studies that reported complication rate by grade, the mean low Clavien grade (Grade 2 or less) complication rate was 9.3% and the mean high Clavien grade (Grade 3 or more) complication rate was 6.5%. Conclusions: Robot-assisted surgery is technically feasible and has been shown to achieve very favorable outcomes for pyeloplasty in children. The evidence, however, is mostly retrospective and from single sites, which introduces potential biases. Further research is needed to further elucidate RALP benefits compared with the open and laparoscopic approach. As a randomized control trial may not be practical in this space, perhaps a prospective multi-institutional design with a uniform reporting system of pediatric RALP is the next step to define its benefits and limits.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.026 | 0.005 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".