Bibliographic record
Abstract
Introduction: Robotic-assisted laparoscopic pyeloplasty (RALP) has gained momentum in the treatment of pediatric ureteropelvic junction obstruction (UPJO), with similar outcomes compared to open and laparoscopic approaches; however, robotic surgery has been associated with longer operative time, which is major determinant of total surgery cost.The Da Vinci Xi system is the successor to the Si system that provides better robotic arm ergonomics, a mobile boom, and a targeting system designed to streamline robot docking.We hypothesized that these enhancements would reduce overall operative time and the total cost of RALP.Thus, our aim was to compare operative outcomes for pediatric RALP with the Da Vinci Si and Xi systems at our institution.Methods: We performed a retrospective cohort study of all pediatric patients undergoing RALP at our institution from 2019-2022.We compared the final 24 months of the Da Vinci Si system to the first 12 months of the Xi system.Bilateral or re-do pyeloplasty, and patients undergoing multiple procedures were excluded.Primary outcomes were operating room (OR) time, estimated blood loss (EBL), and length of inpatient stay.Secondary outcomes included change in hydronephrosis post-operatively.We controlled for surgeon experience, patient age, sex, laterality, reason for presentation, and imaging characteristics.Results: A total of 101 patients were included with a median age of 6 years (IQR 2-12) and median followup of six months (IQR 3-14).There were no differences in age at surgery, laterality, sex, reason for presentation, or imaging findings between both cohorts.Most (92%) patients demonstrated improvement in hydronephrosis postoperatively, with no difference based on robotic system.Mean operative time and EBL were lower in the Xi cohort (mean OR time 182 min vs. 207 min, p=0.02; median EBL 2 ml vs. 5 ml, p=0.02).Length of inpatient stay was similar in both cohorts (p=0.13).Conclusions: For pediatric robotic-assisted laparoscopic pyeloplasty, the Da Vinci Xi has a similar high success rate and is associated with shorter operative time and lower EBL compared to the Si system.This reduction in OR time may increase the cost-effectiveness of using a robotic approach.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.285 | 0.147 |
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".