Mitrofanoff Appendicovesicostomy in Robotic Paediatric Surgery—A Systematic Review
Bibliographic record
Abstract
INTRODUCTION: Proper bladder drainage is crucial. Children with bladder dysfunction may require alternative methods like clean intermittent catheterisation (CIC). However, CIC can be challenging for individuals with impairments. The Mitrofanoff procedure provides a solution by connecting the appendix to the bladder and creating a stoma on the skin, allowing for continent catheterisation. Minimally invasive techniques, including robotics, have been adopted recently. The aim of this study is to review the existing literature on robotic Mitrofanoff procedures. MATERIALS AND METHODS: A systematic review on paediatric robotic Mitrofanoff procedures on the PubMed, Cochrane, and Scopus databases was conducted according to the PRISMA Statement. Critical appraisals of the included studies were performed with the Newcastle Ottawa Scale. RESULTS: Six studies were included about the robotic Mitrofanoff procedure. Sex was reported in 50% of the studies. Ages were within the twelve-year age limit, as per the inclusion criteria. The mean operative time was 499.3 (±171.1) min. Four of the six studies reported a length of stay with a median of 6 days (±4; range 1.8-23). The incidence of complications was in line with established benchmarks. Only one study compared the Mitrofanoff procedure to open surgery, finding similar outcomes but longer operating times. Port placement and surgical strategy was described. CONCLUSIONS: Robotics can offer potential advantages for the Mitrofanoff procedure, despite its application still being in its early stages. This study emphasises the potential safety and efficacy of the robotic approach and promotes the need for further prospective high-quality studies.
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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 | 0.004 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".