Robotic Approach to Paediatric Gastrointestinal Diseases: A Systematic Review
Bibliographic record
Abstract
Introduction: The use of minimally invasive surgery (MIS) for paediatric surgery has been on the rise since the early 2000s and is complicated by factors unique to paediatric surgery. The rise of robotic surgery has presented an opportunity in MIS for children, and recent developments in the reductions in port sizes and single-port surgery offer promising prospects. This study aimed to present a systematic overview and analysis of the existing literature around the use of robotic platforms in the treatment of paediatric gastrointestinal diseases. Materials and Methods: In accordance with the PRISMA Statement, a systematic review on paediatric robotic gastrointestinal surgery was conducted on Pubmed, Cochrane, and Scopus. A critical appraisal of the study was performed using the Newcastle Ottawa Scale. Results: Fifteen studies were included, of which seven were on Hirschsprung’s disease and eight on other indications. Included studies were heterogeneous in their populations, age, and sex, but all reported low incidences of intraoperative complications and conversions in their robotic cohorts. Only one study reported on a comparator cohort, with a longer operative time in the robotic cohort (180 vs. 152 and 156 min, p < 0.001), but no significant differences in blood loss, length of stay, intraoperative complications, postoperative complications, or conversion. Conclusions: Robotic surgery may play a role in the treatment of paediatric gastrointestinal diseases. There is limited data available on modern robotic platforms and almost no comparative data between any robotic platforms and conventional minimally invasive approaches. Further technological developments and research are needed to enhance our understanding of the potential that robotics may hold for the field of paediatric surgery.
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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 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".