Laparoscopic-Assisted Colostomy in Children
Bibliographic record
Abstract
INTRODUCTION: Colostomy morbidity has been reported to be as high as 50%. Laparoscopic-assisted colostomy (LAC) is associated with decreased colostomy complication. LAC is recommended for stoma formation in adults but has not been previously reported in children. In this paper, we report on our initial experience with LAC in children. MATERIALS AND METHODS: Using a two- to four-port (3.5-mm) technique, LAC was performed in a female with an imperforate anus and 2 male patients with complicated Hirschsprung's disease (HD), respectively. Data collected included operative time, time to recover bowel function, and morbidity. Close follow-up was done until stoma closure. RESULTS: The operative time was 144 minutes in the HD patients (including concomitant laparoscopic biopsies and a leveling colostomy) and 40 minutes in the imperforate anus patient. Median time to passage of both flatus and stool was 40 hours (range, 24-48). Time to commence feeds postop was 40 hours (range, 24-48). The median time of follow-up was 3 months (range, 2-9) until the stoma was taken down. No complications have occurred to date. CONCLUSIONS: LAC is safe and easily performed in neonates and infants. It facilitates accurate stoma placement and orientation. It allows additional bowel mobilization, especially in HD. In accordance with the adult experience, LAC seems to obviate stoma-related complications. Encouraged by our initial low morbidity rate, a prospective evaluation of this technique is planned.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".