Laparoscopic Full-Thickness Intestinal Biopsies in Children
Bibliographic record
Abstract
BACKGROUND: Laparoscopy may reduce postoperative pain and hospital stay, compared with laparotomy. The use of laparoscopic surgery to obtain full-thickness intestinal biopsies in children has not been previously reported. METHODS: Eleven children aged 1.6 to 19 years (median, 4.5 years) underwent laparoscopic full-thickness biopsy of the stomach, small bowel, colon, or a combination thereof. Each procedure used one 12-mm and two 5-mm ports. RESULTS: Eight children with obstructive symptoms after a pull-through for Hirschsprung disease underwent multiple colon and small bowel biopsies (range, 3-6; median, 5); intestinal neuronal dysplasia was found in two. Two patients with cystic fibrosis had diffuse colonic narrowing; a diagnosis of enzyme-induced fibrosing colonopathy was made in one and nonspecific inflammation was found in the other. One child had a thickened stomach, and a gastroscopic-directed full-thickness biopsy revealed plasmacytoma. Nine of the 11 patients had a previous laparotomy, and ports were placed through preexisting scars. Median hospital stay was 2 days. No patient required more than 24 hours of narcotics. There were no leaks, and no other morbidity or mortality occurred. None of the patients required conversion to an open procedure. Biopsy results significantly affected treatment for each patient. CONCLUSIONS: Laparoscopic full-thickness intestinal biopsy is safe and effective for a variety of gastrointestinal problems in children. This technique is associated with a short hospital stay, minimal pain, and a very low risk of complications and can be performed even in patients who have had a previous laparotomy.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".