One Bite or Two? A Prospective Trial Comparing Colonoscopy Biopsy Technique in Patients with Chronic Ulcerative Colitis
Bibliographic record
Abstract
BACKGROUND AND STUDY AIMS: Surveillance for mucosal dysplasia in patients with chronic ulcerative colitis requires numerous biopsies (often over 40). The aim of the present study was to determine if two biopsies could be obtained with jumbo forceps before removing them from the instrument (double biopsy technique), as opposed to one biopsy per pass, without sacrificing the histological quality of the biopsy material. METHODS: Twelve patients with chronic ulcerative colitis underwent colonoscopy, and four-quadrant biopsies were obtained at 10 cm intervals. For biopsies at each interval, two quadrants were obtained using the double biopsy technique and the other two quadrants were obtained individually. Two pathologists blinded to the biopsy technique examined each biopsy for technical and diagnostic qualities. The primary outcome was the histological adequacy in the evaluation of dysplasia. RESULTS: A total of 468 biopsies were obtained. A higher proportion of double-biopsy specimens were inadequate for dysplasia assessment compared with single-biopsy specimens (OR=2.78, 95% CI 1.37 to 5.59; P=0.005). In the double biopsy technique group, 14 samples were deemed inadequate due to actual tissue specimen loss, compared with eight samples in the single biopsy technique. However, when analysis was repeated using only the retrieved specimens, the double biopsy technique continued to be at higher risk of obtaining inadequate specimens (OR=14.5, 95% CI 2.1 to 98.7; P=0.006). CONCLUSIONS: The results of the present study suggest that the double biopsy technique is vulnerable to specimen loss and reduced histological quality, and the adoption of this technique as an equivalent method for tissue sampling may be premature.
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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 | 0.006 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".