A Simple Method to Improve Adenoma Detection Rate During Colonoscopy: Altering Patient Position
Bibliographic record
Abstract
BACKGROUND: Colonoscopy is currently considered to be the gold standard method for detecting and removing adenomatous polyps. However, tandem colonoscopy studies reveal a pooled polyp miss rate of 22%. OBJECTIVE: A prospective randomized trial was conducted to assess whether alteration of patient position during colonoscopy withdrawal increases the adenoma detection rate (ADR). METHOD: The study group included 120 patients who presented for elective colonoscopic examination. After reaching the cecum, patients were randomly assigned in a 1:1 ratio to examination in either the left lateral position or other positions (left lateral position for the cecum, ascending colon and hepatic flexure; supine for transverse colon; and supine and right lateral position for splenic flexure, descending and sigmoid colon) first. Examination of the colon was performed segment by segment. The size, morphology and location of all polyps were recorded. Polyps were removed immediately after examination of a colon segment when all positions were completed. ADR and polyp detection rates (PDR) were calculated. RESULTS: A total of 102 patients completed the study. Examination in the left lateral position revealed 66 polyps in 31 patients (PDR 30.3%) and 42 adenomas in 24 patients (ADR 23.5%). PDR increased to 43.1% (81 polyps in 44 patients) and the ADR to 33.3% (53 adenomas in 34 patients) after the colon was examined in the additional positions (P<0.001 and P=0.002, respectively). The increase in the number of adenomas detected was statistically significant in the transverse and sigmoid colon. The addition of position changes led to a 9.8% increase in the ADR in the transverse colon, splenic flexure, and descending and sigmoid colon. The frequency of surveillance interval was shortened in nine (8.8%) patients after examination of the colon in dynamic positions. CONCLUSION: Alteration of patient position during colonoscopy withdrawal is a simple and effective method to improve ADR.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".