Capsule Endoscopy Versus Colonoscopy in Patients With Previous Colorectal Surgery: A Prospective Comparative Study
Bibliographic record
Abstract
BACKGROUND: Colonic capsule endoscopy (CCE) derived from the video capsule endoscopy, initially proposed to explore the small bowel, has demonstrated high sensitivity and specificity for colonic polyp detection. The primary outcome of the study was to assess the safety, feasibility, and reliability of CCE after colorectal surgery. Secondary outcomes were to identify the detection rate of colonic lesions and recognition of the surgical anastomosis as compared to colonoscopy. METHODS: This is a prospective single-center study conducted over a 2-year period. Thirty-seven patients with a history of colorectal surgery were prospectively included in this study. Each patient received both CCE and colonoscopy, performed by different operators blinded to each other's results. RESULTS: Thirty-two patients (86.5%) completed the study and were included in the final analysis. All capsules were naturally expelled. In three patients (9.4%), the anal verge was not identified during the CCE recording and the examination of the colon was considered incomplete. Surgical anastomosis was accurately identified by CCE in 78.2% of the patients versus 93.8% for colonoscopy (P = 0.65). Thirty-eight lesions were detected in 14 patients. The sensitivity of CCE to detect colonic polyps was 95.2% (95% confidence interval (CI): 77.3-99.2%), the specificity 82.4% (95% CI: 59.0-93.8%). Positive predictive value (PPV) and negative predictive value (NPV) of CCE to detect colonic polyps were 87.0% and 93.3%, respectively. No complications related to the passage of the capsule through the intestinal anastomosis were detected. CONCLUSIONS: CCE proved to be safe and feasible, reporting a similar detection rate of colonic lesion compared to colonoscopy.
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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 | 0.003 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".