Appropriate timing and interval for surveillance colonoscopy after liver transplantation based on a single-centre experience
Bibliographic record
Abstract
Background: Colon cancer surveillance post liver transplantation (LT) is generally recommended. This study aimed to determine the appropriate timing for the first colonoscopy after LT and the interval for subsequent surveillance colonoscopies based on our single-centre real-world experience. Methods: The medical records of patients who underwent LT at Pusan National University Yangsan Hospital between December 2008 and March 2024 were reviewed. Patients who underwent colonoscopy at least once after LT were analyzed. After the first post-transplant colonoscopy, subsequent colonoscopies were divided into an intensive and a nonintensive surveillance group based on a 3-year interval. Results: A total of 404 LT recipients with 1,076 colonoscopies were analyzed. The analysis included pre-transplant (n = 219), first post-transplant (n = 404), and subsequent colonoscopies (n = 453). Cecal intubation failure and poor bowel preparation were higher in the pre-transplant colonoscopy than the post-transplant colonoscopy (3.2% versus 0.8%, p = 0.010; 13.2% versus 4.4%, p < 0.001). Although high-risk polyps were resected in 17 recipients (7.8%) through pre-transplant colonoscopy, they were also discovered in 17 recipients (4.2%) at the first post-transplant colonoscopy. There were no differences in malignancy or high-risk polyp detection between recipients who underwent intensive surveillance (median interval, 22 months) after the first post-transplant colonoscopy and those who did not (median interval, 52 months; 0.6% versus 2.1%, p = 0.381 and 3.7% versus 2.1%, p = 0.598). Conclusions: Colonoscopy prior to LT may be insufficient; therefore, the first colonoscopy after LT should be performed within 1 year. Subsequent colonoscopies should follow the general surveillance interval.
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".