Reporting trends of right-sided hyperplastic and sessile serrated polyps in a large teaching hospital over a 4-year period (2009–2012)
Bibliographic record
Abstract
AIM: An audit of serrated polyps diagnosed over a 4-year period: 2009 to 2012 was undertaken to ascertain the reporting trends of sessile serrated polyps (SSP). METHODS: All right sided hyperplastic polyps (HP) proximal to the splenic flexure and all polyps designated SSP were retrieved from the study period. Three pathologists blinded to the original diagnosis re-examined the slides. Recent American College of Gastroenterology guidelines for the diagnosis of SSP was utilised. RESULTS: No cases of SSP were diagnosed in 2009. In 2010, 32 right-sided cases were encountered, 83 confirmed in 2011 and 134 confirmed in 2012. The vast majority of these were right-sided. With regards to right-sided HP that were re-classified as SSP the data is as follows: 20 of 66 in 2009 (30%); 58 of 91 in 2010 (64%); 42 of 106 (40%) in 2011 and 69 of 206 in 2012 (33%). CONCLUSIONS: This study has demonstrated an almost exponential increase in the diagnosis of SSP over a 4-year period. In addition, 30 to 64% of right-sided HP were re-classified as SSP over the 4-year period suggesting that greater awareness of the diagnostic criteria for SSP is required. SSP is an important precursor lesion in the serrated pathway of colorectal cancer. Its recognition is important for surveillance and therapeutic strategies.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".