KODA score: an updated and validated bowel preparation scale for patients undergoing small bowel capsule endoscopy
Bibliographic record
Abstract
Abstract Background and study aims A reliable outcome measure is needed for bowel preparation quality during capsule endoscopy. Currently, no scales are adequately validated. Our objective was to update an existing small bowel preparation score, create a standardized training module, then determine its inter-rater and intra-rater reliability. Patients and methods Modification to produce standardized scoring of an existing small bowel preparation score was performed followed by development of a training module and validation to create the new Korea-Canada (KODA) score. Twenty readers from a range of backgrounds, including capsule endoscopists, gastroenterology fellows, residents, medical students, and nurses rated bowel cleanliness in 25 capsule videos consisting of 1,233 images, in duplicate 4 weeks apart, after completing the training module. Sequential images selected in 5-minute intervals during small bowel transit were rated on a scale between 0–3 based on the amount of visualized mucosa and the degree of obstruction. Reliability was assessed using estimates of intraclass correlation coefficients (ICCs). Results Intraclass correlation coefficients for inter-rater (ICC 0.81, 95 % CI 0.70–0.87) and intra-rater (ICC 0.92, 95 % CI 0.87–0.94) reliability were almost perfect among the 20 readers. Inter-rater reliability ranged between 0.72 (95 % CI 0.57–0.81) and 0.89 (95 % CI 0.79–0.93) for nurses and residents, respectively. Intra-rater reliability was greater than 0.90 for all groups except for nurses, which was still almost perfect (ICC 0.86, 95 % CI 0.79–0.90). Conclusions Almost perfect inter-rater and intra-rater reliability was observed for the KODA score. This simple score could be used for future clinical trials after completion of the training module.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".