Effect of Standardised Scoring Conventions on Inter-rater Reliability in the Endoscopic Evaluation of Crohn’s Disease
Bibliographic record
Abstract
BACKGROUND AND AIMS: The Crohn's Disease Endoscopic Index of Severity [CDEIS] and Simplified Endoscopic Score for Crohn's Disease [SES-CD] demonstrate consistent overall intra- and inter-rater reliability. However, the reliability of some index items is relatively poor. We evaluated scoring conventions to improve the reliability of these items. METHODS: Five gastroenterologists with no previous experience scoring the CDEIS or SES-CD were trained on their use. A total of 65 video recordings of colonoscopies were scored blindly by each gastroenterologist before and after additional training on index scoring conventions. Intra-class correlation coefficients [ICCs] assessed the effect of application of these conventions on the reliability of the CDEIS, SES-CD, and a Global Evaluation of Lesion Severity [GELS] score. RESULTS: Following training on scoring conventions, inter-rater ICCs (95% confidence interval [CI]) for the total SES-CD score increased from 0.78 [0.71, 0.85] to 0.85 [0.79, 0.89]. The ICCs for the total CDEIS and GELS scores were not affected: corresponding inter-rater ICCs were 0.74 [0.65, 0.81] and 0.49, [0.38, 0.61] before and 0.73 [0.65, 0.81] and 0.53 [0.42, 0.64] following application of scoring conventions. Estimations of ulcer depth, surface area, anatomical location, and stenosis were important sources of variability. CONCLUSIONS: Use of scoring conventions previously developed by expert central readers enhanced the reliability of the SES-CD but did not similarly affect the CDEIS or GELS. As the SES-CD is more likely to be reliable than the CDEIS and can be optimised with targeted training, it is the preferred instrument for use in clinical trials.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 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".