The Impact of Clinical Information on the Assessment of Endoscopic Activity: Characteristics of the Ulcerative Colitis Endoscopic Index Of Severity [UCEIS]
Bibliographic record
Abstract
BACKGROUND AND AIMS: To determine whether clinical information influences endoscopic scoring by central readers using the Ulcerative Colitis Endoscopic Index of Severity [UCEIS; comprising 'vascular pattern', 'bleeding', 'erosions and ulcers']. METHODS: Forty central readers performed 28 evaluations, including 2 repeats, from a library of 44 video sigmoidoscopies stratified by Mayo Clinic Score. Following training, readers were randomised to scoring with ['unblinded', n = 20, including 4 control videos with misleading information] or without ['blinded', n 20] clinical information. A total of 21 virtual Central Reader Groups [CRGs], of three blinded readers, were created. Agreement criteria were pre-specified. Kappa [κ] statistics quantified intra- and inter-reader variability. RESULTS: Mean UCEIS scores did not differ between blinded and unblinded readers for any of the 40 main videos. UCEIS standard deviations [SD] were similar [median blinded 0.94, unblinded 0.93; p = 0.97]. Correlation between UCEIS and visual analogue scale [VAS] assessment of overall severity was high [r blinded = 0.90, unblinded = 0.93; p = 0.02]. Scores for control videos were similar [UCEIS: p ≥ 0.55; VAS: p ≥ 0.07]. Intra- [κ 0.47-0.74] and inter-reader [κ 0.40-0.53] variability for items and full UCEIS was 'moderate'-to-'substantial', with no significant differences except for intra-reader variability for erosions and ulcers [κ blinded: 0.47 vs unblinded: 0.74; p 0.047]. The SD of CRGs was lower than for individual central readers [0.54 vs 0.95; p < 0.001]. Correlation between blinded UCEIS and patient-reported symptoms was high [stool frequency: 0.76; rectal bleeding: 0.82; both: 0.81]. CONCLUSIONS: The UCEIS is minimally affected by knowledge of clinical details, strongly correlates with patient-reported symptoms, and is a suitable instrument for trials. CRGs performed better than individuals.
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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 | 0.006 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".