Categorising Endoscopic Severity of Crohn’s Disease Using the Modified Multiplier SES-CD [MM-SES-CD]
Bibliographic record
Abstract
BACKGROUND AND AIMS: Current endoscopic scoring indices such as the Simple Endoscopic Score for Crohn's Disease [SES-CD] quantify the degree of mucosal inflammation in Crohn's disease [CD] but lack prognostic potential. The Modified Multiplier of the SES-CD [MM-SES-CD] quantifies the endoscopic burden of CD and can be accessed online [https://www.mcmasteribd.com/mm-ses-cd]. This analysis aims to establish MM-SES-CD thresholds that classify CD endoscopic burden into inactive/very mild, mild, moderate, and severe disease based on the probability of achieving endoscopic remission [ER] on active therapy at 1 year. METHODS: This post-hoc analysis included pooled data from three CD clinical trials [n = 350 patients, baseline SES-CD ≥3 with ulceration]. Disease category severity was determined using the maximum Youden Index. Achievement of ER between severity categories was compared using chi square tests. Time to clinical remission [CR] was compared using Kaplan-Meier survival curves. RESULTS: MM-SES-CD severity categories were established as very mild/remission [score <14], mild [≥14 to <31], moderate [≥31 to <45], and severe [≥45], which were predictive of 1-year ER [50%, 30.3%, 21.7%, 8.8%, respectively, p <0.001]. Lower MM-SES-CD scores had numerically higher rates of 1-year clinical remission [CR], and time to 1-year CR was superior to those with higher scores [p = 0.0492]. MM-SES-CD thresholds for achieving 1-year ileal ER among 75 patients with isolated ileal disease were established as mild [score <14], moderate [≥14 to <33], and severe [≥33], which were predictive of 1-year ER [66.7%, 33.3%, 13.3%, respectively, p = 0.027]. CONCLUSIONS: We have established numerical MM-SES-CD cut-offs that categorise endoscopic disease severity and have demonstrated that they are prognostic for 1-year ER and CR.
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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 | 0.013 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".