Development and Investigation of a Non-invasive Disease Severity Index for Inflammatory Bowel Disease
Bibliographic record
Abstract
INTRODUCTION: The disease severity index (DSI) encapsulates the inflammatory bowel disease (IBD) burden but requires endoscopic investigations. This study developed a non-invasive DSI using faecal calprotectin (DSI-fCal) and faecal myeloperoxidase (DSI-fMPO) instead of colonoscopy. METHODS: Adults with IBD were recruited prospectively. Baseline biomarker concentrations were used to develop DSI-fCal and DSI-fMPO, and these were correlated with the original DSI, IBD-symptoms, endoscopic activity, and quality-of-life (QoL). Area under the receiver-operating-characteristics curves (AUROC) assessed DSI-fCal/DSI-fMPO as predictors of clinical and biochemical remission at six months (symptom remission and fCal <150 μg/g, respectively), and a complicated IBD-course at 24 months (disease relapse needing escalation of biologicals/immunomodulators/recurrent corticosteroids, IBD-hospitalisations/surgeries). Multivariable logistic regression assessed the utility of DSI-fCal/DSI-fMPO in predicting a complicated IBD-course at 24 months. RESULTS: In total, 171 patients were included (Crohn's disease=99, female=90, median age=46y (IQR 36-59)). DSI-fCal and DSI-fMPO correlated with the original DSI (r>0.9, p<0.001), endoscopic indices (r=0.45-0.49, p<0.001), IBD-symptoms (r=0.53-0.58, p<0.001) and QoL (r=-0.57-0.58, p<0.001). Baseline DSI-fCal (AUROC=0.79, 95% CI 0.65-0.92) and DSI-fMPO (AUROC=0.80, 95% CI 0.67-0.93) were associated with 6-month clinical and biochemical remission. DSI-fCal (AUROC=0.83, 95% CI 0.77-0.89) and DSI-fMPO (AUROC=0.80, 95% CI 0.73-0.87) performed similarly in predicting a complicated IBD-course to the original DSI (pdifference>0.05). The non-invasive DSI was independently associated with a complicated IBD-course on multivariable analyses (DSI-fCal28, aOR=6.04, 95% CI 2.42-15.08; DSI-fMPO25, aOR=7.84, 95% CI 2.96-20.73). CONCLUSIONS: The DSI-fCal and DSI-fMPO perform similarly in prognosticating the longitudinal disease course as the original DSI, whilst avoiding a need for an endoscopic assessment.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".