Predictive Validity of the TIGER Score for Daily-Life Disease Burden, Complications, and Medication Use in Inflammatory Bowel Disease After 12 Months
Bibliographic record
Abstract
INTRODUCTION: The Toronto Inflammatory Bowel Disease (IBD) Global Endoscopic Reporting (TIGER) score was developed to provide 1 endoscopic scoring index for patients with both Crohn's disease (CD) and ulcerative colitis (UC). The goal of this study was to assess the predictive validity the TIGER score for daily-life disease burden (IBD Disk) and disease complications. METHODS: A prospective 12-month study was conducted in 1 tertiary IBD center. Baseline colonoscopy was performed. Moderate-to-severe mucosal involvement was defined as a TIGER score ≥100, Simple Endoscopic Score for CD >6, Mayo Endoscopic Score >1, and was used as a predictor for clinical outcomes. At each visit, IBD Disk questionnaires, disease complications, hospitalizations, surgeries, and medications were documented. RESULTS: A total of 107 adults, 52 with CD and 55 with UC, were included. Patients with a baseline TIGER score ≥100 had a significantly higher prevalence of an IBD Disk score ≥40 after the 12-month follow-up period despite receiving advanced therapy (33.9% vs 7.8%, P < 0.001). There were significantly more patients with a baseline TIGER score ≥100 who experienced at least 1 hospitalization (39.3% vs 2.0%, P < 0.001), underwent surgery (14.3% vs 0.0%, P < 0.005), had IBD-related complications (41.1% vs 9.8%, P < 0.001), and required steroids (67.9% vs 5.9%, P < 0.001) or advanced therapy (85.7% vs 7.8%, P < 0.001). Similar significant results were obtained with Simple Endoscopic Score for CD and Mayo Endoscopic Score as predictors of outcomes over the 12 months. DISCUSSION: The TIGER score is a simple endoscopic score for patients with CD and UC with an adequate predictive validity for worse clinical outcomes while having noninferiority to the current best-referenced endoscopic scores.
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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 | 0.000 | 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 | 0.001 |
| 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".