Histologic Evaluation of Ulcerative Colitis
Bibliographic record
Abstract
BACKGROUND: Ulcerative colitis (UC) is an idiopathic inflammatory disorder. Currently, the main goals of treatment are to induce and maintain clinical and/or endoscopic remission. However, evidence indicates that persistent disease activity on colonic biopsies in the setting of clinical or endoscopic remission is an independent predictor of poor outcomes. A number of previous studies have proposed histologic indices for use in specific trials of UC. The aim of this study was to systematically review the existing histological indices for UC and assess their potential use in both patient management and clinical trials. METHODS: We performed a systematic review of histological indices evaluating disease activity in UC. MEDLINE (Ovid), EMBASE (Ovid), PubMed, the Cochrane Library (CENTRAL), and Digestive Diseases Week (DDW) abstracts of randomized and/or controlled trials clinical trials were searched from inception to February 2013 for applicable studies. Data from these studies were reviewed and analyzed. RESULTS: After systematically applying inclusion criteria, we identified 108 scientific articles including 88 clinical studies and 21 related clinical reviews. Eighteen indices of histological activity in UC were identified and reviewed. CONCLUSIONS: Although multiple histological scoring indices for assessment of UC disease activity currently exist, none of these instruments were developed using a formal validation process and their operating properties remain poorly understood. Future studies are needed to address this deficiency.
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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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.011 | 0.008 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".