P191 Systematic review and meta-analysis: Patient-reported outcomes and endoscopic appearance in ulcerative colitis
Bibliographic record
Abstract
To evaluate the association of the patient-reported outcomes rectal bleeding and stool frequency with mucosal healing in ulcerative colitis (UC). A systematic review of studies reporting the association of patient-reported outcomes and mucosal healing was conducted. Diagnostic accuracy meta-analysis was performed using the hierarchical bivariate method. Five studies were included with a total of 2132 participants. For rectal bleeding subscore of 0, the pooled sensitivity was 81% (95% confidence interval (CI): 73–86%), specificity 68% (95% CI: 61–75%), positive likelihood ratio (LR) 2.5 (95% CI: 2.2–3.0), and negative LR 0.28 (95% CI 0.22–0.37). For stool frequency subscore of 0, the pooled sensitivity was 40% (95% CI: 25–58%), specificity 93% (95% CI: 86–97%), positive LR 6.0 (95% CI: 3.7–9.7), and negative LR 0.64 (95% CI 0.50–0.82). For combined rectal bleeding and stool frequency subscores of 0, the pooled sensitivity was 36% (95% CI: 22–54%), specificity 96% (95% CI: 91–98%), positive LR 8.4 (95% CI: 5.5–12.8), and negative LR 0.66 (95% CI 0.53–0.84). Forest plots of coupled sensitivity and specificity of combined rectal bleeding and stool frequency subscores = 0 for mucosal healing UC patients with normal rectal bleeding and stool frequency subscores likely have attained mucosal healing. Rectal bleeding is often absent in those with mucosal healing. Normal stool frequency predicts mucosal healing, but often remains abnormal in patients despite mucosal healing.
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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 | 0.011 | 0.037 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.017 | 0.040 |
| Bibliometrics | 0.008 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 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".