Decision tree for early introduction of rescue therapy in active ulcerative colitis treated with steroids
Bibliographic record
Abstract
BACKGROUND: Corticosteroids are the treatment of choice for moderate-to-severe active ulcerative colitis (UC) but up to 30%-40% of patients fail to respond. It has been reported that early clinical-biological parameters may identify those patients at high risk of colectomy. The aim was to identify predictors of rapid response to systemic steroids in moderate-to-severe attacks of UC. METHODS: Consecutive patients treated with prednisone 1 mg/kg/day for moderate-to-severe attacks of UC were prospectively included. Clinical and biological parameters at 3 and 7 days after starting steroids were recorded. Response was defined as mild or inactive UC activity at day 7 (as assessed by the Montreal Classification of severity) together with no need for rescue therapies (cyclosporin, infliximab, or colectomy). A logistic regression analysis was performed to identify those independent predictors of response. In addition, a decision-tree analysis was also performed. RESULTS: Sixty-eight percent of patients (64 out of 94) responded to steroids. In the univariate analysis the number of bowel movements, rectal bleeding, platelet count, and C-reactive protein (CRP) levels at day 3 were associated with response at day 7, but only rectal bleeding was found to be an independent predictor in the logistic regression analysis. Conversely, the classification and regression tree (CART) model included these four variables. The decision-tree model showed a higher sensitivity in predicting a rapid response to steroids than the logistic regression one. CONCLUSIONS: Rapid response to steroids in active UC attacks can be predicted after 3 days of treatment by simple clinical and biological parameters. A decision-tree model for early introduction of rescue therapies is provided.
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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 | 0.000 |
| 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".