The Positioning of Colectomy in the Treatment of Ulcerative Colitis in the Era of Biologic Therapy
Bibliographic record
Abstract
The position of surgery in the treatment of ulcerative colitis (UC) has changed in the era of biologics. Several important questions arise in determining the optimal positioning of surgery in the treatment of UC, which has long been a challenge facing gastroenterologists and surgeons. Surgery is life-saving in some patients and leads to better bowel function and better quality of life in most patients. The benefits of surgery, however, must be weighed against the potential surgical morbidity and compromised functioning that clearly can occur. The introduction of biologic therapy has added further complexity to decisions about medical management, surgery, and the relative timing of these choices. Appropriate medical management of UC may induce and maintain remission and may prevent surgery. However, medical management also carries risks of adverse effects, and recent data suggest that delay of surgery during ineffective medical therapy can increase the chances of negative surgical outcomes. To make individualized timely treatment decisions, early collaboration between gastroenterologists and surgeons is important and more data on predictors of treatment response and positive outcomes are needed. Early identification of patients who would benefit from biologic therapy or surgery is challenging.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".