Use of teduglutide in adults with short bowel syndrome–associated intestinal failure
Bibliographic record
Abstract
Short bowel syndrome (SBS) is a rare gastrointestinal disorder associated with intestinal failure (SBS-IF) and poor health-related outcomes. Patients with SBS-IF are unable to absorb sufficient nutrients or fluids to maintain significantly metabolic homeostasis via oral or enteral intake alone and require long-term intravenous supplementation (IVS), consisting of partial or total parenteral nutrition, fluids, electrolytes, or a combination of these. The goal of medical and surgical treatment for patients with SBS-IF is to maximize intestinal remnant absorptive capacity so that the need for IVS support may eventually be reduced or eliminated. Daily subcutaneous administration of the glucagon-like peptide 2 analog, teduglutide, has been shown to be clinically effective in reducing IVS dependence and potentially improving the health-related quality of life of patients with SBS-IF. The management of patients with SBS-IF is complex and requires close monitoring. This narrative review discusses the use of teduglutide for patients with SBS-IF in clinical practice. The screening of patient eligibility for teduglutide treatment, initiation, monitoring of efficacy and safety of treatment, adapting or weaning off IVS, and the healthcare setting needed for SBS-IF management are described, taking into consideration data from clinical trials, observational studies, and clinical experience.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".