Real-world experience of Teduglutide use in adults with short bowel syndrome: A seven-year international multicenter survey
Bibliographic record
Abstract
BACKGROUND AND AIM: Teduglutide is a glucagon-like peptide-2 analogue used to promote intestinal rehabilitation and decrease the dependence from intravenous supplementation (IVS) in patients with short bowel syndrome and intestinal failure (SBS-IF). The aim of this study was to gain a better understanding of international real-world Teduglutide use since its launch. METHODS: Data from an international multicenter database for chronic IF were analysed. All the adult patients with SBS-IF included by centers that treated at least one patient with Teduglutide during the study period (2015-2022) were investigated. The baseline characteristics and the outcome of patients treated with Teduglutide (n.269) were compared to those of patients not receiving the drug (Controls, n.3081). The center experience was categorized based on the number of patients treated with Teduglutide: <10 or ≥10. RESULTS: Teduglutide cohort exhibited higher male prevalence, younger age, longer duration of HPN, higher percentage of SBS with jejunocolonic anastomosis, lower IVS volume, improved oral intake, and higher percentage of patients weaned from IVS. Controls showed higher percentages of patients deceased or lost to follow up. Centers with ≥10 patients treated with Teduglutide showed higher weaning rates and lower mortality rates. CONCLUSIONS: This is the largest analysis of Teduglutide's real-world setting in SBS-IF. Clinicians preferentially selected for treatment patients with better prognostic indicators. Outcomes were significantly better in centers with higher Teduglutide treatment volumes, emphasizing the need for specialized referral centers to optimize care for SBS-IF patients.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".