Characteristics of adult intestinal failure centers: An international multicenter survey
Bibliographic record
Abstract
BACKGROUND: Current guidelines recommend that patients with chronic intestinal failure (CIF) should be managed by a multidisciplinary team (MDT). However, the characteristics of real-world IF centers and the patients they care for are lacking. The study aims to describe IF center characteristics as well as characteristics of patients with CIF across different global regions. METHODS: This is an international multicenter study of adult IF centers using a survey. The questionnaire survey included questions regarding program and patient characteristics. Thirty-three investigational centers were invited to participate. Each center was asked to answer the survey questions as one MDT. RESULTS: The survey center response rate was 91%. The median number of patients with CIF per center was 128 (range, 30-380). The most common disciplines reported were gastroenterologist (93%), dietitian (90%), nurse (83%), and advanced practitioner (nurse practitioner and physician assistant, 77%). There were centers that did not have a pharmacist, surgeon, psychologist, and social worker (30%, 37%, 60%, and 70%, respectively). The median full-time equivalents (FTEs) per 100 patients were 1.1 for nurses, 1 for dietitians, 1 for advanced practitioners, and 0.9 for gastroenterologists. Short bowel syndrome was the most common cause of CIF (50%) followed by intestinal dysmotility (20%). CONCLUSION: The majority of centers were managing around 100 patients with CIF. Despite the widespread use of the MDT, there are some variances in team characteristics. Gastroenterologists were the most common physicians supporting MDTs. In IF centers, one FTE of each core discipline was supported to manage 100 patients with CIF.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".