The Optimal Timing of Intestinal Transplantation for Children With Intestinal Failure
Bibliographic record
Abstract
In Brief Objective: Identify an optimal approach to the timing of intestinal transplantation for children dependent on total parenteral nutrition (PN). Summary Background Data: Children with short bowel syndrome are frequently dependent on PN for growth and development. Intestinal transplantation is often considered after PN-related complications occur, but optimal timing of transplantation is controversial. Methods: A Markov analytic model was used to determine life expectancy (LY) and quality-adjusted life years on a theoretical cohort of 4-year-old subjects for two treatment strategies: (1) standard care consisting of PN and referral to transplantation according to accepted guidelines and (2) early listing for isolated small intestine transplantation. Results: Early listing for intestinal transplantation was associated with 0.27 additional life years (13.16 vs. 12.89) and 0.76 additional quality-adjusted life years (10.51 vs. 9.75) as compared with current standard care. The unadjusted analysis was sensitive to the development of PN-associated liver disease, at a threshold of approximately 11% per year, and its related probability of dying at a threshold of 80% 2-year mortality. Early listing for transplantation was the dominant strategy until the probability of late bowel rejection reached 35% per year. Conclusions: Children with short bowel syndrome dependent on PN should be considered for intestinal transplantation earlier than what is current practice. The timing of intestinal transplantation in patients with intestinal failure is controversial. In this study, a Markov model was developed to compare early listing for intestinal transplantation against standard care, consisting of parenteral nutrition (PN) and delayed transplantation if necessary. Intestinal transplantation has reached a state of clinical equipoise with PN, and quality of life should be considered in the timing decision for transplantation.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.001 |
| 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".