The Gap in Referral Criteria for Pediatric Intestinal Transplantation
Bibliographic record
Abstract
BACKGROUND: Advancement in treatment of children with intestinal failure did not lead to change in generally accepted referral criteria for intestinal transplantation. Therefore, a study was conducted to evaluate the current referral criteria and to identify potential new criteria for pediatric intestinal transplantation among transplant centers in Europe, the United States, and Canada. METHODS: The literature was searched to identify discussion points regarding current referral criteria and potential needs for extension. Questionnaires were sent to 50 centers performing pediatric intestinal transplantation. Close-ended questions were analyzed with descriptive statistics. Open-ended questions were analyzed by two reviewers using the thematic analysis method. Data were analyzed with SPSS version 17. RESULTS: A total of 18 questionnaires were completed (response rate, 36%; 14 centers in Europe and 4 centers in the United States and Canada). Of all the respondents, 77% considered referral of children as too late and suggested that education of referring hospitals could improve this. Of all the respondents, 50% considered the current referral criteria as too general. More specifically, respondents suggested that "persistent hyperbilirubinemia" must be defined by a time-and-value limit and that the list of referral criteria should include recurring septic episodes and fluid/electrolyte disturbances. CONCLUSIONS: Referral criteria for pediatric intestinal transplantation can be improved by defining more specified decision moments and by educating referring hospitals.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.028 | 0.064 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.002 |
| 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".