The Development of the International Intestinal Failure Registry and an Overview of its Results
Bibliographic record
Abstract
Pediatric intestinal failure (IF) is a rare disease that represents an evolving field in pediatric gastroenterology and surgery. With only a limited number of multicenter collaborations, much of the research in pediatric IF is often confined to single-center reports with small sample sizes. This has resulted in challenges in data interpretation and left many knowledge gaps unanswered. Over the past two decades, five large multicenter collaborations, primarily from North America and Europe, have published their findings. Apart from one ongoing European adult and pediatric registry, these relatively large-scale efforts have been concluded.In 2018, the International Intestinal Failure Registry (IIFR) was initiated by the International Intestinal Rehabilitation and Transplant Association to continue these efforts and answer some of the knowledge gaps in pediatric IF. The IIFR goals are to prospectively assess the natural history of children diagnosed with IF and creating a worldwide platform to facilitate benchmarking and evidence-based interventions in pediatric IF. A pilot phase involving 204 enrolled patients was initiated in 2018 to assess the feasibility of an international IF registry and refine the study protocol and data collection forms. Following the successful completion of this phase, the current phase of the IIFR was launched in 2021. As of May 2023, the registry includes 362 prospectively followed children from 26 centers worldwide. This review provides an overview of the development, structure, and challenges of the IIFR, as well as the main findings from both the pilot and current phase.
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 | 0.045 | 0.049 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.010 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".