Predictors of 1‐year enteral autonomy in children with intestinal failure: A descriptive retrospective cohort study
Bibliographic record
Abstract
INTRODUCTION: The International Intestinal Failure Registry (IIFR) is an international consortium to study intestinal failure (IF) outcomes in a large contemporary pediatric cohort. We aimed to identify predictors of early (1-year) enteral autonomy. METHODS: We included IIFR pilot phase patients. IF was defined by a parenteral nutrition need for at least 60 days due to a primary gastrointestinal etiology. The primary outcome was time to enteral autonomy achievement. We built a mixed-effects Weibull accelerated failure time model with random effects by center to analyze variables associated with enteral autonomy achievement with a primary outcome of time ratio (TR). RESULTS: We included 189 patients (82% with short bowel syndrome) representing 11 international centers. Cumulative incidence of early enteral autonomy was 51.6%, and death was 6.5%. In multivariable analysis, ostomy presence (TR, 2.63; 95% CI, 1.41-4.90) was associated with increased time to enteral autonomy achievement, and Asian/Indian (TR, 0.28; 95% CI, 0.10-0.81) and Pacific Islander race (TR, 0.34; 95% CI, 0.13-0.90) were associated with decreased time to enteral autonomy achievement. In a second model in the subset with measured percentage of bowel length remaining, ostomy presence (TR, 4.21; 95% CI, 1.90-9.33) was associated with increased time to enteral autonomy achievement, whereas greater percentage of bowel remaining (TR, 0.96; 95% CI, 0.94-0.98) was associated with decreased time to enteral autonomy achievement. CONCLUSIONS: Minimizing bowel resection at initial surgery and establishing bowel continuity by ostomy reversal can effectively decrease the time to early enteral autonomy achievement in children with IF.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".