Pediatric gastrostomy feeding tube weaning strategies: A scoping review
Bibliographic record
Abstract
Pediatric feeding tubes (FTs) are used to support nutrition and hydration needs, but ought to be weaned when children are able to eat safely by mouth to maintain growth. We performed a scoping review of FT weaning interventions for children (<21 years) dependent on long-term FTs. Study design, patient characteristics, intervention strategies, setting, duration, interventionist(s), primary study measures, short-term and long-term outcomes are described. Two independent reviewers extracted all data and came to consensus using the Joanna Briggs Institute methodology; a third reviewer resolved discrepancies as needed. Forty-five articles met the inclusion criteria. Most interventions took place in outpatient or inpatient settings, although home, telemedicine, and school settings were also represented. The majority of interventions were led by interdisciplinary teams. Strategies varied and were used in combination, most commonly: parent training and/or education, hunger provocation, and behavioral approaches. Most interventions weaned a majority of children to oral feeding, often with additional success in follow-up; a handful of studies demonstrated that a minority of patients required resumption of FT after initially weaning. Successful programs weaning children from FTs to oral feeding have occurred across various environments involving heterogeneous teams and strategies. Nearly all interventions involve a combination of strategies, parent training and/or education, and three or more interventionists, demonstrating the complexity of weaning programs. To establish best practices for weaning children from FTs when medically safe to do so, future work ought to establish standard measurement tools for treatment outcomes.
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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 | 0.010 | 0.036 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.012 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.001 |
| 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".