Exclusive enteral nutrition for children with Crohn's disease: Use in Australia and attitudes of Australian paediatric gastroenterologists
Bibliographic record
Abstract
AIM: Although available data support a role for exclusive enteral nutrition (EEN) in children with Crohn's disease (CD), use of this therapy varies. The aim of this study was to define the patterns of use of EEN across Australia and to better understand the reasons for this variation. METHODS: Using an existing email network, Australian paediatric gastroenterologists were asked to provide details of their attitudes towards, and use of, EEN in children. A questionnaire was designed to direct responses, with regard to use of EEN, to current EEN protocols and patterns of use. RESULTS: Twenty-one replies were received (58% response). Although 12 respondents felt that EEN was an appropriate therapy for CD, only 8 regularly used EEN for their patients. Usage varied between states and within units. Current use was related to practitioners' experiences of EEN during their gastroenterology training. The concerns of those who did not recommend EEN included compliance, cost and resource demands. The doctors who recommend EEN reported that family support, team approach and disease location were important factors for a positive outcome from EEN. Current protocols varied in terms of type of formula, length of therapy and use of concurrent medications. CONCLUSIONS: Variations in care were illustrated across these paediatric gastroenterologists. Practitioners have many reasons and concerns about the use of EEN: these impede the wider use of EEN for paediatric CD. More consistent protocols for the use of EEN and an improved understanding of the mechanisms of EEN could lead to enhanced use of this therapy.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".