DOZ047.22: FEED-EASY: feeding disorders in children with esophageal atresia study
Bibliographic record
Abstract
Abstract Introduction With advances in surgical and neonatal care, survival of patients with esophageal atresia (EA) has improved over time. While a number of conditions associated with EA may have an impact on feeding development (delayed primary anastomosis, anastomotic leaks, recurrent tracheoesophageal fistula, anastomotic stricture, gastroesophageal reflux, esophageal dysmotility, etc.) and although children with EA experience a number of oral aversive events in their first year of life, feeding disorders (FD) are poorly described and frequently unrecognized. The primary aim of this study was to describe FD in children born with EA, with a standardized scale. The secondary aim was to describe conditions associated with FD. Methods FEED-EASY is a multicentric French study. Parents of children born with EA between 2013 and 2016 in one of the 22 participating centers were asked to participate and received the French version of the standardized and reproductive ‘Montreal Children's Hospital Feeding Scale (MCH-FS)’. Results One hundred and forty-five children were included; 61 (42%) had FD according to the MCH-FS. These children were characterized by disinterest in food, oral hypersensitivity, difficulty in touching some textures and food avoidance, with an influence in quality of life. Nineteen (13%) were tube-fed between 1 and 4 years of age. Birth weight and chronic respiratory difficulties were associated with FD in children with EA. Anastomotic stricture (present in 31% of the included children) was not associated with FD. Conclusions FD is frequent and unrecognized in children with EA, and can influence growth and quality of life. MCH-FS allows pediatricians to identify FD in children with EA within a couple of minutes.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".