P-12: Nutritional Morbidity Following Surgical Repair in Esophageal Atresia/Trachoesophageal Fistula Patients
Bibliographic record
Abstract
Nutritional morbidity has been reported in infants with esophageal atresia/trachoesophageal fistula (EA/TEF). Thoracoscopic repair is associated with lower height z-scores in the first year of life and gastro-esophageal reflux disease (GERD) is associated with lower BMI in older children. This study attempts to explore EA-related nutritional morbidity during infancy. Single center, retrospective review of repaired EA/TEF infants from Jan. 2011–Mar. 2014 including EA type, co-morbidities, anthropometrics and nutritional interventions. Statistical analysis performed with Stata® 12.0. Of 35 EA/TEF cases: 11% type A, 3% type B, 77% type C, 9% type E; 46% were premature, 37% had VACTERL associations. Most were repaired by thoracotomy (91%) so type of repair was not examined. Weight z-scores from birth to first follow-up improved (p = 0.03) with those on promotility drugs (63%) having a trend towards lower weight z- scores at discharge (p = 0.06) despite receiving similar calories. Overall calorie intake was within estimated energy expenditures (EER). However, calorimetry (n = 13) revealed resting energy expenditures of 15 ± 26% higher than predicted. Calorie intake did not differ with presence of VACTERL association, whereas calorie intake and prematurity trended towards significance (p = 0.06). At discharge, 40% required nutrition via enterostomy tube; these patients received significantly more calories than those without tubes (p < 0.05). Nutritional morbidities in EA/TEF infants are complex and the current review is limited by the small sample size. Mean EER appears to be within expected norms, but calorimetry suggests a potential for higher than expected caloric requirements. Further assessments are required.
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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 | 0.000 | 0.001 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".