P-15: A Specialized Multi-Disciplinary Clinic for Children With Esophageal Atresia/Tracheoesophageal Fistula (EA/TEF)
Bibliographic record
Abstract
Esophageal atresia with or without tracheoesophageal fistula (EA/TEF) is a congenital foregut anomaly that occurs in less than 1 in 3000 live births (O'Neill's 2004). Innovations and improvements in neonatal resuscitation and management have significantly improved survival of EA/TEF patients. These patients can be very complex due to their neonatal presentation (no antenatal diagnoses, variability in surgical interventions, associated anomalies and morbidities). Recognizing the complexity of these patients and the long-term follow up required, a Multi-Disciplinary clinic for EA/TEF patients was initiated at The Hospital for Sick Children in Toronto in 2013. A year following its implementation, we evaluated patient and family satisfaction with a centrally coordinated clinic. Using patient/family satisfaction surveys developed for out-patient clinics, we evaluated the effectiveness of the one stop clinic approach. Our Multi-Disciplinary clinic involved many services including specialists in pediatric surgery, neonatology, gastroenterology, respirology and cardiology. We focused on neurodevelopment, feeding and nutritional challenges & respiratory and airway management throughout the lifespan. We also focused on a safe transition from pediatrics to adult care with this complex patient population. Our evaluation is still in progress however early results indicate that parents are satisfied with the one stop shopping approach to clinic visit and the expertise this clinic is able to provide. We have a family centered approach using collaboration and sharing of expertise to provide essential continuity of care for this patient population.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.018 | 0.002 |
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".