Outcomes of the international database on SARS-CoV-2 infections in children with Esophageal Atresia/Tracheoesophageal Fistula
Bibliographic record
Abstract
Background and Aim To assess the outcomes of children born with esophageal atresia/tracheoesophageal fistula (EA-TEF) with concomitant SARS-CoV-2 infection. Methods An international survey was circulated to the International Network of Esophageal Atresia ( INoEA) members from April 2020 to May 2022. Information on demography, type of EA-TEF, co-morbidities, complications, hospitalization, and therapies administered for SARS-CoV-2 infection was collected for all patients. Results Forty-two patients from April 2020-May 2022, with a mean age of 6.8 years were reported from Argentina, Switzerland, Netherlands, Canada, France, Italy, Australia and Turkey. 34 patients (81%) had a type C, EA-TEF. 30 had respiratory comorbidities, 14 had associated cardiac malformations and 14 had a history of recurrent anastomotic stricture. Reported medications included proton-pump inhibitors (n=14), inhaled bronchodilators (n=3) and inhaled corticosteroids (n=4). Six patients (14%) were hospitalised. Three required respiratory support and one required extra-corporal membranous oxygenation. There were no deaths. Respiratory, cardiac and gastrointestinal comorbidities were not associated with increased risk of hospitalization. Concomitant medication at time of infection was associated with increased risk for hospitalization with SARS-CoV-2 infection (p=0.0035), however PPI alone was not significantly associated with increased risk for hospitalization (p=0.16). Conclusion Rates of hospitalization with SARS-CoV-2 are higher for patients with EA-TEF than the general pediatric population, with increased risk in those on medication in patients. 67% of those admitted required respiratory support. Infection likely does not represent a risk for severe respiratory complications or severe outcome.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".