P-10: Home High-Flow Nasal Cannulae as A Treatment for Extensive Tracheomalacia
Bibliographic record
Abstract
Severe tracheomalacia is a life threatening condition whose management is challenging. Here we describe a case of tracheomalacia treated with long term high-flow cannula. A 39-week gestational age male was noted to have thick secretions, stridor and difficulty breathing at birth. Orogastric tube insertion was unsuccessful and a chest x-ray suggested esophageal atresia. Esophageal atresia type C was confirmed upon surgery. Ligation of the fistula and end to end oesophagus anastomosis were performed. He was extubated within 24 h and maintained on Bipap. Esophageal impedancemetry revealed severe gastro-esophageal reflux. The patient underwent a gastrostomy and Nissen fundoplicature. At 2 months, he was switched to high-flow nasal cannulae (HFNC) at 7LPM with room air. Attempts to decreased HFNC below 5LPM failed, with increased stridor, SaO2 < 90% and PCO2 > 65 mmHg. Bronchoscopy repeated at 4 months showed left main bronchomalacia and severe tracheomalacia with involvement from the cervical trachea to the carina. ChestCT scan showed absence of vascular ring. The patient remained stable on continuous HFNC over the next months. The patient was discharged at 5 months on the AIRVO TM 2 humidifier with integrated flow generator at a flow of 5 LPM and room air. At discharge, prolonged pulse oxymetry showed a mean SaO2 of 97%; PCO2 was 53 mmHg. As the patient continued to evolve well at 9 months, HFNC was discontinued during waking hours and finally stopped at the age of 1 year. This is the first report of successful treatment of severe tracheomalacia using HFNC. Further studies and follow-up are required before conclusive recommendations can be made.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".