Paediatric airway stenting: An endoscopic approach to the management of severe airway obstruction
Bibliographic record
Abstract
BACKGROUND: Airway stenting is a complex bronchoscopic intervention that is infrequently performed in children due to limited training opportunities and a lack of appropriate paediatric equipment. We present our institutional data on children (<18 years) who underwent airway stent placement for various tracheobronchial pathologies. METHODS: We conducted a retrospective study of children with notable airway anomalies who underwent stent placement at our institute over a 3.5-year period (January 1, 2020, to June 30, 2023). Data collected included patient age, type and severity of airway obstruction, clinical condition at presentation, type of stent used, complications, outcomes, and follow-up findings. RESULTS: During the study period, 13 stents were deployed in 12 children with tracheobronchial obstruction. Indications for stenting included severe airway stenosis, airway malacia, stenosis with malacia, and tracheoesophageal fistula (TEF). Stent selection depended on age, lesion location, and device availability. No procedure-related mortalities were noted. The most common complication was granulation tissue formation. After an average 10-month follow-up, 85.7% were clinically stable following stent removal. CONCLUSION: Although limited by sample size, our findings support the safety and efficacy of airway stenting in children with tracheobronchial obstruction. Stenting serves as a suitable therapeutic choice when conventional approaches have been unsuccessful or are not suitable. Therefore, it is crucial to establish a robust follow-up system to promptly address any potential complications.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".