Cryotherapy in the paediatric airway: Indications, success and safety
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVE: Cryotherapy in interventional bronchoscopy is a new treatment modality, which has recently been made available for the paediatric airway. Lack of experience and safety concerns have led to hesitant adaptation. The aim of this study was to assess indications, success rates and complications of airway cryotherapy in children. METHODS: Bronchoscopists from medical centre performing cryotherapy in patients between 0 and 18 years were invited to participate in a prospective study based on an online questionnaire. Patient and participant data were collected between June 2020 and June 2021. RESULTS: A total of 69 cryotherapy procedures were performed in 57 patients a for three main indications: Biopsy (30), restoration of airway patency (23) and foreign body aspiration (16). The overall success rate was 93%, the remaining 7% were performed for foreign body removal and required a switch of technique. Restoration of airway patency was successfully applied in various pathologies, including mucus plugs, bronchial casts and post traumatic stenosis. The diagnostic yield of transbronchial biopsies was 96%. No severe complications were encountered; one pneumothorax following a cryobiopsy required a chest drain for 48 h. No child was admitted to intensive care or died from a procedural complication. CONCLUSION: In this largest paediatric case collection to date, cryotherapy was safe and carried a high success rate. Cryobiopsy compares favourably to the widely used forceps biopsy and could replace it in the future. Paediatric bronchoscopists are encouraged to add cryotherapy to their armamentarium of airway interventions.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".