CRC iDREAM - an ERS Clinical Research Collaboration: An International Survey on the Diagnosis and Management of Sleep-Disordered Breathing in Infants
Bibliographic record
Abstract
Introduction: The iDREAM CRC was launched in 2024. Pediatric sleep disordered breathing (SDB) received increasing attention, resulting in advancements in diagnosis and management guidelines, primarily for children aged 2 years and older. However, infants and toddlers below this age have been overlooked, creating a gap in addressing their sleep-related issues. Aim: As a first step, we launched an international survey among our members to get an inventory of available diagnostic and management tools. Methods: An online survey was sent to pediatric sleep centers in Europe and across the world. Results: The survey included responses from 21 centers to date from Belgium, Canada, France, Hong Kong, India, Israel, Italy, Lithuania, the Netherlands, Norway, Portugal, Switzerland, Turkey and the United Kingdom with the majority being university hospitals. 67% of centers used polysomnography (mostly attended) to diagnose SDB in infants. The most widely used oAHI cut-off was 1/h, but centers also applied 1.5, 2 and 5 as criteria. AASM guideline and the ERS statement were the most used reference papers. Although a specialized pediatric ENT was present in most hospitals, endoscopic upper airway evaluation was not routinely performed in all centers. All but one center initiated non-invasive ventilation if needed at their own center. Home cardiorespiratory monitoring was provided by a slight majority of centers (67%). Conclusion: These pilot data from the first survey of our CRC on sleep-disordered breathing in infants clearly show potential to standardize the diagnosis, work-up and management of obstructive sleep apnea in this vulnerable 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 | 0.011 | 0.018 |
| 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 | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".