Pediatric Aerodigestive Medicine: Advancing Collaborative Care for Children With Oropharyngeal Dysphagia
Bibliographic record
Abstract
OBJECTIVES: Aerodigestive disorders encompass various pathological conditions affecting the lungs, upper airway, and gastrointestinal tract in children. While advanced care has primarily occurred in specialty centers, many children first present to general pediatric gastroenterologists with aerodigestive symptoms necessitating awareness of these conditions. At the 2021 Annual North American Society for Pediatric Gastroenterology, Hepatology and Nutrition meeting, the aerodigestive Special Interest Group held a full-day symposium entitled, Pediatric Aerodigestive Medicine: Advancing Collaborative Care of Children with Aerodigestive Disorders. The symposium aimed to underline the significance of a multidisciplinary approach to achieve better outcomes for these complex patients. METHODS: The symposium brought together leading experts to highlight the growing aerodigestive field, promote new scientific and therapeutic strategies, share the structure and benefits of a multidisciplinary approach in diagnosing common and rare aerodigestive disorders, and foster multidisciplinary discussion of complex cases while highlighting the range of therapeutic and diagnostic options. In this article, we showcase the diagnostic and therapeutic approach to oropharyngeal dysphagia (OPD), one of the most common aerodigestive conditions, emphasizing the role of a collaborative model. CONCLUSIONS: The aerodigestive field has made significant progress and continues to grow due to a unique multidisciplinary, collaborative model of care for these conditions. Despite diagnostic and therapeutic challenges, the multidisciplinary approach has enabled and greatly improved efficient, high-quality, and evidence-based care for patients, including those with OPD.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".