Aspects of the assessment and management of pharyngoesophageal dysphagia
Bibliographic record
Abstract
Swallowing complaints are common and may have significant consequences for nutrition and pulmonary health. Etiology varies and different aspects of the deglutitive system may be affected. A thorough assessment from the oral cavity to the stomach will provide physiologic information that enables specific targeted management plans to be devised. Although the swallow trajectory bridges anatomic areas, there has previously been a tendency to compartmentalize assessment and treatment by arbitrary anatomic boundaries. It is now clear that this approach fails to appreciate the complexity of swallow mechanics and that systems (oral, pharyngeal, esophageal, and pulmonary) are intertwined and codependent. Swallowing specialists from different backgrounds and with complementary skill sets form a multidisciplinary team that can provide insight and address multiple areas of management. With the advent of new tools for instrumental evaluation, such as manometry, targeted rehabilitative strategies can be informed by physiology, increased in precision and breadth, and assessed quantitatively. Surgical approaches have evolved toward endoscopic techniques, and food technology is expanding options in dietary management. The multidisciplinary team is core to managing this varied and often neglected patient population. This review is for clinicians treating swallowing disorders and will explore the selected aspects of the assessment and management of pharyngoesophageal swallowing disorders.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".