Fiberoptic Endoscopic Evaluation of Swallowing (FEES) in Head and Neck Cancer Patients with Late Radiation-Associated Dysphagia: Swallowing Safety, Efficacy, and Dysphagia Phenotype
Bibliographic record
Abstract
Late radiation-associated dysphagia (late-RAD) remains a challenge in head and neck cancer (HNC) survivorship, despite advancements in treatment methods. Although Fiberoptic Endoscopic Evaluation of Swallowing (FEES) stands as the preferred diagnostic approach for oropharyngeal dysphagia assessment in the HNC population, current studies lack a FEES-derived swallowing parameter characterization and phenotypic classification within this specific cohort. This study sought to employ FEES-based assessment to characterize swallowing safety and efficacy profiles, identify distinct phenotypes in HNC patients suffering from late-RAD, and examine potential correlations between safety and efficacy parameters. A retrospective analysis included twenty-four post-radiotherapy HNC patients evaluated using standardized FEES protocols across three bolus consistencies (liquid, semisolid, and solid). Swallowing safety was quantified using the Penetration–Aspiration Scale (PAS), while efficacy was measured via the Yale Pharyngeal Residue Severity Rating Scale (YPRSRS). Additionally, six distinct dysphagia phenotypes were characterized within the cohort. Propulsion deficit was the predominant phenotype (92%), followed by delayed pharyngeal phase (37.5%) and protective deficit (25%), with 46% of patients exhibiting multiple phenotypes. Unsafe swallowing occurred most frequently with liquid consistency (62.5%), while residue was most prevalent with semisolid (82.6% valleculae, 52.2% pyriform sinuses) and solid consistencies (92.3% valleculae, 53.8% pyriform sinuses). Significant correlations were found between penetration–aspiration and pharyngeal residue scores across consistencies (p < 0.05). FEES examination revealed distinct phenotypes in late radiation-associated dysphagia, with a predominance of propulsion deficit and significant interdependence between safety and efficacy parameters.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".