The Role of Vocal Fold Bowing on Cough and Swallowing Dysfunction in Progressive Supranuclear Palsy
Bibliographic record
Abstract
OBJECTIVES: Progressive supranuclear palsy (PSP) is a neurodegenerative disease which results in cough and swallowing dysfunction and aspiration pneumonia. Relationships among vocal fold atrophy, cough, and swallowing have been identified in related diseases, but remain unknown in PSP. This study examined: 1) the prevalence of vocal fold bowing in PSP, and 2) the influence of vocal fold bowing on cough and swallowing in PSP. STUDY DESIGN: Prospective Cohort Study. METHODS: Twenty-three participants with PSP completed instrumental assessments of cough and swallowing. Vocal fold bowing (BI) and swallowing safety (PAS) was assessed using flexible laryngoscopy. Measures of cough effectiveness were obtained using spirometry. Statistical analyses were used to determine the frequency of mild-moderate (BI > 0) and severe (BI > 12.2) bowing, and to assess the influence of BI on PAS and cough effectiveness in PSP. RESULTS: Fifty-two percent (n = 12) of participants exhibited severe bowing while 48% (n = 11) exhibited mild-to-moderate bowing. Voluntary cough peak expiratory flow rate (P = .01), as well as reflex (P = .02) and voluntary (P = .005) cough volume acceleration were lower for participants with severe BI when compared to mild-to-moderate BI. However, BI did not influence PAS (P > .05). CONCLUSIONS: Findings from this study suggest that vocal fold bowing is highly prevalent in PSP and associated with reduced reflex and voluntary cough effectiveness. These findings provide insight into the pathophysiology of compromised airway protection in this patient population. Future studies should examine vocal fold atrophy as a treatment target for behavioral and medical intervention in PSP. LEVEL OF EVIDENCE: 3 (Prospective Observational Study) Laryngoscope, 131:1217-1222, 2021.
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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 | 0.005 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".