Rehabilitating Cough Dysfunction in Parkinson's Disease: A Randomized Controlled Trial
Bibliographic record
Abstract
BACKGROUND: Disorders of airway protection (cough and swallowing) are pervasive in Parkinson's disease (PD) resulting in a high incidence of aspiration pneumonia and death. However, there are no randomized controlled trials comparing strength and skill-based approaches to improve airway protection in PD. OBJECTIVES: The aim of this study was to compare expiratory muscle strength training (EMST) and sensorimotor training for airway protection (smTAP) to improve cough-related outcomes in people with PD. METHODS: Participants with PD and dysphagia were recruited for this prospective phase II randomized-blinded controlled clinical trial. Participants completed baseline assessment, 5 weeks of EMST or smTAP, and a post-training assessment. Primary outcome measures included maximum expiratory pressure (MEP) and voluntary cough peak expiratory flow rate (PEFR). Mixed effects models were used to assess the effects of EMST and smTAP on outcomes. RESULTS: A total of 65 participants received either EMST (n = 34) or smTAP (n = 31). MEP improved from pre- to post-treatment for smTAP (P < 0.001, d = 0.19) and EMST (P < 0.001, d = 0.53). Voluntary PEFR increased from pre- to post-treatment for smTAP (P < 0.001, d = 0.19) and EMST (P < 0.001, d = 0.06). Moreover, reflex cough PEFR (P < 0.001, d = 0.64), reflex cough expired volume (P < 0.001, d = 0.74), and urge to cough (P = 0.018, OR = 2.70) improved for the smTAP group but not for the EMST group. CONCLUSIONS: This clinical trial confirmed the efficacy of smTAP to improve reflex and voluntary cough function, above and beyond EMST, the current gold standard. © 2022 International Parkinson and Movement Disorder Society.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".