Effectiveness of Interventions for Dysphagia in Parkinson Disease: A Systematic Review
Bibliographic record
Abstract
PURPOSE: Dysphagia is a common sequela of Parkinson disease (PD) and is associated with malnutrition, aspiration pneumonia, and mortality. This review article synthesized evidence regarding the effectiveness of interventions for dysphagia in PD. METHOD: Electronic searches were conducted in Ovid MEDLINE, Embase, Cochrane Central Register of Controlled Trials, CINAHL, and speechBITE. Of the 2,015 articles identified, 26 met eligibility criteria: interventional or observational studies with at least five or more participants evaluating dysphagia interventions in adults with PD-related dysphagia, with outcomes measured using videofluoroscopic swallowing study (VFSS), fiberoptic endoscopic evaluation of swallowing (FEES), or electromyography (EMG). Risk of bias (RoB) was evaluated using the Evidence Project tool and predetermined criteria regarding the rigor of swallowing outcome measures. RESULTS: = 4). Critical appraisal of study findings for RoB, methodological rigor, and transparency showed the majority of studies failed to adequately describe contrast media used, signal acquisition settings, and rater blinding to time point. Low certainty evidence generally suggested improved swallow timing with exercises with biofeedback and deep brain stimulation (DBS), improved safety with DBS and expiratory muscle strength training, and improved efficiency with the Lee Silverman Voice Treatment and levodopa. CONCLUSIONS: Studies with lower RoB and greater experimental rigor showed potential benefit in improving swallowing efficiency but not safety. Further research investigating discrete changes in swallowing pathophysiology post-intervention is warranted to guide dysphagia management in PD. SUPPLEMENTAL MATERIAL: https://doi.org/10.23641/asha.17132162.
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 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 | 0.009 | 0.036 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.009 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".