Inspiratory Muscle Training and the Perception of Dyspnea in Parkinson's Disease
Bibliographic record
Abstract
BACKGROUND: Pulmonary and respiratory muscle function impairment are common in patients with Parkinson's disease (PD). Inspiratory muscle training may improve strength, dyspnea and functional capacity in healthy subjects and in those with chronic obstructive pulmonary disease. This study investigated the effect of specific inspiratory muscle training (SIMT) on pulmonary functions, inspiratory muscle performance, dyspnea and quality of life, in patients with PD. PATIENTS AND METHODS: Twenty patients with PD (stage II and III Hoehn and Yahr scale) were recruited for the study and were divided into two groups: (a) ten patients who received SIMT and (b) ten patients who received sham training, for three months. Pulmonary functions, the respiratory muscle strength and endurance, the perception of dyspnea (POD) and the quality of life were studied before and within one week after the training period. All subjects trained daily, six times a week, each session consisting of 1/2 hour, for 12 weeks. RESULTS: Following the training period, there was a significant improvement, in the training group but not in the control group, in the following parameters: inspiratory muscle strength, (PImax, increased from 62.0 +/- 8.2 to 78.0 +/- 7.5 cm of H2O (p < 0.05), inspiratory muscle endurance (increased from 20.0 +/- 2.8 to 29.0 +/- 3.0 cm of H2O (p < 0.05), and the POD (decreased from 17.9 +/- 3.2 to 14.0 +/- 2.4 units (p < 0.05). There was a close correlation between the increase in the inspiratory muscle performance and the decrease in the POD. CONCLUSIONS: The inspiratory muscle performance may be improved by SIMT in patients with PD. This improvement is associated with a significant decrease in their POD.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.001 | 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".