Effects of Inspiratory Muscle Training on Exercise Capacity and Spontaneous Physical Activity in Elderly Subjects: a Randomized Controlled Pilot Trial
Bibliographic record
Abstract
Inspiratory muscle training (IMT) has been shown to improve exercise capacity in diseased populations. We chose to examine the effects of eight weeks of IMT on exercise capacity and spontaneous physical activity in elderly individuals. Eighteen moderately active elderly subjects (68.1 +/- 6.8 years [mean +/- SD]; range 58 - 78 years) were randomly assigned to either an experimental group (n = 9) or a control group (n = 9) in a double-blind manner. All subjects underwent inspiratory muscle testing, treadmill exercise testing and a four-day measurement period of spontaneous physical activity (using accelerometry) both pre- and post-intervention. The experimental group underwent eight weeks of incremental IMT using a pressure threshold device, while the control group underwent sham training using identical devices. After IMT training, inspiratory muscle strength (mean + 21.5 cm H (2)O; 95 % CI: 9.3, 33.7; p = 0.002), V.O (2peak) (+ 2.8 ml x min (-1) x kg (-1); 95 % CI: 0.5, 5.2; p = 0.022), time to exhaustion during a fixed workload treadmill test (+ 7.1 min; 95 % CI: 1.8, 2.4; p = 0.013) and time engaged in moderate-to-vigorous physical activity (+ 59 min; 95 % CI: 15, 78; p = 0.008) improved. Except for a decline in moderate-to-vigorous physical activity, no significant changes were seen in the control group. Therefore, IMT may be a useful technique for positively influencing exercise capacity and physical activity in elderly individuals.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| 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 | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".