Relationship between clinical and functional outcomes with resting inspiratory muscle strength in chronic respiratory diseases
Bibliographic record
Abstract
Background: Impairments in inspiratory muscle strength have been described in a range of cardiopulmonary diseases in which dyspnea and exercise intolerance are cardinal features. It remains unclear whether inspiratory muscle strength would be uniformly related to these negative outcomes among different patient populations. Methods: Subjects with COPD (N=36), chronic fibrosing interstitial lung disease (ILD) (N=30), pulmonary arterial hypertension (PAH) (N=31) and healthy controls (C) (N=22) performed resting lung function tests (including maximal inspiratory pressure; MIP) and an incremental cardiopulmonary exercise test. Results: All patient groups presented with significantly lower MIP compared to C (PAH: 71±17 % pred; ILD: 87±25 % pred; COPD: 88±28 % pred and C: 111±29 % pred). Of note, PAH had lower MIP values compared to COPD (p=0.04) and ILD (p=0.07). In healthy and COPD, MIP was not related to peak exercise capacity or dyspnea. Conversely, MIP was positively related to peak oxygen uptake (r=0.462; p=0.01) in ILD and inversely related to exertional dyspnea in ILD (peak Borg Dyspnea/peak minute-ventilation: r=-0.352; p=0.056) and activity-related dyspnea in PAH (modified MRC scale: r=-0.443; p=0.013). Conclusion: Impairments in inspiratory muscle strength are more closely related to negative clinical (dyspnea) and functional (exercise intolerance) outcomes in ILD and PAH than COPD. These results suggest that inspiratory muscle training might be particularly beneficial to these specific patient populations.
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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 | 0.003 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".