Association between inspiratory muscle weakness and slowed oxygen uptake kinetics in patients with chronic obstructive pulmonary disease
Bibliographic record
Abstract
Patients with chronic obstructive pulmonary disease (COPD) may have poor inspiratory muscle function, which reduces minute and alveolar ventilation, leading to increased hypoxemia and slow pulmonary oxygen uptake kinetics. However, little is known about the effect of inspiratory muscle weakness (IMW) on oxygen uptake kinetics in patients with COPD. Thus, we tested the hypothesis that COPD patients with IMW have slowed oxygen uptake kinetics. An observational study was conducted that included COPD patients with moderate to severe airflow limitation and a history of intolerance to exercise. Participants were divided into 2 groups: (IMW+; n = 22) (IMW–; n = 23) of muscle weakness. The maximal inspiratory, expiratory, and sustained inspiratory strength as well as the maximal endurance of the inspiratory muscles were lower in IMW+ patients (36 ± 9.5 cm H2O; 52 ± 14 cm H2O; 20 ± 6.5 cm H2O; 94 ± 84 s, respectively) than in IMW– patients (88 ± 12 cm H2O; 97 ± 28 cm H2O; 82.5 ± 54 cm H2O; 559 ± 92 s, respectively; p < 0.05). Moreover, the 6-min walk test and peak oxygen uptake were reduced in the IMW+ patients. During the constant work test, oxygen uptake kinetics were slowed in the IMW+ compared with IMW– patients (88 ± 29 vs 61 ± 18 s, p < 0.05). Our findings demonstrate that inspiratory muscle weakness in COPD is associated with slowed oxygen uptake kinetics, and thus, reduced functional capacity.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".