Timing of inspiratory muscle activity in patients with unilateral diaphragm dysfunction
Bibliographic record
Abstract
Aim: To compare the timing of inspiratory muscle activity during exercise in patients with unilateral diaphragm dysfunction (UDD) and healthy controls (HCs). Methods: 10 UDD and 10 HCs performed an incremental cycling test with measurements of ventilatory variables (Table 1) and electromyographic (EMG) recordings of the diaphragm (DIA) with an esophageal catheter and of the scalene (SCA), sternocleidomastoid (SCM) and parasternal intercostal (PI) with surface EMG. We detected each muscle EMG9s onset, offset, and activity duration using a validated algorithm (PMID: 35046839). Each muscle EMG onset, offset, and activity duration was compared between UDD and HCs at isoventilation and peak ventilation. Results: At isoventilation EMG onset, offset and activity duration was similar between UDD and HCs for all muscles (P≥0.18), and only DIA EMG onset occurred before the onset of inspiratory flow. At peak ventilation, DIA EMG onset was similar (P=0.58) between UDD and HCs and occurred before the onset of inspiratory flow in both groups. At peak ventilation, SCM and SCA EMG onset were earlier in UDD than HCs (mean difference±SD: -0.12±0.17 and -0.16±0.23 sec, respectively; P<0.05) and occurred before the onset of inspiratory flow only in UDD. Conclusion: Adaptations in the timing activity of non-diaphragmatic inspiratory muscles occurred at the moment task failure with diaphragm dysfunction but did not occur in healthy participants.
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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 | 0.000 | 0.001 |
| 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 | 0.000 | 0.000 |
| 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".