Inspiratory neural drive and muscle activity during sleep in moderate-to-severe COPD
Bibliographic record
Abstract
The interactions between inspiratory neural drive (IND) and inspiratory muscle activity during sleep in COPD are poorly understood. We compared diaphragmatic electromyography (EMGdi) and respiratory mechanics during supine wakefulness (W) and sleep (rapid eye movement, REM; and non-REM stage 2, N2) in COPD and health. Patients with COPD (n=20; FRC 147.1±31.5%pr; post-BD FEV1 55.7±15.9%pr) and age-matched healthy controls (CTRL, n=20) completed overnight polysomnography with EMGdi(%max), tidal esophageal (Pes,%max), gastric (Pga,%max) and transdiaphragmatic pressure (Pdi,%max) measurement during stable breathing in W, N2 and REM at equivalent time-points. EMGdi, Pdi, and Pes were consistently higher in COPD vs CTRL (+167-234%; p<0.05) in W, N2 and REM, but Pga did not differ between groups. EMGdi, Pdi, and Pes were unchanged by wake-sleep transitions in CTRL. In COPD, EMGdi fell 42% and 37% from W-N2 and W-REM, respectively (p<0.05), but Pdi, Pes, and Pga were unchanged. Neuromuscular efficiency (EMGdi : Pdi & Pes) was similar between CTRL and COPD and decreased from W to sleep. IND and inspiratory muscle activity were elevated in COPD vs CTRL in wake and sleep. Despite this marked mechanical disadvantage in COPD, high diaphragmatic and total inspiratory effort were maintained during sleep even through IND declined sharply. This suggests additional activation of accessory muscles of inspiration during both REM and N2 sleep.
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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 | 0.000 |
| 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".