Generation of in-vivo length-tension curve in severe COPD with magnetic stimulation
Bibliographic record
Abstract
The length-tension relationship of the diaphragm has been studied indirectly by transdiaphragmatic pressure at different lung volumes, or ex-vivo in isolated muscle preparations. Newer technology, such as magnetic stimulation (MagStim) provide direct phrenic stimulation allowing for pressure outputs at different diaphragm lengths. Aim: To non-invasively measure the pressure generating properties of the diaphragm, in severe COPD, to create a partial length tension curve. Methods: To generate the length tension curve specific use of magnetic stimulation is required: unanticipated stimulus, open glottis, electronically timed and with titrated intensity. In severe COPD (N=9, mean FEV1 of 0.82L, 30% predicted) while seated, multiple successive measurements at 60% power through tidal inspiration were made to construct a length tension curve. Results: At FRC, mean negative pressure generated by magnetic stimulation was -2.11 cmH2O. Mean negative pressure lessened linearly from FRC through inspiration, at 2/5, 3/5, 4/5 and 5/5 of tidal inspiration (-1.96, -1.5 to -1.19 cmH2O, p<0.01), as diaphragm length progressively shortened throughout tidal inspiration. All stimulus events were well tolerated by these severe GOLD IV (2001) subjects without distress. Conclusion: This clinical method of in-vivo creation of a diaphragm length tension relation may be very useful in the assessment of respiratory failure or fatigue.
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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 | 0.000 | 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".