Reliability of using magnetic stimulation to evaluate muscle function in patients with severe to very severe COPD and healthy subjects
Bibliographic record
Abstract
In addition to voluntary activation strategies, limb muscle function can also be assessed during non-voluntary limb muscle contractions by calculating activation using un-potentiated (Qtwunpot) and potentiated twitch force (Qtwpot) from a series of twitches induced by magnetic stimulation. The test-retest reliability of these measurement techniques was investigated in the present study. Patients with COPD (n=20) (FEV1 38 % predicted) and healthy subjects (n=15) completed two testing sessions (> 48h between sessions) to assess quadriceps muscle function using magnetic stimulation. At each occasion, a ramp protocol of non-potentiated stimulations at increasing intensities (40, 50, 60, 70, 80, 85, 90, 95, 100% of stimulator output) was performed. After participants were asked to perform a set of three maximal 5-s voluntary contractions (MVCs). This was followed by potentiated twitches at 100% stimulator output. Qtwunpot and Qtwpot are defined as the peak response observed during the ramp protocol and potentiated twitches, respectively. MVC was defined as the peak of the strongest voluntary contraction. Results presented in Table 1. Magnetic stimulation of the femoral nerve provides a reliable method for assessing muscle function in patients with COPD and healthy subjects, which, in contrast, to a MVC is independent of the subjects9 motivation and cooperation.
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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 | 0.003 | 0.009 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".