Skeletal Muscle Strength and Endurance in Recipients of Lung Transplants
Bibliographic record
Abstract
PURPOSE: Exercise limitation in recipients of lung transplant may be a result of abnormalities in the skeletal muscle. However, it is not clear whether these abnormalities are merely a reflection of the changes observed in the pretransplant condition. The purpose of this paper was to compare thigh muscle volume and composition, strength, and endurance in lung transplant recipients to people with chronic obstructive pulmonary disease (COPD). METHODS: Single lung transplant recipients (n=6) and people with COPD (n=6), matched for age, sex, and BMI participated in the study. Subjects underwent MRI to determine muscle size and composition, lower extremity strength testing and an isometric endurance test of the quadriceps. RESULTS: Lung transplant recipients had similar muscle volumes and intramuscular fat infiltration of their thigh muscles and similar strength of the quadriceps and hamstrings to people with COPD who had not undergone transplant. However, quadriceps endurance tended to be lower in transplant recipients compared to people with COPD (15 +/- 7 seconds in transplant versus 31 +/- 12 seconds in COPD, p = 0.08). CONCLUSIONS: Recipients of lung transplant showed similar changes in muscle size and strength as people with COPD, however muscle endurance tended to be lower in people with lung transplants. Impairments in muscle endurance may reflect the effects of immunosuppressant medications on skeletal muscle in people with lung transplant.
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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 | 0.002 |
| 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) | 0.002 | 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".