Is isometric strength loss immediately after eccentric exercise related to changes in indirect markers of muscle damage?
Bibliographic record
Abstract
This study tested the hypothesis that the magnitude of maximal isometric strength (MVC) loss immediately following eccentric exercise (MVC-post) would relate to changes in other indirect markers of muscle damage following exercise. Eighty-nine men were recruited from the same student population and performed 24 maximal eccentric actions of the elbow flexors. Commonly used markers of muscle damage such as relaxed and flexed elbow joint angles, range of motion (ROM), upper-arm circumference, muscle soreness, and plasma creatine kinase (CK) activity were measured before, immediately after, and 1-4 d after exercise. Pearson's product-moment correlation coefficients (r) between change in MVC-post and other markers of muscle damage, as well as MVC during recovery days, were calculated. Changes in MVC-post ranged from -72.8% to -17.6%, and correlated significantly (p < 0.01) with MVC at 1 (r = 0.59), 2 (0.63), 3 (0.61), and 4 (0.62) d after exercise. Reduction in MVC-post also correlated significantly (p < 0.05) with changes in relaxed (r = 0.50) and flexed elbow joint angles (-0.40), ROM (0.55), arm circumference (-0.45), peak palpation (-0.34) and extension muscle soreness (-0.48), and peak CK activity (-0.59). However, the r values were not necessarily high, and MVC-post poorly reflected the distribution of some measures, such as peak CK activity (124 - 50 440 IU x L(-1). These results suggest that MVC-post is not a strong correlate of the changes in markers of muscle damage following eccentric exercise of the elbow flexors.
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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 | 0.004 |
| 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".