Isometric versus Dynamic Measurements of Fatigue: Does Age Matter? A Meta-analysis
Bibliographic record
Abstract
PURPOSE: The assessment of power changes after fatiguing exercise provides important additional information about neuromuscular function compared with traditional isometric measurements, especially when exploring age-related changes in fatigability. Therefore, the aim of this review was to explore the effects of age on neuromuscular fatigue (NMF) when measured in isometric compared with dynamic contractions. The importance of central and peripheral mechanisms contributing to age-related NMF was discussed. METHODS: Medline, EMBASE, Cochrane Central Register of Controlled Trials, and SPORT Discus databases were searched. The combination of terms related to the intervention (fatiguing exercise), population (old people) and outcomes (isometric force and power) were used. This meta-analysis was registered on PROSPERO (CRD42016048389). RESULTS: Thirty-one studies were included. The meta-analyses revealed that force decrease was greater (there was more NMF) in young subjects than their older counterparts when fatigue was induced by isometric tasks (effect size [ES], 0.913; confidence interval [CI], 0.435-1.391; P < 0.001), but not when the fatiguing exercise was performed in dynamic mode (ES, 0.322; CI, -0.039 to 0.682; P = 0.08). Older individuals demonstrated a greater reduction in power after fatigue induced by either dynamic or isometric tasks (ES, -0.891; CI, -1.657 to -0.125; P = 0.023). CONCLUSIONS: There is no difference in the isometric force loss between young and old people when fatigue is induced by dynamic tasks. However, maximal power is more decreased after fatigue tasks in older adults. Thus, the assessment of fatigue (isometric force vs power) must be considered in identifying age-related NMF mechanisms.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.006 | 0.018 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 teacher head, 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".