Loaded 5 Sit-to-Stand Test to Determine the Force–Velocity Relationship in Older Adults: A Validation Study
Bibliographic record
Abstract
Force–velocity profiling (F-v) evaluates muscle function through the identification of maximum force (F0), velocity (V0), power (Pmax) and optimal velocity (Vopt). The purpose of this study was to investigate the validity and feasibility of loaded 5 Sit-to-Stand (5STS) force-velocity profiling compared to the gold standard instruments (isokinetic Dynamometry, ISO) and asses the relationship between the 5STS-derived muscle function indexes with clinical markers of muscle mass and strength. Forty-six older adults (21 females: 63.8 ± 3.9 yrs) performed 5STS (four different weight conditions) and ISO tests (five different velocities). Paired t-tests, regression analyses, and Bland–Altman analysis were conducted. The results showed significant differences in F0, V0, and Vopt (p < 0.001) but no difference in Pmax (p = 0.259) between tests. Only F0 and Pmax were highly correlated between tests (r = 0.71, r = 0.84, respectively). Bland–Altman analysis showed a not significant bias and good precision (p = 0.260, 34 W) only for Pmax. Large to very large correlations (r = 0.53 to 0.81) were found between F0 and Pmax and clinical markers of muscle mass and strength. In conclusion, loaded 5STS profiling could be a feasible, valid, and cost- and time-efficient alternative to ISO for the characterization of clinically relevant markers of muscle function in healthy older adults.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".