Lower extremity muscle strength reference values for young Saudi male adults aged 21 to 23 years and their correlation with anthropometric parameters and balance
Bibliographic record
Abstract
Normative reference values for muscle strength are needed for muscle strength assessment and estimation of prognosis in lower extremity related neuromuscular disorders, as muscle strength influenced by anthropometric parameters and muscle strength itself affects balance. Normative reference values for muscle strength in the Saudi Arabian population is lacking in the literature. Hence, the current study aimed to establish normative reference values for lower extremity muscle strength and to correlate these values with anthropometric parameters and balance. Lower extremity muscle strength and balance were assessed by baseline hand-held dynamometer and by forward, lateral, and oblique direction reach tests in 421 young male adults between 21 and 23 years of age. The mean and standard deviation of lower extremity strength ranged from 43.83 ± 16.92 lb to 62.07 ± 10.74 lb. Body weight, body mass index, and oblique and lateral reach distances were correlated with some knee and ankle muscle strength values. Body weight, body mass index, and balance showed significant effect on lower extremity muscle strength. Furthermore, decreased muscle strength may impair balance; the current clinical practice should evaluate body weight, body mass index, and muscle strength during the assessment process.
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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 | 0.001 | 0.001 |
| 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) | 0.001 | 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".