Handgrip Strength Asymmetry in Middle-aged and Older Adults: Clinical Aspects
Bibliographic record
Abstract
Background: Identifying early markers of neurodegeneration remains a key challenge. Recent studies (Zammit AR, 2021; Chen Z. et al., 2022; Wang et al., 2023) suggest an association between handgrip strength (HGS) asymmetry and cognitive decline. This study explores clinical characteristics of HGS asymmetry in middle-aged and elderly patients. Methods: Ninety patients (mean age 63.7±1.2 years; 58.9% men) were enrolled. Inclusion criteria: age >45, preserved hand function. HGS was measured using a KERN MAP 130K1 dynamometer. Asymmetry coefficient was defined as the ratio of non-dominant to dominant hand strength; values <0.9 or >1.1 indicated asymmetry. Cognitive function was assessed via the MoCA test; anxiety and depression via the HADS scale. Results: Mean HGS: dominant hand – 28.5±1.8 kg, non-dominant – 25.9±1.3 kg. HGS asymmetry was found in 54.4% of patients (dominant hand – 38 cases; non-dominant – 11). MoCA scores were lower in the asymmetry group (22.8±0.6) vs. the non-asymmetry group (24.8±0.4; p<0.05). Significant declines were observed in visuoconstructive skills (1.67±0.24 vs 2.58±0.30) and memory (1.61±0.39 vs 2.11±0.40). MoCA negatively correlated with age (r = -0.39) and anxiety (r = -0.32). In the asymmetry group, strong correlations were found between gender and muscle strength (r = -0.70), and between muscle strength and MoCA scores (r = 0.34). Conclusion: HGS asymmetry was present in over half of patients and was associated with lower cognitive scores. The asymmetry coefficient may serve as a clinical marker of early cognitive decline.
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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 | 0.000 | 0.001 |
| 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 | 0.001 | 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".