Is there a relationship between hand grip strength and knee osteoarthritis in terms of radiological and functional findings in female patients?
Bibliographic record
Abstract
OBJECTIVES: The aim of this study was to assess the presence of the relationship between hand grip strength (HGS) and radiological and functional signs of knee osteoarthritis (KOA). PATIENTS AND METHODS: Between March 2019 and January 2020, a total of 64 female patients (mean age: 63.4±8.8 years; range, 50 to 80 years) with bilateral chronic knee pain who were diagnosed with KOA using radiological and clinical findings according to the 2019 American College of Rheumatology guidelines were included in the study. Patient demographics, body mass index (BMI) values, and hand dominance were recorded. The Western Ontario and McMaster Universities Arthritis Index (WOMAC) and Lower Extremity Functional Scale (LEFS) were used for the assessment of KOA functionality. The Kellgren-Lawrence (KL) grading system was used for the radiological assessment of KOA. Electronic dynamometer was used for HGS measurement and values were normalized according to BMI results. RESULTS: In the assessment of relationship between HGS and functionality of KOA, a negative, moderate correlation was found between the WOMAC and HGS-Dominant (D) (r=0.312, p<0.05) and HGS-Non-Dominant (ND) (r=0.391, p<0.01). In addition, a positive, moderate correlation was found between the LEFS and HGS-D (r=0.344, p<0.01) and HGS-ND (r=0.371, p<0.01). There was a weak, negative correlation between the HGS-ND, KL-D (r=0.256, p<0.05) and KL-ND (r=0.283, p<0.05), while no significant correlation was found between the HGS-D and KL. CONCLUSION: Our study results show that HGS-ND is associated with KOA radiologically and functionally. The HGS should be added in the WOMAC and LEFS scales in the functional assessment of KOA and new scales including HGS assessment should be developed.
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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 | 0.003 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".