Association between WOMAC score and 2D:4D ration in women with knee osteoarthritis
Bibliographic record
Abstract
Introduction: The main issue in osteoarthritis is the risk of pain and physical disability. \nKnee osteoarthritis is one of the commonest joint disorders that lead to physical \ndisability. Elderly women experience lower quality of life due to functional limitation \nand physical disability than male. Main factor that cause physical disability are \nincreasing age, obesity, lack of exercise, previous knee injury and medical comorbidity. \nIn human, finger length ratio (2D:4D) is a sexually dimorphic trait. Generally, \nmales have low 2D:4D ratio; a ring finger that is longer than their index finger. While \nfemale typically have high or equal 2D: 4D ratio, index finger longer than ring fingers \nor the same length. Different digit ratio associated with human physical capability, \nattitude and characteristic. Previous study suggested that low 2D:4D ratio associated \nwith higher risk to developed knee osteoarthritis in women. \nObjectives: To determine association between WOMAC score, Body Mass Index \n(BMI) with 2D:4D ratio in women with grade 2 and 3 of knee osteoarthritis. \nPatients and Methods: We conducted cross sectional study in 118 women with knee \nosteoarthritis (Kellgren Lawrence grade 2 -3), who completed the Western Ontario and \nMcMaster Osteoarthritis Index (WOMAC) questionnaire. Length of index finger and \nring finger were measured from right hand radiographs. Subjects were classified into \nthree groups: type I (index finger longer than ring finger), type II (equal length) and \ntype III (index finger shorter than ring finger). Body Mass Index (BMI) was measured \nand recorded by standard procedure.Result: The majority of the participants were classified under type III finger pattern \nn=56 (47%). However, this study showed there was no significant mean difference \nbetween mean total WOMAC score and each component with 2D:4D ratio. BMI \ncorrelated significantly with worse knee OA symptoms for total WOMAC score (pvalue< \n0.001, r = 0.643). There was a significant association between 2D:4D ratio and \nBody Mass Index (BMI) (F-stat (df) 4.38 (2), P-value 0.015) and higher BMI majority \nin type II (mean (SD) 30.2 (4.31)). \nConclusion: There is no association between WOMAC score and 2D:4D ratio in \nwomen with grade 2 and 3 of knee osteoarthritis. It means that different type of finger \npattern does not affect the severity of physical disability. However, the study showed \npositive correlation between total WOMAC score and higher Body Mass Index (BMI) \nand significant association between 2D:4D ratio and higher Body Mass Index (BMI). \nThose with higher Body Mass Index (BMI) majority in type II
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.004 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".