Study of the relation between body weight and functional limitations and pain in patients with knee osteoarthritis
Bibliographic record
Abstract
OBJECTIVE: To assess the influence of the body weight in functional capacity and pain of adult and elderly individuals with knee osteoarthritis. METHODS: The sample consisted of 107 adult and elderly patients with knee osteoarthritis divided into two groups (adequate weight/adiposity and excessive weight/adiposity) according to body mass index and percent of body fat mass, assessed by electric bioimpedance. Subjects were evaluated for functional mobility (Timed Up and Go Test), pain, stiffness and function (Western Ontario and MacMaster Universities Osteoarthritis Index - WOMAC), pain intensity (Visual Analogue Scale - VAS) and pressure pain tolerance threshold (algometry in vastus medialis and vastus lateralis muscles). Data were analyzed with Statistical Package of the Social Sciences, version 22 for Windows. Comparisons between groups were made through Student's t test, with significance level set at 5%. RESULTS: There was predominance of females in the sample (81.3%), and mean age was 61.8±10.1 years. When dividing the sample by both body mass index and adiposity, 89.7% of them had weight/adiposity excess, and 59.8% were obese. There was no difference between groups regarding age, pain intensity, pressure pain tolerance threshold, functional mobility, stiffness and function. However, pain (WOMAC) was higher (p=0.05) in the group of patients with weight or adiposity excess, and pain perception according to VAS was worse in the group of obese patients (p=0.05). CONCLUSION: Excessive weight had negative impact in patients with osteoarthritis, increasing pain assessed by WOMAC or VAS, although no differences were observed in functionality and pressure pain tolerance.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".