Presented to fulfill requirements of Graduation with Research Distinction
Bibliographic record
Abstract
Knee osteoarthritis (OA) is one of the leading causes of chronic pain, functional limitation, and physical disability among older adults. Being overweight or obese may exacerbate pain symptoms and the risk of functional decline among knee OA patients (5, 7, 14). However, it has yet to be determined if risk of functional decline and inactivity differs as a function of weight status among older, knee OA patients. PURPOSE: The purpose of this investigation was to examine differences in self-reported pain symptoms and physical function among overweight, obese, and morbidly obese older adults with knee OA. METHODS: Seventy-one (58 women and 13 men; M age = 63 years) knee OA patients classified as overweight (n=21), obese (n=36) or morbidly obese (n=14) completed assessments of the Western Ontario and McMaster Universities (WOMAC) Osteoarthritis scale. RESULTS: Results of univariate ANCOVA analyses controlling for age revealed that morbidly obese participants reported worse pain (p < 0.01) and greater functional disability (p < 0.01) when compared with overweight and obese counterparts. No significant differences were observed for pain or functional disability, between participants classified as obese or overweight. CONCLUSIONS: These findings suggest that pain and risk for physical disability increases as a function of weight status among older knee OA patients. Morbidly obese patients demonstrated the least favorable pain outcomes and greatest functional disability. Collectively, the present findings indicate the benefits of lower weight for both mobility self-efficacy and objective functional performance among older adults with knee OA.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.007 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.874 | 0.785 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".