Analysis of functional status of elderly with osteoarthritis
Bibliographic record
Abstract
The objective of this study was to analyze the influence of gender, age and pharmacological treatment for osteoarthritis (OA) on the functional status of physically independent elderly. This cross-sectional study involved 105 elder individuals from both genders (age: 68.80±6.3 years) with OA of the hip and / or knee, which was confirmed by radiographic analysis. Two specific instruments assessed functional status: Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) and Lequesne Index. It was observed worse condition in females in Lequesne (p=0.007), global WOMAC (p=0.013), as well as in its fields: pain intensity (p=0.023), stiffness (p=0.032) and functional status (p=0.018). However, considering age and radiological status, no differences were observed between groups in all variables (p>0.05). It was observed that the individuals with pharmacological treatment for OA have poor functional status in all functional questionnaires (Lequesne, p=0.005; global WOMAC, p=0.008 as well as in specific WOMAC fields, such as Pain intensity, p=0.004; Stifness, p=0.007; and Functional status p=0.023). At multivariate modelo (multiple linear regression), it was observed that gender and pharmacological treatment may influence the functional status of elderly with OA, whereas women and medicated individuals are those showing the worse condition both in Lequesne and WOMAC indexes. It was observed worse functional status in women with osteoarthritis and pharmacological treatment evoked no improvement in functional status of these individuals.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".