The combination of osteoporosis and low lean mass correlates with physical function in end-stage knee osteoarthritis: A retrospective observational study
Bibliographic record
Abstract
We aimed to investigate the prevalence of osteoporosis and low lean mass, either together or in isolation, and their association with physical function, pain, and quality of life (QOL) in patients with end-stage knee osteoarthritis (OA). This retrospective cross-sectional observational study included 578 patients (77 males and 501 females) diagnosed with end-stage knee OA. Patients were divided into 4 groups based on body composition parameters: control, osteoporosis, low lean mass, and osteoporosis + low lean mass. All participants underwent performance-based physical function tests, including a stair climbing test (SCT), a 6-minute walk test, a timed up and go test, and instrumental gait analysis, to examine spatiotemporal parameters. Self-reported physical function and pain levels were measured using the Western Ontario McMaster Universities Osteoarthritis Index and visual analog scale, respectively. Self-reported QOL was measured using the EuroQOL 5 dimensions (EQ-5D) questionnaire. Of 578 patients, 268 (46.4%) were included in the control group, 148 (25.6%) in the osteoporosis group, 106 (18.3%) in the low lean mass group, and 56 (9.7%) in the osteoporosis + low lean mass group. Analysis of variance revealed that the scores for the osteoporosis + low lean mass group in the SCT-ascent, SCT-descent, and timed up and go test were significantly higher, whereas those for the 6-minute walk test, gait speed, and cadence were significantly lower than those for the other groups (P < .05). After adjusting for age, sex, and body mass index, multiple linear regression analysis identified SCT-ascent (β = 0.140, P = .001, R2 = 0.126), SCT-descent (β = 0.182, P < .001, R2 = 0.124), gait speed (β = -0.116, P = .005, R2 = 0.079), and cadence (β = -0.093, P = .026, R2 = 0.031) as being significantly associated with osteoporosis + low lean mass. Thus, osteoporosis + low lean mass correlates with poor physical function, but not pain and QOL, in patients with end-stage knee OA.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".