Intensive Weight Loss Program Improves Physical Function in Older Obese Adults with Knee Osteoarthritis
Bibliographic record
Abstract
OBJECTIVE: Physical function and body composition in older obese adults with knee osteoarthritis (OA) were examined after intensive weight loss. RESEARCH METHODS AND PROCEDURES: Older obese adults (n = 87; > or = 60 years; BMI > or = 30.0 kg/m2) with symptomatic knee OA and difficulty with daily activities were recruited for a 6-month trial. Participants were randomized into either a weight stable (WS) or weight loss (WL) program. Participants in WL (10% weight loss goal) were prescribed a 1000 kcal/d energy deficit diet with exercise 3 d/wk. WS participants attended health information sessions. Body composition and physical function (Western Ontario and McMaster University Osteoarthritis Index, 6-minute walking distance, and stair climb time) were assessed at baseline and 6 months. Statistical analysis included univariate analysis of covariance on 6-month measurements using baseline values as covariates. Associations between physical function and body composition were performed. RESULTS: Body weight decreased 8.7 +/- 0.8% in WL and 0.0 +/- 0.7% in WS. Body fat and fat-free mass were lower for WL than WS at 6 months (estimated means: fat = 38.1 +/- 0.4% vs. 40.9 +/- 0.4%, respectively; fat-free mass = 56.7 +/- 0.4 vs. 58.8 +/- 0.4 kg, respectively). WL had better function than WS, with lower Western Ontario and McMaster University Osteoarthritis Index scores, greater 6-minute walk distance, and faster stair climb time (p < 0.05). Changes in function were associated with weight loss in the entire cohort. DISCUSSION: An intensive weight loss intervention incorporating energy deficit diet and exercise training improves physical function in older obese adults with knee OA. Greater improvements in function were observed in those with the most weight loss.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| 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".