Effects of bariatric surgery on knee osteoarthritis, knee pain and quality of life in female patients.
Bibliographic record
Abstract
OBJECTIVES: Bariatric surgery is an effective intervention for severe obesity and associated comorbidities. We compared symptoms, joint space and life quality of morbidly obese patients with symptomatic knee osteoarthritis before and after bariatric surgery. METHODS: 34 patients with knee osteoarthritis were evaluated with standing anteroposterior and lateral radiography, medial and lateral joint distances of the knees, Visual Analog Scale (VAS), Western Ontario and McMaster Universities Arthritis Index (WOMAC) questionnaire and the Short Form 36 (SF-36) before and 6 months after surgery. RESULTS: before and after surgery, respectively. SF-36 subscales were significantly higher after surgery (p<0.05), while mean VAS values and WOMAC scores were significantly lower postoperatively (p<0.001). Right knee medial and left knee lateral joint distance measurements were significantly higher postoperatively (p<0.05). BMI change, in linear regression analysis had no significant effect on VAS, WOMAC, SF-36 and knee lateral and medial joint distance measurements. CONCLUSIONS: Although bariatric surgery might improve pain, life quality and functionality of knee osteoarthritis in early period, improvement is not directly related to weight loss amount.
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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) | 0.000 | 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 | 0.000 |
| 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".