What Else to Pay Attention in Terms of Bone Health Other than Osteoarthritis among Candidates Undergoing Total Knee Replacement: Observations in a Subset of Indian Population
Bibliographic record
Abstract
Abstract Background Earlier it was thought that osteoarthritis and osteoporosis were mutually exclusive but many studies now prove that these diseases coexist. This study was undertaken to assess the bone health in terms of mineral density and other markers among patients undergoing total knee replacement due to osteoarthritis. Methods A total of 100 patients with advanced osteoarthritis undergoing total knee replacement and satisfying inclusion and exclusion criteria were selected. Detailed social, medical, personal, and family history was recorded. All participants underwent for dual-energy X-ray absorptiometry scan (spine and both hips), X-rays (both knees and pelvis), Western Ontario and McMaster Universities osteoarthritis index (WOMAC) scoring, and serum levels of vitamin D, calcium, phosphorus, alkaline phosphatase, and Parathyroid hormone (PTH). Data collected and analyzed. Results In total, 87% of total participants were females. Mean values for age, height, weight, serum vitamin D3, serum PTH, serum calcium, serum phosphorus, serum alkaline phosphatase, WOMAC score, and bone mineral density (BMD) score (T-score) were 65.35 years, 160.15 cm, 69.37 kg, 26.91 ng/mL, 48.02 pg/mL, 9.01 mg/mL, 3.40 ng/mL, 57.91 IU/L, 56.32, and −1.16, respectively. Conclusion Osteopenia and osteoporosis seem prevalent in the Indian population with advanced knee osteoarthritis. Our findings do not support the hypothesis of inverse relation between osteoarthritis and lower BMD. The study reflected poorer bone health and lesser average age for Indian patients undergoing total knee replacement.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".