The role of sex, age, and BMI in treatment decisions for knee osteoarthritis: conservative management versus total knee replacement
Bibliographic record
Abstract
BACKGROUND: Knee osteoarthritis (KOA) has a complex, multifactorial nature with well-established risk factors which may influence treatment decisions. Here we want to identify distinctive characteristics between patients receiving conservative treatment versus total knee replacement (TKR), analyzing both patient-specific and knee-specific features. METHODS: This case-control study compared patients assigned to TKR versus conservative management, examining subjects aged 60-75 years with radiographically confirmed KOA (Kellgren-Lawrence grades 2-3), with all participants evaluated by blinded clinicians using validated assessment tools including Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC), Hospital Anxiety and Depression Scale (HADs), Pain Catastrophizing Scale (PCS) and Daily physical activity (DPA) questionnaires. The study employed multivariate analysis of variance for continuous variables at both patient and knee levels, followed by univariate analysis of variance for significant factors, while logistic and linear regression analyses were used to calculate odds ratios, with Bonferroni corrections applied to adjust p-values for multiple comparisons. RESULTS: in the conservative management group. TKR patients demonstrated significantly worse scores in WOMAC, HADS, and PCS compared to the conservative management group, though DPA levels remained similar between both groups. At the knee level, women demonstrated significantly higher pain sensitivity and central sensitization compared to men, with no differences between conservative and TKR groups. CONCLUSIONS: Patients undergoing TKR exhibited significantly worse baseline clinical outcomes, particularly in WOMAC scores, despite having similar radiographic severity to those receiving conservative treatment, suggesting that functional and symptomatic measures may be more valuable than radiographic findings in determining surgical intervention.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".