Preoperative Clinical Phenotyping for Individualised Rehabilitation in End-Stage Knee Osteoarthritis
Bibliographic record
Abstract
Background: Osteoarthritis (OA) of the knee is a highly prevalent and heterogeneous condition. Identifying distinct clinical phenotypes within end-stage knee OA populations may inform tailored preoperative management strategies for individuals awaiting total knee replacement (TKR) surgery. Methods: This cross-sectional study employed exploratory factor analysis to identify clinical presentation patterns among patients with knee OA awaiting TKR in South Africa, using modifiable variables including demographic data, physical examination findings, patient-reported outcomes, and functional measures. Results: Three distinct clinical phenotypes emerged: (1) gait and weight—characterised by poor gait mechanics, obesity, and low self-efficacy; (2) central pain—encompassing central sensitisation, depression, and reduced functional performance; and (3) functional factors—reflecting muscular weakness and functional limitations. Conclusions: This study highlights the heterogeneity in clinical presentations among patients with end-stage knee OA awaiting TKR in South Africa. The identified phenotypes suggest a need for tailored, multidisciplinary preoperative interventions incorporating weight management, pain management, psychological support, targeted exercise programs, and behavioural change strategies to optimise post-surgical outcomes and enhance overall care.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".