Knee manipulation under anaesthetic following total knee arthroplasty
Bibliographic record
Abstract
The purpose of this study was to compare clinical outcomes of total knee arthroplasty (TKA) after manipulation under anaesthesia (MUA) for post-operative stiffness with a matched cohort of TKA patients who did not requre MUA. In total 72 patients (mean age 59.8 years, 42 to 83) who underwent MUA following TKA were identified from our prospective database and compared with a matched cohort of patients who had undergone TKA without subsequent MUA. Patients were evaluated for range of movement (ROM) and clinical outcome scores (Western Ontario and McMaster Universities Arthritis Index, Short-Form Health Survey, and Knee Society Clinical Rating System) at a mean follow-up of 36.4 months (12 to 120). MUA took place at a mean of nine weeks (5 to 18) after TKA. In patients who required MUA, mean flexion deformity improved from 10° (0° to 25°) to 4.4° (0° to 15°) (p < 0.001), and mean range of flexion improved from 79.8° (65° to 95°) to 116° (80° to 130°) (p < 0.001). There were no statistically significant differences in ROM or functional outcome scores at three months, one year, or two years between those who required MUA and those who did not. There were no complications associated with manipulation. At most recent follow-up, patients requiring MUA achieved equivalent ROM and clinical outcome scores when compared with a matched control group. While other studies have focused on ROM after manipulation, the current study adds to current literature by supplementing this with functional outcome scores.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".