Preoperative predictors of locomotor ability two months after total knee arthroplasty for severe osteoarthritis
Bibliographic record
Abstract
OBJECTIVE: To identify preoperative predictors of locomotor ability 2 months after total knee arthroplasty (TKA). METHODS: Sixty-five participants scheduled for a first TKA were recruited. The dependent variable was the distance covered during the 6-minute gait test 2 months after TKA. The independent variables, measured before surgery, were grouped into 3 categories: 1). personal; 2). organic system, and 3). capability variables. Multiple regression analyses were conducted to determine the best predictors of the dependent variable. Modified cross-validation of the model combining predictors from the three categories was obtained with 10 random samples derived from the original cohort by resampling with replacement. RESULTS: Predictors were identified in the 3 categories: 1). gender, number of comorbidities, body mass index, 2). knee pain, flexion and strength, lower limb mechanical power, and 3). preoperative 6-minute gait distance. When these variables were modeled together only the preoperative 6-minute gait distance and knee pain and flexion remained significant (adjusted R(2) = 0.66). CONCLUSION: Using variables easily measured before surgery, it is possible to predict with good accuracy locomotor ability 2 months after TKA.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".