Patient appropriateness for total knee arthroplasty and predicted probability of a good outcome
Bibliographic record
Abstract
OBJECTIVES: One-fifth of total knee arthroplasty (TKA) recipients experience a suboptimal outcome. Incorporation of patients' preferences in TKA assessment may improve outcomes. We determined the discriminant ability of preoperative measures of TKA need, readiness/willingness and expectations for a good TKA outcome. METHODS: In patients with knee osteoarthritis (OA) undergoing primary TKA, we preoperatively assessed TKA need (Western Ontario-McMaster Universities OA Index (WOMAC) Pain Score and Knee injury and Osteoarthritis Outcome Score (KOOS) function, arthritis coping), health status, readiness (Patient Acceptable Symptom State, depressive symptoms), willingness (definitely yes-yes/no) and expectations (outcomes deemed 'very important'). A good outcome was defined as symptom improvement (met Outcome Measures in Rheumatology and Osteoarthritis Research Society International (OMERACT-OARSI) responder criteria) and satisfaction with results 1 year post TKA. Using logistic regression, we assessed independent outcome predictors, model discrimination (area under the receiver operating characteristic curve, AUC) and the predicted probability of a good outcome for different need, readiness/willingness and expectations scenarios. RESULTS: Of 1,053 TKA recipients (mean age 66.9 years (SD 8.8); 58.6% women), 78.1% achieved a good outcome. With TKA need alone (WOMAC pain subscale, KOOS physical function short-form), model discrimination was good (AUC 0.67, 95% CI 0.63 to 0.71). Inclusion of readiness/willingness, depressive symptoms and expectations regarding kneeling, stair climbing, well-being and performing recreational activities improved discrimination (p=0.01; optimism corrected AUC 0.70, 0.66-0.74). The predicted probability of a good outcome ranged from 44.4% (33.9-55.5) to 92.4% (88.4-95.1) depending on level of TKA need, readiness/willingness, depressive symptoms and surgical expectations. CONCLUSIONS: Although external validation is required, our findings suggest that incorporation of patients' TKA readiness, willingness and expectations in TKA decision-making may improve the proportion of recipients that experience a good outcome.
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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 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".