The importance of patient expectations in predicting functional outcomes after total joint arthroplasty.
Bibliographic record
Abstract
OBJECTIVE: To evaluate the relationship between patient expectations of total joint arthroplasty (TJA) and health related quality of life plus satisfaction 6 months after surgery. Methods. This prospective cohort study included patients undergoing primary total hip (THA) and knee arthroplasty (TKA). Patients were evaluated with self-report questionnaires prior to surgery and 6 months post-surgery. Medical Outcomes Study Short Form 36 (SF-36), the Western Ontario McMaster Universities Osteoarthritis Index (WOMAC), and a satisfaction scale were used to evaluate outcomes at final followup. Multivariate regression models were used to evaluate the impact of expectations on outcomes. RESULTS: There were 102 patients with THA and 89 with TKA. Mean age was 66 years. All patients achieved significant improvements in their WOMAC and SF-36 scores following surgery. Patient expectations regarding surgery were not associated with their age, gender, index joint of surgery, marital status, or race. Expectations were not correlated with pre-operative functional health status. Expectation of complete pain relief after surgery was an independent predictor of better physical function and improvement in level of pain at 6 months post-surgery. Expectation of low risk of complications from TJA was an independent predictor of greater satisfaction. CONCLUSIONS: Patient expectations were important independent predictors of improved functional outcomes and satisfaction following TJA. Greater understanding of the relationship between expectations and outcomes may improve the process of care and outcomes of TJA.
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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 | 0.001 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 | 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".