Determinants of satisfaction 1 year after total hip arthroplasty: the role of expectations fulfilment
Bibliographic record
Abstract
BACKGROUND: Between 7% and 15% of patients are dissatisfied after total hip arthroplasty (THA). To assess predictors and postoperative determinants of satisfaction and expectation fulfilment one year after (THA). METHODS: Before THA surgery, 132 patients from three tertiary care centres and their surgeons were interviewed to assess their expectations using the Hospital for Special Surgery Total Hip Replacement Expectations Survey (THR survey). One year after surgery, patients (n = 123) were contacted by phone to complete a questionnaire on expectation fulfilment (THR survey), satisfaction, functional outcome (Womac), and health-related quality of life (SF 12). Univariate and multivariate analyses were performed. RESULTS: Preoperative predictors of satisfaction were a good mental wellbeing (adjusted OR 1.09 [1.02; 1.16], p = 0.01) and optimistic surgeons expectations (1.07 [1.01; 1.14], p = 0.02). The main postoperative determinant of satisfaction was the fulfilment of patient's expectations (1.08 [1.04; 1.12], p < 0.001). Expectation fulfilment could be predicted before surgery by young age (regression coefficient -0.55 [-0.88; -0.21], p = 0.002), good physical function (-0.96 [-1.82; -0.10], p = 0.03) and good mental wellbeing (0.56 [0.14; 0.99], p = 0.01). Postoperative determinants of expectation fulfilment were functional outcome (-2.10 [-2.79; -1.42], p <0.001) and pain relief (-14.83 [-22.38; -7.29], p < 0.001). CONCLUSION: To improve patient satisfaction after THA, patients' expectations and their fulfilment need to be carefully addressed. Patients with low mental wellbeing or physical function should be identified and specifically informed on expected surgical outcome. Surgeons' expectations are predictive of satisfaction and information should aim to lower discrepancy between surgeons' and patients' expectations.
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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 | 0.004 |
| 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".