Expectation fulfillment is associated with good outcomes and patient satisfaction after knee arthroplasty: a prospective study in a multi-ethnic Asian population
Bibliographic record
Abstract
We aimed to evaluate the relationship between patient expectations and outcomes after knee arthroplasty (KA) in an Asian population in Singapore. We recruited consecutive patients with severe knee osteoarthritis (KOA) scheduled for KA. Pre-operatively, patients provided socio-demographic data and completed the Hospital for Special Surgery Knee Replacement Expectations Survey (HSS-KRES) for baseline pre-operative expectations and Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) for baseline pain and function. Telephone interviews were conducted at 6- and 12-months post-operatively to collect the WOMAC, satisfaction with KA, and the extent to which pre-operative expectations had been fulfilled. We included 1136 patients (mean age 65.9 years, 69.9% female), of which 1103 and 1089 completed the telephone interviews at 6- and 12-months post-KA respectively. In the multivariable models, expectation fulfilment was consistently associated with improvements in WOMAC pain and function at 6- and 12-months post-operatively, but not the baseline expectations. In the sensitivity analyses, expectation fulfilment was also found to be significantly associated with the achievement of minimal clinically important difference (MCID) for WOMAC pain and function at both 6- and 12-months. Expectation fulfilment was associated with patient satisfaction in the adjustment models at both 6- and 12-months after KA. The fulfilment of expectations, rather than pre-operative expectations, is associated with improvements in WOMAC pain, function and overall satisfaction at 6- and 12-months after KA.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".