Physical Performance and Patient‐Reported Outcomes Remain Stable at 5 Years After Total Knee Arthroplasty
Bibliographic record
Abstract
Purpose: To evaluate changes in physical performance tests (PPTs) and patient-reported outcome measures (PROMs) at baseline, 1 year after total knee arthroplasty (TKA), and a minimum of 5 years after TKA. Methods: We enrolled patients who underwent TKA between 2013 and 2015 performed by a single arthroplasty surgeon at Siriraj Hospital, Mahidol University, Bangkok, Thailand. We evaluated PPTs and PROMs over a minimum 5-year follow-up period to assess changes over time, identified independent factors associated with PPT deterioration, and determined TKA survivorship. Results: The study included 126 participants with a mean age of 77.8 years. The average follow-up time was 7.4 ± 2.3 years. PPTs and PROMs changed significantly over time from baseline. However, the 2-minute walk test and timed up-and-go test results slightly declined after 1 year but did not attain minimal clinically important differences, and PROMs were maintained and showed no clinically significant changes after 1 year. Hospitalizations owing to complex medical conditions or trauma were independently associated with PPT deterioration. There was a 98.8% survivorship rate at 7.6 years. Conclusions: In an Asian population undergoing TKA, PPTs and PROMs are maintained within acceptable ranges for at least 5 years after primary TKA. Trauma or hospitalizations arising from complex medical conditions were found to be associated with functional decline. A combined evaluation of PPTs and PROMs is advocated for a comprehensive assessment of patients after TKA. Level of Evidence: Level III, cohort study.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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 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".