Total Hip Arthroplasty Patient-Reported Outcome Measures Plateau by One Year: A Scoping Review and Meta-Analysis
Bibliographic record
Abstract
BACKGROUND: To assess total hip arthroplasty (THA) success, various stakeholders utilize patient-reported outcome measures (PROMs). However, these metrics remain unstandardized, and data collection time points vary. In this study, we addressed this gap by systematically investigating the THA PROMs plateau. We asked: (1) in the THA literature, when do studies acquire PROMs; and (2) when does a plateau occur? METHODS: A systematic review was conducted using PubMed and EMBASE to identify studies of adult THA patients that reported joint-specific PROMs (Harris Hip Score (HHS), Oxford Hip Score (OHS), University of California, Los Angeles Activity Scale, Western Ontario and McMaster Universities Osteoarthritis Index, Numerical Rating Scales Visual Analog Scales and Hip Disability and Osteoarthritis Outcome Score (HOOS)). Studies were included if they collected data from before arthroplasty to at least 5 years postoperatively. After data extraction, random-effects meta-analyses evaluated PROM score changes across time points, while Kruskal-Wallis tests assessed differences in the rate of change for the HHS and the OHS. RESULTS: Studies most frequently reported the HHS (n = 14) and the OHS (n = 11). Meta-analyses revealed early score improvements that stabilized over time. The minimal clinically important difference-based comparisons showed plateaus in PROM scores by 6 months in 40.7% of cases and by 1 year in 18.5%. Rate-of-change analyses confirmed that the score change approached zero for most PROMs by 1 year. For HHS, the rate of change from zero to 6 months was significantly greater than later time points, while for OHS, a significant difference was observed between the first 6 months and after 1 year (P < 0.05). CONCLUSIONS: The PROMs tended to plateau after 6 months, with additional improvement limited after 1 year. Streamlining collection to this timeframe can reduce costs, improve registry efficiency, and enhance patient adherence without compromising clinical insight.
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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 | 0.035 | 0.083 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.017 | 0.038 |
| Bibliometrics | 0.015 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".