Patient-reported outcome measures in arthroplasty registries
Bibliographic record
Abstract
- The International Society of Arthroplasty Registries (ISAR) Patient-Reported Outcome Measures (PROMs) Working Group have evaluated and recommended best practices in the selection, administration, and interpretation of PROMs for hip and knee arthroplasty registries. The 2 generic PROMs in common use are the Short Form health surveys (SF-36 or SF-12) and EuroQol 5-dimension (EQ-5D). The Working Group recommends that registries should choose specific PROMs that have been appropriately developed with good measurement properties for arthroplasty patients. The Working Group recommend the use of a 1-item pain question ("During the past 4 weeks, how would you describe the pain you usually have in your [right/left] [hip/knee]?"; response: none, very mild, mild, moderate, or severe) and a single-item satisfaction outcome ("How satisfied are you with your [right/left] [hip/knee] replacement?"; response: very unsatisfied, dissatisfied, neutral, satisfied, or very satisfied). Survey logistics include patient instructions, paper- and electronic-based data collection, reminders for follow-up, centralized as opposed to hospital-based follow-up, sample size, patient- or joint-specific evaluation, collection intervals, frequency of response, missing values, and factors in establishing a PROMs registry program. The Working Group recommends including age, sex, diagnosis at joint, general health status preoperatively, and joint pain and function score in case-mix adjustment models. Interpretation and statistical analysis should consider the absolute level of pain, function, and general health status as well as improvement, missing data, approaches to analysis and case-mix adjustment, minimal clinically important difference, and minimal detectable change. The Working Group recommends data collection immediately before and 1 year after surgery, a threshold of 60% for acceptable frequency of response, documentation of non-responders, and documentation of incomplete or missing data.
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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 | 0.198 | 0.404 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.011 | 0.021 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".