Achieving Consensus on Total Joint Replacement Trial Outcome Reporting Using the OMERACT Filter: Endorsement of the Final Core Domain Set for Total Hip and Total Knee Replacement Trials for Endstage Arthritis
Bibliographic record
Abstract
OBJECTIVE: Discussion and endorsement of the OMERACT total joint replacement (TJR) core domain set for total hip replacement (THR) and total knee replacement (TKR) for endstage arthritis; and next steps for selection of instruments. METHODS: The OMERACT TJR working group met at the 2016 meeting at Whistler, British Columbia, Canada. We summarized the previous systematic reviews, the preliminary OMERACT TJR core domain set and results from previous surveys. We discussed preliminary core domains for TJR clinical trials, made modifications, and identified challenges with domain measurement. RESULTS: Working group participants (n = 26) reviewed, clarified, and endorsed each of the inner and middle circle domains and added a range of motion domain to the research agenda. TJR were limited to THR and TKR but included all endstage hip and knee arthritis refractory to medical treatment. Participants overwhelmingly endorsed identification and evaluation of top instruments mapping to the core domains (100%) and use of subscales of validated multidimensional instruments to measure core domains for the TJR clinical trial core measurement set (92%). CONCLUSION: An OMERACT core domain set for hip/knee TJR trials has been defined and we are selecting instruments to develop the TJR clinical trial core measurement set to serve as a common foundation for harmonizing measures in TJR clinical trials.
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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 | 0.821 | 0.864 |
| Meta-epidemiology (narrow) | 0.002 | 0.003 |
| Meta-epidemiology (broad) | 0.007 | 0.013 |
| Bibliometrics | 0.012 | 0.010 |
| Science and technology studies | 0.006 | 0.009 |
| Scholarly communication | 0.015 | 0.014 |
| Open science | 0.010 | 0.018 |
| Research integrity | 0.013 | 0.016 |
| Insufficient payload (model declined to judge) | 0.004 | 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".