Comparison of the EuroQol and short form 6D in Singapore multiethnic asian knee osteoarthritis patients scheduled for total knee replacement
Bibliographic record
Abstract
OBJECTIVE: To compare the EuroQol (EQ-5D) and Short Form 6D (SF-6D) among multiethnic Asian patients with knee osteoarthritis (OA) scheduled for total knee replacement in Singapore. METHODS: Patients were asked to complete questionnaires including the EQ-5D, Short Form 36, Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC), and Lequesne knee index. EQ-5D and SF-6D utility scores were calculated using the scoring algorithms developed from the UK general population. Agreement between the 2 instruments was assessed by comparing their score distributions, means, medians, intraclass correlation coefficients (ICCs), and a Bland-Altman plot. Correlations of the EQ-5D and SF-6D with WOMAC and Lequesne knee index scores were also examined. RESULTS: A consecutive sample of 258 knee OA patients (127 English-speaking and 131 Chinese-speaking) participated. The mean +/- SD EQ-5D utility score was 0.49 +/- 0.31 (range -0.25-1.00) and the mean SF-6D utility score was 0.63 +/- 0.12 (range 0.32-0.89). In a hypothetical example, this 0.14-point difference in mean utility scores yielded a difference of $10,000/quality-adjusted life year (QALY) in cost-effectiveness ratios. The score distribution was bimodal for the EQ-5D and normal for the SF-6D. This poor agreement was also demonstrated by the Bland-Altman plot and the low ICC (range 0.18-0.54). Correlations of the WOMAC and Lequesne index with the EQ-5D were higher than with the SF-6D. CONCLUSION: Using different preference-based health-related quality of life instruments may yield different utility scores, which could have a great impact on QALY estimates. This highlights the importance of selecting appropriate instruments for economic evaluation. Additional research is needed to determine which instrument (the EQ-5D or the SF-6D) should be used in OA patients.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.016 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".