Comparison of the EuroQOL-5D With the Oswestry Disability Index, Back and Leg Pain Scores in Patients With Degenerative Lumbar Spine Pathology
Bibliographic record
Abstract
STUDY DESIGN: Cross-sectional study. OBJECTIVE: To evaluate the response behavior of EuroQOL-5D (EQ-5D) compared with the Oswestry Disability Index (ODI), and back and leg pain scores. SUMMARY OF BACKGROUND DATA: Recent changes in policies have highlighted the need for demonstration of both quality and cost effectiveness. In an effort to meet these requirements, surgeons are collecting health-related quality of life and utility data. Unfortunately, the burden of extensive data collection on both physician and patient is considerable. The EQ-5D is a commonly used, easily administered, brief utility measure that can provide both clinical and utility data. The EQ-5D has not yet been validated in spine patients in comparison with established outcome measures. METHODS: EQ-5D, ODI, back and leg pain (0-10) scores were collected as part of standard clinical practice. Spearman rank correlations between the ODI, back and leg pain scores, and the EQ-5D were determined. A subanalysis to determine dimension-specific effects was done. Data were categorized by level of low back disability and level of back and leg pain. RESULTS: Data from 8385 patients (5046 females, 3339 males), mean age 52 (range, 18-96) were analyzed. There was a strong correlation between EQ-5D and ODI (r = -0.776) and between EQ-5D and back pain (r = -0.648); and moderate correlation between EQ-5D and leg pain scores (r = -0.538). Increasing disability, as measured by ODI, lead to lower EQ-5D scores, with similar response behavior for both back and leg pain scores. All correlations were statistically significant at P < 0.0001. CONCLUSION: The EQ-5D correlated well with established spine outcome measures, including ODI, and back and leg pain scores. EQ-5D correlated best with ODI scores. Correlation with back pain was stronger than leg pain, but all correlations were relatively strong. The EQ-5D can serve spine surgeons as an effective measure of clinical outcome and health utility for economic analysis.
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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 | 0.004 | 0.010 |
| 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 | 0.000 | 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".