Health state utility of patients with single-level cervical degenerative disc disease: comparison of anterior cervical discectomy and fusion with cervical disc arthroplasty
Bibliographic record
Abstract
OBJECT: Cost-effectiveness analysis (CEA) of medical interventions has become increasingly relevant to the discussion of optimization of care. The use of utility scales in CEA permits a quantitative assessment of effectiveness of a given intervention. There are no published utility values for degenerative disc disease (DDD) of the cervical spine, anterior cervical discectomy and fusion (ACDF), or cervical disc replacement (CDR). The purpose of this study was to define health utility values for those health states. METHODS: The 36-Item Short Form Health Survey data from the ProDisc-C investigational device exemption study were obtained for single-level DDD at baseline and 24 months postoperatively after ACDF or CDR procedures. Patients in the original study were randomized to either ACDF or CDR. Utilizing a commercially available Short Form-6 dimensions program, utility scores were calculated for each health state using a set of parametric preference weights obtained from a sample of the general population using the recognized valuation technique of standard gamble. RESULTS: The baseline health state utility (HSU) value for a patient with single-level DDD was 0.54 in both the ACDF and CDR groups. Postoperative changes in HSU values were seen in both intervention groups at 24 months. Cervical disc replacement had a HSU value of 0.72. Anterior cervical discectomy and fusion was found to have a postoperative utility state of 0.71. No statistically significant difference was found in the HSU for ACDF and CDR at 24 months of follow-up. CONCLUSIONS: This study represents the first calculated HSU value for a patient with single-level cervical DDD. Additionally, 2 common treatment interventions for this disease state were assessed. Both treatments were found to have significant impact on the HSU values. These values are integral to future CEA of ACDF and CDR.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 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".