Comparison of lifetime incremental cost:utility ratios of surgery relative to failed medical management for the treatment of hip, knee and spine osteoarthritis modelled using 2-year postsurgical values
Bibliographic record
Abstract
BACKGROUND: Demand for surgery to treat osteoarthritis (OA) of the hip, knee and spine has risen dramatically. Whereas total hip (THA) and total knee arthroplasty (TKA) have been widely accepted as cost-effective, spine surgeries (decompression, decompression with fusion) to treat degenerative conditions remain underfunded compared with other surgeries. METHODS: An incremental cost-utility analysis comparing decompression and decompression with fusion to THA and TKA, from the perspective of the provincial health insurance system, was based on an observational matched-cohort study of prospectively collected outcomes and retrospectively collected costs. Patient outcomes were measured using short-form (SF)-36 surveys over a 2-year follow-up period. Utility was modelled over the lifetime, and quality-adjusted life years (QALYs) were determined. We calculated the incremental cost per QALY gained by estimating mean incremental lifetime costs and QALYs of surgery compared with medical management of each diagnosis group after discounting costs and QALYs at 3%. Sensitivity analyses were also conducted. RESULTS: The lifetime incremental cost:utility ratios (ICURs) discounted at 3% were $5321 per QALY for THA, $11,275 per QALY for TKA, $2307 per QALY for spinal decompression and $7153 per QALY for spinal decompression with fusion. The sensitivity analyses did not alter the ranking of the lifetime ICURs. CONCLUSION: In appropriately selected patients with leg-dominant symptoms secondary to focal lumbar spinal stenosis who have failed medical management, the lifetime ICUR for surgical treatment of.
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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 | 0.012 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.006 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".