Cost-Effectiveness Analysis of Motion-Preserving Operations for Wrist Arthritis
Bibliographic record
Abstract
BACKGROUND: The authors conducted a cost-effectiveness analysis to answer the question: Which motion-preserving surgical strategy, (1) four-corner fusion, (2) proximal row carpectomy, or (3) total wrist arthroplasty, used for the treatment of wrist osteoarthritis, is the most cost-effective? METHODS: A simulation model was created to model a hypothetical cohort of wrist osteoarthritis patients (mean age, 45 years) presenting with painful wrist and having failed conservative management. Three initial surgical treatment strategies-(1) four-corner fusion, (2) proximal row carpectomy, or (3) total wrist arthroplasty-were compared from a hospital perspective. Outcomes included clinical outcomes and cost-effectiveness outcomes (quality-adjusted life-years and cost) over a lifetime. RESULTS: The highest complication rates were seen in the four-corner fusion cohort: 27.1 percent compared to 20.9 percent for total wrist arthroplasty and 17.4 percent for proximal row carpectomy. Secondary surgery was common for all procedures: 87 percent for four-corner fusion, 57 percent for proximal row carpectomy, and 46 percent for total wrist arthroplasty. Proximal row carpectomy generated the highest quality-adjusted life-years (30.5) over the lifetime time horizon, compared to 30.3 quality-adjusted life-years for total wrist arthroplasty and 30.2 quality-adjusted life-years for four-corner fusion. Proximal row carpectomy was the least costly; the mean expected lifetime cost for patients starting with proximal row carpectomy was $6003, compared to $11,033 for total wrist arthroplasty and $13,632 for four-corner fusion. CONCLUSIONS: The authors' analysis suggests that proximal row carpectomy was the most cost-effective strategy, regardless of patient and parameter level uncertainties. These are important findings for policy makers and clinicians working within a universal health care system.
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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 | 0.001 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| 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".