A Population-Based Nested Case-Control Study of the Costs of Hip and Knee Replacement Surgery
Bibliographic record
Abstract
BACKGROUND: Studies of total joint arthroplasty (TJA) have not evaluated the costs and outcomes in the context of expected arthritis worsening. OBJECTIVES: Using a cost-consequence approach, to examine changes in direct health care costs and arthritis severity after TJA for hip/knee arthritis compared with contemporaneous changes in matched controls. RESEARCH DESIGN: Case control study nested in a population-based prospective cohort. SUBJECTS: In a population cohort with disabling hip/knee osteoarthritis followed from 1996 to 2003, primary TJA recipients were matched with cohort nonrecipients on age, sex, region of residence, comorbidity, and inflammatory arthritis diagnosis. MEASURES: Pre- and postoperative total and arthritis-attributable direct health care costs, arthritis severity, and general health status were compared for cases and matched controls. RESULTS: Of 2109 participants with no prebaseline TJA, 185 cases received a single elective TJA during the follow-up period; of these, 183 cases and controls were successfully matched. Mean age was 71 years, 77.6% were female, 35.5% had > or =2 comorbidities, and 81.5% had > or =2 joints affected. At baseline, controls had less pain and disability and lower total and arthritis-attributable health care costs than cases. After surgery, although overall health care utilization was unchanged, cases experienced significant decreases in arthritis-attributable costs (mean decrease $278 including prescription drugs) and pain and disability (P < 0.0001 for all). Over the same time period, controls experienced a significant increase in total health care costs (mean increase $1978 including prescription drugs, P = 0.04) and no change or worsening of their arthritis status. CONCLUSION: Compared with matched controls, arthroplasty is associated with significant reductions in pain, disability, and arthritis-attributable direct costs.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".