Increased Rates of Both Knee and Hip Arthroplasties in Older Patients with Ankylosing Spondylitis
Bibliographic record
Abstract
OBJECTIVE: To determine the risks of primary total hip arthroplasty (THA) and total knee arthroplasty (TKA) in older patients with ankylosing spondylitis (AS). METHODS: We used administrative data from 1999 to 2013 on US Medicare beneficiaries to identify patients (< 75 yrs old) with AS and a comparison group without AS. Rates of primary THA and primary TKA were computed for each group, and standardized for age, sex, and race. We also examined risks of primary TKA among patients with AS by their THA status. RESULTS: We analyzed 52,568 patients with AS and 4,617,179 patients without AS. Between 1999 and 2013, the standardized incidence of primary THA in patients with AS doubled from 4.5 per 1000 patient-years (PY) to 9.6 per 1000 PY. Rates of primary TKA were higher in patients with AS than controls in all years. In 2013, the standardized incidence of primary TKA in AS was 12.3 per 1000 PY versus 5.7 per 1000 PY in the comparison group (RR 2.14, 95% CI 1.93-2.38). Rates of primary TKA were twice as high among patients with AS and THA than among those without THA (20.4 vs 10.2 per 1000 PY). CONCLUSION: Rates of THA in older patients with AS doubled over recent years, outpacing the increase in the general population. Rates of TKA were also substantially higher in older patients with AS. The increased risk of TKA in AS may be a consequence of damage from knee inflammation, or alterations in lower extremity biomechanics due to hip arthritis.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".