Incidence and Predictive Factors for Orthopedic Surgery in Patients with Psoriatic Arthritis
Bibliographic record
Abstract
OBJECTIVE: To investigate the incidence of orthopedic procedures in patients with psoriatic arthritis (PsA), and how patient characteristics, time of diagnosis, and treatment affect the need for surgery. METHODS: We reviewed the medical history of 1432 patients with possible PsA at Haukeland University Hospital in Bergen, Norway. There were 590 patients (mean age 49 yrs, 52% women) who had sufficient journal information and a confirmed diagnosis of PsA, and who were included in the present study. Relevant orthopedic procedures were obtained from the hospital's administrative patient records. Survival analyses were completed to evaluate the effect of different factors such as year of diagnosis, age, sex, radiographic changes, disease activity, and treatment, on the risk of surgery. RESULTS: There were 171 procedures (25% synovectomies, 15% arthrodesis, and 53% prostheses) performed on 117 patients. These factors all increased the risk of surgery: female sex [relative risk (RR) 1.9, p = 0.001], age ≥ 70 years at diagnosis (RR 2.4, p = 0.001), arthritis in initial radiographs (RR 2.2, p = 0.006), and maximum erythrocyte sedimentation rate 30-59 mm/h (RR 1.6, p = 0.026). Time period of diagnosis had no effect on the outcome. In a subanalysis of surgery exclusive of hip and knee arthroplasty, diagnosis in earlier years (1954-1985 vs 1999-2011) was a risk factor (RR 2.1, p = 0.042). Antirheumatic treatment changed significantly over time. CONCLUSION: There were 20% of patients with PsA who needed surgery. We found that the prognosis of patients with PsA did not change regarding the risk of orthopedic surgery, despite the change in treatment. A possible explanation is the increase in large joint replacements in the general population.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".