Occurrence and Effect of Lower Extremity Ulcer in Rheumatoid Arthritis — A Population-based Study
Bibliographic record
Abstract
OBJECTIVE: To assess the occurrence, risk factors, morbidity, and mortality associated with lower extremity (LE) ulcers in patients with rheumatoid arthritis (RA). METHODS: Retrospective review of Olmsted County, Minnesota, USA, residents who first fulfilled the 1987 American College of Rheumatology criteria for RA in 1980-2007 with followup to death, migration, or April 2012. Only LE ulcers that developed after the diagnosis of RA were included. RESULTS: The study included 813 patients with 9771 total person-years of followup. Of them, 125 developed LE ulcers (total of 171 episodes), corresponding to a rate of occurrence of 1.8 episodes per 100 person-years (95% CI: 1.5, 2.0 per 100 person-yrs). The cumulative incidence of first LE ulcers was 4.8% at 5 years after diagnosis of RA and increased to 26.2% by 25 years. Median time for the LE ulcer to heal was 30 days. Ten of 171 episodes (6%) led to amputation. LE ulcers in RA were associated with increased mortality (HR 2.42; 95% CI 1.71, 3.42), adjusted for age, sex, and calendar year. Risk factors for LE ulcers included age (HR 1.73 per 10-yr increase; 95% CI 1.47, 2.04), rheumatoid factor positivity (HR 1.63; 95% CI 1.05, 2.53), presence of rheumatoid nodules (HR 2.14; 95% CI 1.39, 3.31), and venous thromboembolism (HR 2.16; 95% CI 1.07, 4.36). CONCLUSION: LE ulcers are common among patients with RA. The cumulative incidence increased by 1% per year. A significant number require amputation. Patients with RA who have LE ulcers are at a 2-fold risk for premature mortality.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".