A meta-analysis of avascular necrosis in systemic lupus erythematosus: prevalence and risk factors.
Bibliographic record
Abstract
OBJECTIVES: To determine the prevalence of and risk factors for avascular necrosis (AVN) in systemic lupus erythematosus (SLE). METHODS: MEDLINE, CINAHL, Web of Science, EMBASE and Cochrane Library were searched from inception to July, 2015 and a random effects model was used to combine frequencies; study quality was assessed using STROBE. RESULTS: 2,041 citations identified 62 articles. Many results had high heterogeneity. The prevalence of symptomatic AVN was 9% (range 0.8%-33%) in SLE and 29% for asymptomatic AVN; femoral head was the most common location (8.0%). High-dose corticosteroids (CS) any CS use, maximum and cumulative dose, pulse therapy, and CS side-effects (hypertension, Cushings, but not diabetes mellitus or hyperlipidaemia) were associated with AVN, as was active SLE (cutaneous vasculitis, renal and neuropsychiatric manifestations, serositis, cytopenias) and Sjögren's, Raynaud's phenomenon, arthritis, cyclophosphamide (but not azathioprine mycophenolate mofetil, or methotrexate) and more damage (excluding musculoskeletal system). Antimalarial drugs were not protective. Rashes and oral ulcers were not associated with AVN. Mean daily dose of CS and duration of CS use had no impact on AVN occurence. Autoantibodies and other immunological markers did not predispose to AVN, except IgM anticardiolipin antibodies which doubled the risk. African Americans experienced more AVN (OR 1.8, p=0.04). CONCLUSIONS: AVN may occur in 1/3 of patients with SLE and 9% with symptoms. Features of active organ SLE (CNS, renal, cutaneous vasculitis, serositis, cytopenias) are associated with AVN as are CS, especially early in disease and at high doses. Those with early CS side-effects seem to have the highest risk of AVN.
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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 | 0.019 | 0.032 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.018 | 0.054 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".