Canadian Rheumatology Association Meeting, Victoria, British Columbia, Canada, March 28–31, 2012
Bibliographic record
Abstract
Objective: Worse outcomes in systemic lupus erythematosus (SLE) patients from lower socioeconomic strata (SES) have been well documented.Low SES is associated with higher chronic stress, which in turn may result in increased inflammation and immune dysfunction.We examined the relationship between SES, autoantibody frequency, and inflammation in SLE patients.Methods: Adult incident and prevalent SLE patients were enrolled in a prospective cohort at a single centre.Sociodemographic variables, data on health-related habits, diagnostic criteria, disease activity, autoantibodies, treatment, and damage were collected annually using standardized tools.SES was measured as educational level achieved and annual household income.Disease activity was evaluated using the Systemic Lupus Activity Measure (SLAM).Organ damage was measured using the SLICC/ACR Damage Index (SDI).Autoantibodies measured included antinuclear antibody, dsDNA antibody, extractable nuclear antigens and anti-phospholipid antibodies.Inflammation was measured using the erythrocyte sedimentation rate (ESR) score from the SLAM.Baseline data was analyzed, testing for differences in ESR score and total number of autoantibodies positive between income and education groups.Significant variables from univariate analyses were then included in multivariate regression models examining for predictors of total autoantibody frequency, ESR score, and organ damage.Results: Two hundred seventy-three patients were enrolled in the cohort, mean disease duration was 13.7 years, and mean age was 48.5 years.Ninety percent were female, 14% had incomes below the poverty line, while 51% had annual incomes >$50,000.Seventy-seven percent had completed high school.No associations were found between SES and autoantibody frequency.Less education and low income were associated with increased ESR scores (p< 0.001, p=0.035 respectively) in univariate analysis.Both income and education were predictors of higher ESR scores in linear regression (p=0.025 and p=0.047 respectively).Higher ESR score and lack of high school completion (p=0.032 and p=0.04 respectively) were predictors of SDI scores when total ACR score, age, and income were included in the regression model.Conclusion: In our cohort, low SES was a predictor of increased inflammation.Both increased inflammation and lower educational attainment were independent predictors of organ damage.Thus inflammation may be a mediating factor between low SES and poor disease outcomes in SLE.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.298 | 0.106 |
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".