Cardiovascular Risk Scores in Axial Spondyloarthritis Versus the General Population: A Cross-sectional Study
Bibliographic record
Abstract
OBJECTIVE: Cardiovascular (CV) morbidity and mortality are increased in axial spondyloarthritis (axSpA).We conducted a cross-sectional study evaluating the 10-year atherosclerotic cardiovascular disease (ASCVD) risk in axSpA compared to the general US population. METHODS: We included 211 adults, 40-75 years old with ankylosing spondylitis (AS) or nonradiographic axSpA from 2 sites, who had available data on comorbidities, medication use, blood pressure measures, and laboratory cholesterol values. General population comparators from the 2009-2014 National Health and Examination Survey (NHANES) cycles were matched 4:1 to subjects, on age, sex, and race. We estimated the prevalence ratio for a 10-year ASCVD risk score ≥ 7.5% comparing axSpA and matched NHANES comparators using conditional Poisson regression. RESULTS: Overall, subjects were 53.9 ± 11.2 years old, 69% were male, and 74% were White. The mean 10-year ASCVD risk score was 6.7 ± 6.9% for those with axSpA, and 9.0 ± 10.5% for NHANES comparators. Compared to those with axSpA, the prevalence of current smoking and diabetes was higher among NHANES comparators. The estimated prevalence ratio for a 10-year ASCVD risk score ≥ 7.5% comparing those with axSpA and their age-, sex-, and race-matched comparators was 0.96 (95% CI 0.74-1.24). CONCLUSION: The prevalence of a 10-year ASCVD risk score ≥ 7.5% was not significantly different comparing axSpA patients and those drawn from the general population who were similar in terms of age, sex, and race. Future studies should focus on improved CV risk prediction in axSpA, because underestimation by a general population risk score may potentially explain these results.
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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 | 0.002 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".