Inflammatory Joint Diseases and Risk of Cardiovascular Disease in Modern Rheumatology
Bibliographic record
Abstract
In this issue of The Journal , Liew, et al present a cross-sectional study comparing the 10-year atherosclerotic cardiovascular disease (ASCVD) risk score in patients with axial spondyloarthritis (axSpA) versus the general US population. Their hypothesis was that a diagnosis of axSpA would be associated with a higher risk score of ASCVD1. They studied patients with axSpA participating in 2 different cohort studies (followed at the University of California, San Francisco, and University of Texas Houston Health Science Center). Altogether, the cohorts included patients with both radiographic axSpA/ankylosing spondylitis (AS) and nonradiographic axSpA. Patients were followed prospectively with regular data collections. The 10-year ASCVD risk scores were calculated for patients aged 40–75 years without a history of ASCVD and with available measures of blood pressure and laboratory measures of cholesterol. Individuals from The National Health and Nutrition Examination Survey (NHANES) were used as a comparator group and were matched 4:1 to the axSpA patients according to age, sex, and race. After calculating the 10-year ASCVD risk scores for both the axSpA group and the NHANES group, the authors subsequently compared the prevalence ratio for a 10-year ASCVD risk score ≥ 7.5% between the patients with axSpA and the comparator NHANES group, first for the whole axSpA group, and then for the patients with AS (sensitivity analyses). The authors found that the prevalence ratio of the 10-year ASCVD risk score ≥ 7.5% was neither increased in patients with axSpA nor in patients with AS compared to the NHANES controls; this finding was in contrast to their hypothesis that patients with axSpA would have higher ASCVD risk scores. As an explanation of this finding, the authors suggest that the study may be underpowered to find a true difference in ASCVD risk. Alternatively, the results may reflect that the ASCVD risk … Address correspondence to Dr. I.J. Berg, Diakonhjemmet Hospital, Department of Rheumatology, Box 23 Vinderen, 0319 Oslo, Norway. Email: ingerjoridberg{at}gmail.com.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".