Prediction of Cardiovascular Events in Patients with Ankylosing Spondylitis and Psoriatic Arthritis: Role of Lipoproteins in a High-risk Population
Bibliographic record
Abstract
OBJECTIVE: To evaluate lipids and apolipoproteins as predictors of cardiovascular mortality and morbidity (CVD) in patients with spondyloarthritis (SpA). METHODS: In the pooled cohort of participants in the IDEAL, TNT, and CARDS trials, 50 had ankylosing spondylitis (AS), 36 had psoriatic arthritis (PsA), and 21,641 did not have AS or PsA (non-SpA). We compared lipid levels at baseline between AS or PsA and non-SpA, and hazard ratios (HR) for CVD were calculated in a Cox proportional hazard model. RESULTS: Atherogenic lipids were lower in samples from AS, but not in PsA, compared to non-SpA. The HR for 1 SD increase in baseline lipids for future CVD was for total cholesterol 1.39 (95% CI 0.82, 2.36) in AS, 1.01 (95% CI 0.44, 2.31) in PsA, and 1.10 (95% CI 1.07, 1.14) in non-SpA. Both high-density lipoprotein (HDL) and apolipoprotein (ApoA-1) were significantly associated with CVD in AS (HR 3.67, 95% CI 1.47, 9.06, and HR 1.89, 95% CI 1.02, 3.54, respectively), in contrast to PsA (HDL: HR 1.03, 95% CI 0.49, 2.15; ApoA-1: HR 0.79, 95% CI 0.34, 1.89) and non-SpA (HDL: HR 0.86, 95% CI 0.84, 0.89; ApoA-1: HR 0.88, 95% CI 0.85, 0.91). CONCLUSION: HDL and ApoA-1 were surprisingly associated with increased risk of future CVD in patients with AS, whereas these lipids were protective in non-SpA.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".