PERFORMANCE OF VALIDATED CARDIOVASCULAR RISK SCORES IN A GLOBAL (UK/US) COHORT OF YOUNG PEOPLE WITH CHILDHOOD-ONSET SYSTEMIC LUPUS ERYTHEMATOSUS STRATIFIED BASED ON CROSS-VALIDATED METABOLOMIC SIGNATURES
Bibliographic record
Abstract
PV159 / #51 Poster Topic: AS18 - Pediatric SLE Background/Purpose Childhood-onset systemic lupus erythematosus (cSLE) is associated with increased cardiovascular disease risk (CVD risk) starting early in life. As a consequence, 4% of children and young people (CYP) with cSLE recruited to a large UK study experienced at least 1 CVD-event 2 years post diagnosis, at a median age of 16 years. The APPLE trial, a large interventional clinical trial in cSLE, evaluated the efficacy of atorvastatin in decreasing atherosclerosis progression in CYP aged 10-18 years, using serial carotid intima-media thickness (CIMT) measurements. Although the trial did not meet the primary endpoint, it provided the opportunity to discover a novel serum metabolomic signature associated with a high rate of atherosclerosis progression. Methods We explored the comparative performance of 4 age-appropriate and validated CVD risk scores in a global cSLE (UK/US) cohort. Demographic data, CVD risk factors and cSLE characteristics were collected cross-sectionally from 2 cSLE cohorts: a retrospective UCL (University College London) cohort (N=109, UK) and a prospective APPLE trial cohort (N=121) cohort, both stratified based on the metabolomic signature of high CIMT progression, we previously identified in the APPLE trial. QRISK-3, Framingham (FRS), Atherosclerotic Cardiovascular Disease (ASCVD) scores (validated for age 20-25) and the Pathobiological Determinants of Atherosclerosis in Youth (PDAY) score (validated from age ≥14) were calculated and assessed for performance against cross-validated metabolomic signatures of CIMT progression. We used descriptive statistics, area under the curve (AUC), and linear regression analyses. Results All scores had very low performance against CVD risk metabolomic stratification (Table 1). The PDAY score performed best, with 67% specificity, but 50% sensitivity, in correctly classifying CYP with high CVD risk, and only in the slightly older UCL cohort. Linear regression analysis found that age/disease activity were the strongest determinants of PDAY score (1 year increase in age/1 point increase in median SLEDAI-2K score over the disease course were associated with 1.13/0.41 points increase in PDAY score, respectively, when corrected for sex/disease duration/damage/lipid levels/steroids). Table 1 Conclusions In conclusion, in this large study, CVD risk scores, even if validated for ages ≥14, do not adequately capture CVD risk in adolescents with cSLE (APPLE trial cohort). PDAY score performed moderately well for young adults only (UCL cohort), highlighting the need for better CVD risk stratification tools. Future research is warranted for optimized CVD risk identification/management in cSLE.
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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 | 0.005 |
| 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 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".