Laboratory markers of cardiovascular risk in pediatric SLE: the APPLE baseline cohort
Bibliographic record
Abstract
As part of the Atherosclerosis Prevention in Pediatric Lupus Erythematosus (APPLE) Trial, a prospective multicenter cohort of 221 children and adolescents with systemic lupus erythematosus (SLE) (mean age 15.7 years, 83% female) underwent baseline measurement of markers of cardiovascular risk, including fasting levels of high-density lipoprotein (HDL), low-density lipoprotein (LDL), triglycerides (TG), lipoprotein A (Lpa), homocysteine and high-sensitivity C-reactive protein (hs-CRP). A cross-sectional analysis of the baseline laboratory values and clinical characteristics of this cohort was performed. Univariable relationships between the cardiovascular markers of interest and clinical variables were assessed, followed by multivariable linear regression modeling. Mean levels of LDL, HDL, Lpa, TG, hs-CRP and homocysteine were in the normal or borderline ranges. In multivariable analysis, increased Systemic Lupus Erythematosus Disease Activity Index (SLEDAI), prednisone dose, and hypertension (HTN) were independently associated with higher LDL levels. Higher hs-CRP and creatinine clearance were independently related to lower HDL levels. Higher body mass index (BMI), prednisone dose, and homocysteine levels were independently associated with higher TG levels. Only Hispanic or non-White status predicted higher Lpa levels. Proteinuria, higher TG and lower creatinine clearance were independently associated with higher homocysteine levels, while use of multivitamin with folate predicted lower homocysteine levels. Higher BMI, lower HDL, and longer SLE disease duration, but not SLEDAI, were independently associated with higher hs-CRP levels. The R(2) for these models ranged from 7% to 23%. SLE disease activity as measured by the SLEDAI was associated only with higher LDL levels and not with hs-CRP. Markers of renal injury (HTN, proteinuria, and creatinine clearance) were independently associated with levels of LDL, HDL, and homocysteine, highlighting the importance of renal status in the cardiovascular health of children and adolescents with SLE. Future longitudinal analysis of the APPLE cohort is needed to further examine these relationships.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".