Abnormal Cardiac Biomarkers in Patients with Systemic Lupus Erythematosus and No Prior Heart Disease: A Consequence of Antimalarials?
Bibliographic record
Abstract
OBJECTIVE: Cardiac involvement in systemic lupus erythematosus (SLE) is often undiagnosed in its early phases. Specific heart biomarkers may identify patients at risk. We sought to investigate the prevalence and associated factors for such biomarkers in SLE. METHODS: Brain natriuretic peptide (BNP) and cardiac troponin I (cTnI) were measured simultaneously in 151 consecutive patients with no history of heart disease or pulmonary arterial hypertension (PAH). None had electrocardiographic abnormalities suggestive of acute coronary syndrome. Cross-sectional comparisons and logistic regression analyses were performed. Patients with abnormal biomarkers were investigated to delineate the specific cause. RESULTS: Sixteen patients (16/151, 10.6%) had elevated BNP, and 9 of them also had abnormal cTnI. Compared to subjects with normal biomarkers, they were older, had longer disease and antimalarial (AM) use duration, and more frequently persistent creatine phosphokinase (CPK) elevation. Multivariable regression analysis showed prolonged AM treatment (> 5.6 yrs) and persistent CPK elevation to be important predictors for elevated cardiac biomarkers. Six patients were diagnosed with definite (based on endomyocardial biopsy, n = 2) or possible (based on cardiac magnetic resonance after exclusion of other causes) AM-induced cardiomyopathy (AMIC); all had both BNP and cTnI elevated. Alternative causes were identified in 5, while no definitive diagnosis could be made in the remaining patients. CONCLUSION: About 10% of patients with SLE had elevated myocardial biomarkers, in the absence of prior cardiac disease or PAH. One-third of them were diagnosed with AMIC. Prolonged AM therapy and persistent CPK elevation conferred an increased risk for abnormal BNP and cTnI, which might predict AMIC.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".