Bibliographic record
Abstract
Background and aims Antimalarial (AM)-induced cardiomyopathy is an extremely rare complication of AM treatment in systemic lupus erythematosus (SLE). The use of specific cardiac biomarkers may identify patients at risk. We sought to investigate the prevalence and associated factors for abnormal myocardial biomarkers in lupus patients. Methods Consecutive patients (n=179) attending the Toronto Lupus Clinic were enrolled. BNP (brain natriuretic peptide, assessing pressure and/or volume overload) and cTnI (cardiac troponin I, assessing myocardial necrosis) were measured simultaneously. None had ECG abnormalities suggestive of acute coronary syndrome. Analysis was performed with SAS 9.3; p<0.05 was considered significant. Results Twenty-seven patients (15.1%) had elevated BNP and/or cTnI; 11 with prior history of heart failure, coronary artery disease, pulmonary hypertension and/or exertional dyspnea were excluded. Compared to subjects with normal biomarkers, the remaining patients (n=16) were older [54.7±15.1 vs. 47.8±12.2 years, p=0.037], had longer disease duration [22.6±10.4 vs. 15.5±10.1 years, p<0.001], longer AM use [12.5±9.6 vs. 7.9±8 years, p=0.034] and more frequently persistent CPK elevation [44.4 vs. 16.4%, p<0.001]. Multi-variable regression analysis showed chronic AM treatment combined with CPK elevation to be an important predictor for elevated myocardial biomarkers [HR=1.41, 95%CI=1.06–1.89, p=0.02]. Two patients were diagnosed with AM-induced cardiomyopathy on endomyocardial biopsy; both had CPK and BNP/cTnI elevation. Conclusions Approximately 9% of unselected SLE patients had elevated myocardial biomarkers, in the absence of prior cardiac disease. Chronic AM therapy accompanied by persistent CPK elevation conferred an increased risk for abnormal BNP and cTnI, which might predict cardiomyopathy in such patients.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".