Evaluation of Left Atrial Function by Real-time 3-D Echocardiography in Patients with Systemic Lupus Erythematosus
Bibliographic record
Abstract
OBJECTIVE: Left atrial function plays a key role in maintaining an optimal cardiac output. Left ventricular diastolic dysfunction has been reported in systemic lupus erythematosus (SLE), but its effect on left atrial function has been largely overlooked. Our aim was to assess left atrial performance using real-time 3-D echocardiography (RT3DE) technology in patients with SLE. METHODS: Our study included 102 patients with SLE without any cardiac symptoms, and 32 healthy controls. According to the Systemic Lupus International Collaborating Clinics/American College of Rheumatology Damage Index (SDI), all subjects were classified into 3 groups: healthy controls, patients with an SDI = 0, and patients with an SDI ≥ 1. RESULTS: Left atrial volume indexed to body surface area was dilated in subjects with SLE, whereas the left atrial passive emptying fraction (EF) was lower. Left atrial active EF was significantly higher in the SDI = 0 group than in controls (46.4 ± 9.1% vs 30.0 ± 10.3%, p < 0.05); however, it was significantly lower in the SDI ≥ 1 group than in the SDI = 0 group (41.2 ± 9.8% vs 46.4 ± 9.1%, p < 0.05). By multivariate linear analysis, the SDI was independently and positively associated with left atrial volume index and inversely associated with left atrial total function. CONCLUSION: Our study demonstrated that left atrial mechanical function and volume are impaired in SLE, particularly in patients with an SDI ≥ 1 and disease activity. RT3DE may have better diagnostic value than traditional echo indexes in detecting subclinical cardiac dysfunction in patients with SLE.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".