Evidence of Myocardial Edema in Patients With Nonischemic Dilated Cardiomyopathy
Bibliographic record
Abstract
BACKGROUND: Nonischemic dilated cardiomyopathy (DCM) is associated with high mortality and morbidity. Cardiovascular magnetic resonance allows for the noninvasive assessment of function, morphology, and myocardial edema. Activation of inflammatory pathways may play an important role in the etiology of chronic DCM and may also be involved in the disease progression. HYPOTHESIS: The purpose of our study was to assess the incidence of myocardial edema as a marker for myocardial inflammation in patients with nonischemic DCM. METHODS: We examined 31 consecutive patients ( mean age, 57 ± 12 years) with idiopathic DCM. Results were compared with 39 controls matched for gender and age (mean age, 53 ± 13 years). Parameters of left ventricular function and volumes, and electrocardiogram-triggered, T2-weighted, fast spin echo triple inversion recovery sequences were applied in all patients and controls. Variables between patients and controls were compared using t tests for quantitative and χ2 tests for categorical variables. RESULTS: Ejection fraction (EF) was 40.3 ± 7.8% in patients and 62.6 ± 5.0% in controls (P < 0.0001). In T2-weighted images, patients with DCM had a significantly higher normalized global signal intensity ratio compared to controls (2.2 ± 0.6 and 1.8 ± 0.3, respectively, P = 0.0006), consistent with global myocardial edema. There was a significant but moderate negative correlation between signal intensity ratio in T2-weighted images and EF (-0.39, P < 0.001). CONCLUSIONS: Evidence shows that myocardial edema is associated with idiopathic nonischemic DCM. Further studies are needed to assess the clinical and prognostic impact of these findings.
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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) | 0.000 | 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 | 0.001 | 0.000 |
| 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".