The Electrocardiogram in the Diagnosis and Management of Patients with Dilated Cardiomyopathy
Bibliographic record
Abstract
The term dilated cardiomyopathy (DCM) defines a heterogeneous group of cardiac disorders, which are characterized by left ventricular or biventricular dilatation and systolic dysfunction in the absence of abnormal loading conditions or coronary artery disease sufficient to cause global systolic impairment. In approximately one third of cases, DCM is familial with a genetic pathogenesis and various patterns of inheritance. Although the electrocardiogram (ECG) has been considered traditionally non-specific in DCM, the recently acquired knowledge of the genotype-phenotype correlations provides novel opportunities to identify patterns and abnormalities that may point toward specific DCM subtypes. A learned ECG interpretation in combination with an appropriate use of other ECG-based techniques including ambulatory ECG monitoring, exercise tolerance test and imaging modalities, such as echocardiography and cardiovascular magnetic resonance, may allow the early identification of specific genetic or acquired forms of DCM. Furthermore, ECG abnormalities may reflect the severity of the disease and provide a useful tool in risk stratification and management. In the present review, we discuss the current role of the ECG in the diagnosis and management of DCM. We describe various clinical settings where the appropriate use and interpretation of the ECG can provide invaluable clues, contributing to the important role of this basic tool as cardiovascular medicine evolves.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".