Diagnosis and Management of Patients with Left Ventricular Hypertrophy: Role of Multimodality Cardiac Imaging. A Scientific Statement of the Heart Failure Association of the European Society of Cardiology
Bibliographic record
Abstract
Left ventricular (LV) hypertrophy consists in an increased LV wall thickness. LV hypertrophy can be either secondary, in response to pressure or volume overload, or primary, i.e. not explained solely by abnormal loading conditions. Primary LV hypertrophy may be due to gene mutations or to the deposition or storage of abnormal substances in the extracellular spaces or within the cardiomyocytes (more appropriately defined as pseudohypertrophy). LV hypertrophy is often a precursor to subsequent development of heart failure. Cardiovascular imaging plays a key role in the assessment of LV hypertrophy. Echocardiography, the first-line imaging technique, allows a comprehensive assessment of LV systolic and diastolic function. Cardiovascular magnetic resonance provides added value as it measures accurately LV and right ventricular volumes and mass and characterizes myocardial tissue properties, which may provide important clues to the final diagnosis. Additionally, scintigraphy with bone tracers is included in the diagnostic algorithm of cardiac amyloidosis. Once the diagnosis is established, imaging findings may help predict future disease evolution and inform therapy and follow-up. This consensus document by the Heart Failure Association of the European Society of Cardiology provides an overview of the role of different cardiac imaging techniques for the differential diagnosis and management of patients with LV hypertrophy.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".