Imaging in Patients with Suspected Acute Heart Failure: Timeline Approach Position Statement on Behalf of the Heart Failure Association of the European Society of Cardiology
Bibliographic record
Abstract
Acute heart failure is one of the main diagnostic and therapeutic challenges in clinical practice due to a non-specific clinical manifestation and the urgent need for timely and tailored management at the same time. In this position statement, the Heart Failure Association aims to systematize the use of various imaging methods in accordance with the timeline of acute heart failure care proposed in the recent guidelines of the European Society of Cardiology. During the first hours of admission the point-of-care focused cardiac and lung ultrasound examination is an invaluable tool for rapid differential diagnosis of acute dyspnoea, which is highly feasible and relatively easy to learn. Several portable and stationary imaging modalities are being increasingly used for the evaluation of cardiac structure and function, haemodynamic and volume status, precipitating myocardial ischaemia or valvular abnormalities, and systemic and pulmonary congestion. This paper emphasizes the central role of the full echocardiographic examination in the identification of heart failure aetiology, severity of cardiac dysfunction, indications for specific heart failure therapy, and risk stratification. Correct evaluation of cardiac filling pressures and accurate prognostication may help to prevent unscheduled short-term readmission. Alternative advanced imaging modalities should be considered to assist patient management in the pre- and post-discharge phase, including cardiac magnetic resonance, computed tomography, nuclear studies, and coronary angiography. The Heart Failure Association addresses this paper to the wide spectrum of acute care and heart failure specialists, highlighting the value of all available imaging techniques at specific stages and in common clinical scenarios of acute heart failure.
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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 | 0.006 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.007 | 0.008 |
| Insufficient payload (model declined to judge) | 0.005 | 0.005 |
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".