T2-weighted cardiovascular magnetic resonance in acute cardiac disease
Bibliographic record
Abstract
Cardiovascular magnetic resonance (CMR) using T2-weighted sequences can visualize myocardial edema. When compared to previous protocols, newer pulse sequences with substantially improved image quality have increased its clinical utility. The assessment of myocardial edema provides useful incremental diagnostic and prognostic information in a variety of clinical settings associated with acute myocardial injury. In patients with acute chest pain, T2-weighted CMR is able to identify acute or recent myocardial ischemic injury and has been employed to distinguish acute coronary syndrome (ACS) from non-ACS as well as acute from chronic myocardial infarction.T2-weighted CMR can also be used to determine the area at risk in reperfused and non-reperfused infarction. When combined with contrast-enhanced imaging, the salvaged area and thus the success of early coronary revascularization can be quantified. Strong evidence for the prognostic value of myocardial salvage has enabled its use as a primary endpoint in clinical trials. The present article reviews the current evidence and clinical applications for T2-weighted CMR in acute cardiac disease and gives an outlook on future developments."The principle of all things is water"Thales of Miletus (624 BC - 546 BC).
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".