Ten Years of 2D Longitudinal Strain for Early Myocardial Dysfunction Detection: A Clinical Overview
Bibliographic record
Abstract
In recent years, the role of left ventricular ejection fraction (EF) as the gold standard parameter for the evaluation of systolic function has been questioned, and many efforts have been concentrated in the clinical validation of new noninvasive tools for the study of myocardial contractility. Improvement in the accuracy of speckle-tracking echocardiography has resulted in a large amount of research showing the ability of two-dimensional strain to overcome EF limitations in the majority of primary and secondary heart diseases. Currently, global longitudinal strain (GLS) is considered the most accurate and sensitive parameter for the assessment of early left ventricular dysfunction. This review summarizes the advantages that this measurement can provide in several clinical settings. Moreover, the important cautions that should be considered in making the choice to use GLS also are addressed. Finally, a special focus on bull's-eye polar maps for the assessment of regional changes of longitudinal function and the usefulness of these maps in the differential diagnosis of several diseases is provided.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".