The continuing challenge of evaluating diastolic function by echocardiography in children
Bibliographic record
Abstract
PURPOSE OF REVIEW: Assessment of diastolic function by echocardiography is challenging but important. Left ventricular filling has been more extensively studied than the right ventricle, and predominantly in adult populations. Although multiple parameters exist to assess diastolic function, they all have limitations, including load and heart rate dependency, which make assessment of diastolic function particularly challenging. The purpose of this article is to review evolving concepts and modalities for echo assessment of diastolic function in children. RECENT FINDINGS: The paradigm whereby diastolic dysfunction severity progresses in a staged fashion from impaired relaxation to increasing ventricular stiffness, may not apply in children. In addition, previous adult guidelines are not readily applicable to children with cardiomyopathy and the applicability of the newly revised adult guidelines needs to be evaluated in children. It is unlikely that any one single echocardiographic diastolic parameter will adequately reflect diastolic function. Hence, parameters derived from atrioventricular valve inflow, pulmonary venous, and tissue Doppler need to be integrated. Newer modalities such as diastolic strain rate and rotation mechanics may be useful as more sensitive markers of early ventricular dysfunction but have important limitations and require more evaluation before routine use in practice. Assessment of systolic-diastolic coupling may enhance assessment of diastolic function. SUMMARY: Diastolic function impacts outcomes and should be part of routine echocardiographic assessment of function. An integrative approach combining different parameters, possibly with contribution of newer modalities in the future, is required.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".