Interpretation of Left Ventricular Diastolic Dysfunction in Children With Cardiomyopathy by Echocardiography
Bibliographic record
Abstract
BACKGROUND: Left ventricular diastolic dysfunction (DD) is a key determinant of outcomes in pediatric cardiomyopathy (CM), but remains very challenging to diagnose and classify. Adult paradigms and guidelines relating to DD are currently applied in children. However, it is unknown whether these are applicable to children with CM. We investigated the assessment of DD in children with CM using adult and pediatric echocardiographic criteria and tested whether recent adult guidelines are applicable to this population. METHODS AND RESULTS: Three investigators independently classified diastolic function in 4 study groups: controls, dilated, hypertrophic, and restrictive CM. Agreement among investigators, failure to classify DD, and the reasons for diagnostic failure were determined. The usefulness of individual echo parameters to diagnose and classify DD was assessed. One hundred seventy-five children (aged 0-18 years) were studied. DD diagnostic criteria were discrepant in the majority of patients. Delayed relaxation was diagnosed in only 14% of hypertrophic CM patients and never in dilated CM and restrictive CM, with 50% of those patients having coexisting findings of elevated filling pressures. Many key parameters, such as mitral and pulmonary venous Doppler, were not informative. Agreement among investigators for grading of DD was poor (36% of CM patients). CONCLUSIONS: Assessment of DD in childhood CM seems inadequate using current guidelines. The large range of normal pediatric reference values allows diagnosis of DD in only a small proportion of patients. Key echo parameters to assess DF are not sufficiently discriminatory in this population, and discrepancies between criteria within individuals prevent further classification and result in poor interobserver agreement.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".