Systolic-diastolic functional coupling in healthy children and in those with dilated cardiomyopathy
Bibliographic record
Abstract
Systolic and diastolic function affect dilated cardiomyopathy (DCM) outcomes. However, systolic-diastolic coupling, as a distinct characteristic, may itself affect function but is poorly characterized. We hypothesized that echocardiographic left ventricular (LV) longitudinal systolic tissue velocities (S') correlate with diastolic longitudinal velocities (E') and that their relationship is associated with ventricular function and that this relationship is impaired in pediatric DCM. We analyzed data from the Pediatric Heart Network Ventricular Volume Variability study, using linear regression and generalized additive modeling to assess relationships between S' and E' at the lateral and septal mitral annulus. We explored relationships between the systolic:diastolic (S:D) coupling ratio (S':E' relative to age) and ventricular function. Up to 4 echocardiograms from 130 DCM patients (mean age: 9.3 ± 6.1 yr) and 1 echocardiogram from each of 591 healthy controls were analyzed. S' and E' were linearly related in controls (r = 0.64, P < 0.001) and DCM (r = 0.83, P < 0.001). In DCM, the magnitude of association between S' and E' was reduced with progressive ventricular remodeling. The S:D ratio was more strongly associated with LV function in controls vs. DCM. The septal S:D ratio was higher (presumed worse) in DCM vs. controls (0.69 ± 0.13 vs. 0.62 ± 0.12, P = 0.001). A higher septal S:D ratio was associated with worse LV dimensions (parameter estimate: 0.0061, P = 0.004), mass (parameter estimate: 0.0074, P = 0.002), ejection fraction (parameter estimate: -0.0303, P = 0.024), and inflow propagation (parameter estimate: -0.3538, P < .001). S:D coupling becomes weaker in DCM with LV remodeling and dysfunction. The S:D coupling ratio may be useful to assess coupling, warranting study in relation to patient outcomes.
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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 | 0.000 | 0.002 |
| 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".