A Multicenter Study of Three-dimensional Echocardiographic Evaluation of Normal Pediatric Left Ventricular Volumes and Function
Bibliographic record
Abstract
Background: Three-dimensional echocardiography (3DE) evaluation of left ventricular (LV) volume and function in pediatrics compares favorably with cardiac magnetic resonance imaging. The aim of this study was to establish from a multicenter, normal pediatric z-score values of 3DE left ventricular volumes and function. Methods: Six hundred and ninety-eight healthy children (ages 0 to 18 years) were recruited from five centers. LV 3DE was acquired from the 4-chamber view. A vendor independent software analyzed end-diastolic volume (EDV), end-systolic volume (ESV), stroke volume (SV), and ejection fraction (EF) using semi-automated quantification. Body surface area (BSA) based z-scores were generated. Intraobserver and interobserver variability were calculated using intraclass correlation (ICC) and repeatability coefficient (RC). Results: Z-scores were generated for ESV, EDV, and SV. The ICC for intraobserver variability for EDV, ESV, and SV were 0.99, 0.99, and 0.99 respectively. The ICC for interobserver variability for EDV, ESV, and SV were 0.98, 0.94, and 0.98 respectively. The RC for intraobserver and interobserver variability for LV EF was 4.39% (95% CI: 3.01, 5.59) and interobserver was 7.08% (95%CI: 5.51, 8.42). Conclusions: We report pediatric Z-scores for normal LV volumes using the semi-automated method from five centers, enhancing its generalizability. 3DE evaluation of LV volumes and EF in pediatric patients is highly reproducible.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".