Characterization of Intracardiac Flow in the Right Ventricle With Pressure and Volume Overload in Children
Bibliographic record
Abstract
Background: Blood flow visualization using vector flow mapping (VFM) holds potential as a novel indicator of right ventricular (RV) function. Methods: This study included 12 patients with atrial septal defect (ASD group, mean (± standard deviation) age: 6.2 ± 1.5 years), six patients with pulmonary hypertension (PH group, mean age: 6.8 ± 2.3 years), and 35 healthy, age-matched children (control group, mean age: 7.3 ± 1.6 years). VFM data were obtained from the parasternal RV short-axis view. Results: VFM images in the majority of the control group showed a counterclockwise rotating vortex below the tricuspid anterior leaflet and clockwise vortex below the septal leaflet in early diastole. In late diastole, a clockwise vortex flow appeared at the RV apex to the outflow tract. In the ASD and PH groups, the formation of vortical flow below the tricuspid valve was decreased. Late-diastolic vortices also differed from the control group, with counterclockwise or no vortex flow seen in this phase in these groups. Flow energy loss (EL), kinetic energy (KE) and energetic performance index (EPI) were related to RV systolic and diastolic functions. Mean EL over one cardiac cycle (ELcycle) was significantly higher in the PH group than in the control group (P = 0.0471). KE of the RV inflow tract (KE-RVin) and outflow tract (KE-RVout) were significantly lower in the PH group than in the control and ASD groups (P < 0.05 each). Conclusions: These results suggest that RV vortex formation may be a factor in efficient ejection. EL, KE, and EPI may be applicable to evaluate RV contractility and diastolic function.
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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 | 0.001 |
| 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 | 0.000 | 0.000 |
| 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".