Abstract 10567: Systolic and Diastolic Myocardial Stiffness of the Right Ventricle Free Wall Assessed by Ultrafast Ultrasound Imaging in Humans: Comparison with Pressure-Volume Loop in Healthy Volunteers and Pulmonary Arterial Hypertension Patients
Bibliographic record
Abstract
Background: Echocardiographic parameters to assess systolic and diastolic RV function are strongly dependent on loading conditions. Myocardial stiffness (MS) is an intrinsic myocardial property that influences both diastolic and systolic cardiac function. MS is independent of loading conditions and pre-clinical studies have demonstrated a correlation between 1) systolic MS and contractility (or ESPVR); 2) end-diastolic MS and compliance (or EDPVR). Shear wave imaging (SWI) by ultrafast ultrasound imaging allows quantitative MS assessment at any time of the cardiac cycle. This noninvasive technique could provide load-independent measure of RV function. Methods (figure 1): Ten children, 5 pulmonary arterial hypertension patients (PAH) undergoing diagnostic right heart catheterization (RHC) were prospectively enrolled as well as 5 age-matched heathy volunteers (HV). MS was assessed at baseline and during FiO2 70%+40ppm NO for the PAH group. MS in the RV free wall using SWI every 100ms during the cardiac cycle. RV-ESPVR and RV-EDPVR were assessed by pressure-volume loops using a pressure catheter and real-time 3D-echo volumes. Results (figure 2): MS increased significatively in systole compared to end-diastole in both groups (p<0.01) and more significantly in the PAH group (p<0.01). In the PAH group, no difference was found in systolic MS between baseline and during FiO2 70%+40ppm NO (p=0.67). Systolic MS correlated with RV-ESPVR (r=0.75). End-diastolic MS correlated with RV-EDP (r=0.76) and RV-EDPVR (r=0.85). Conclusions: Our preliminary data demonstrate that MS could be a quantitative measure of RV contractility and diastolic compliance of the RV.
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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 | 0.000 | 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) | 0.002 | 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".