Intraventricular pressure difference estimation based on blood speckle tracking—invasive validation and early clinical application
Bibliographic record
Abstract
AIMS: Ventricular relaxation creates an intraventricular pressure difference (IVPD) and resultant diastolic suction. Non-invasive estimation by echocardiographic techniques would allow to clinically evaluate IVPD as an important component of diastolic functional assessment. The aims of the current study were to evaluate the accuracy of IVPD estimation based on Blood Speckle Tracking (BST) echocardiography compared with invasive pressure measurements and to clinically apply the method in children with univentricular hearts (UVH) and controls. METHODS AND RESULTS: The accuracy of BST-based IVPD-estimates was assessed in an open-chest porcine model, comparing BST-based IVPD with simultaneous repeated invasive pressure measurements in six pigs using micromanometer catheters. BST-based IVPD assessment during early diastolic filling was performed in 83 healthy controls and 44 patients with UVH and compared between the groups. The validation in pigs included 103 measurements, demonstrating a mean difference of -0.01 mmHg (P = 0.33) and high correlation (r = 0.95, P value < 0.001) between IVPD from BST (-1.31 ± 0.28 mmHg) and invasive measurements (-1.30 ± 0.31 mmHg). In the paediatric patients, age range 6 months-17.76 years, feasibility was 93.9% in controls and 88.6% in UVH patients. Median IVPD was significantly higher in controls compared with UVH (-1.82 vs. -0.88 mmHg, P < 0.001). Intraclass correlation coefficients for variability of clinical BST-data were 0.99 (interobserver) and 0.98 (intraobserver) respectively. CONCLUSION: BST echocardiography provides accurate estimation of IVPD in early diastole. IVPD was significantly lower in children with UVH compared with controls suggesting lower diastolic suction, which can impact overall filling dynamics.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".