Identification of pulmonary artery stiffening due to left heart disease by ultrasonography
Bibliographic record
Abstract
AIMS: Pulmonary hypertension (PH) is a common complication of left heart disease (LHD) that leads to right heart failure and death. Pulmonary artery (PA) stiffening has recently emerged as an important diagnostic and prognostic parameter in PH. The present study aimed to develop and validate an ultrasonographic index to identify PA stiffening in PH due to LHD. METHODS AND RESULTS: First, ultrasonographic stiffness index (US-SI) was derived from pulmonary arterial (PA) radial strain (PA-RS), diameter, and stroke volume in rat model and correlated with ex vivo measured 'true' PA stiffness E. Then, US-SI was validated in a cohort of 24 LHD patients with or without PH prior to heart transplantation and again compared with 'true' PA stiffness measured ex vivo in collected PA specimens. In rats, ultrasonographic PA-RS and US-SI correlated closely with E, and both were able to detect 'true' PA stiffening with ≥80% sensitivity and specificity. In LHD patients, even though ultrasonographic right PA radial strain or US-SI correlated similarly with E, observer assessment and testing for diagnostic validity identified US-SI as more robust and accurate method that detects 'true' PA stiffening with 83.3% sensitivity and 95.8% specificity. CONCLUSIONS: Both PA strain and US-SI allow for ultrasonographic detection of PA stiffening in patients or animal models with LHD; however, US-SI identifies patients with stiffened PA with higher diagnostic validity and accuracy.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.000 |
| 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".