Catheter-Induced Postextrasystolic Potentiation in the Assessment of Severity of Low-Gradient Aortic Valve Stenosis
Bibliographic record
Abstract
Background: Deciphering which patients with low-gradient aortic valve disease have severe stenosis can be difficult. We aimed to correlate the postextrasystolic potentiation (PESP) with dobutamine stress echocardiography and multidetector computed tomography in patients with low-gradient aortic valve stenosis. Methods: Patients with an aortic valve area ≤1 cm 2 and a mean gradient <40 mm Hg were included. Aortic valve stenosis severity was assessed by a core lab with dobutamine stress echocardiography, followed by a multidetector computed tomography aortic valve score if indeterminate. A premature ventricular contraction was induced by intentional catheter contact with the myocardium within the left ventricle. PESP was calculated as a percent change of pre-to-post mean gradient. Multidetector computed tomography was used to measure the aortic valve calcification score, and subsequently, aortic valve calcification density. Results: Twenty-eight patients (age, 77±10 years; 19 female) were included. Dobutamine stress echocardiography increased mean gradient from baseline of 25±7 mm Hg to 36±11 mm Hg; pre-premature ventricular contraction mean gradient was 25±7 mm Hg and increased to post-premature ventricular contraction mean gradient of 32±10 mm Hg, representing a PESP of 24±11%. A ≥20% in PESP resulted in 100% sensitivity, 77% specificity, 83% positive predictive value, and 100% negative predictive value for diagnosing severe aortic valve stenosis. There was a significant correlation between PESP and projected aortic valve area and aortic valve calcification density (R=−0.64, P =0.0003; R=0.057, P =0.014, respectively). Conclusions: In patients with low-gradient aortic valve stenosis, catheter-induced premature ventricular contractions during cardiac catheterization causing ≥20% PESP has a 100% sensitivity for severe aortic valve stenosis. Validation of this 20% cutoff in larger groups with correlation to clinical end points is required.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.010 |
| Bibliometrics | 0.000 | 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".