Video densitometric assessment of aortic regurgitation after transcatheter aortic valve implantation: results from the Brazilian TAVI registry
Why this work is in the frame
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Bibliographic record
Abstract
AIMS: We sought to examine the feasibility and reproducibility of a new video densitometric (VD) quantification of aortic regurgitation (AR) on aortography, and its long-term clinical impact. METHODS AND RESULTS: Using dedicated video densitometry software, AR after TAVI was quantified, and inter- and intra-observer reproducibility was investigated in 182 aortograms of the Brazilian TAVI registry. The aortograms were analysed using two software algorithms: 1) the quantitative regurgitation analysis (qRA) index interrogating the entire left ventricle (LV), and 2) a new method with the left ventricle outflow tract (LVOT) as a region of interest (ROI) (LVOT-AR). LVOT-AR was feasible in 64.8% vs. 29.7% of aortograms, compared with qRA index. Using the LVOT-AR, inter-observer variability was low (mean difference±standard deviation [SD]: 0.01±0.05, p=0.53), and the two observers' measurements were highly correlated (r=0.95, p<0.001). Patients with LVOT-AR >0.17 had a significantly higher one-year all-cause mortality risk compared with patients with LVOT-AR ≤0.17 (37.1% vs. 11.2%, p=0.0008). CONCLUSIONS: This study proposes an alternative methodology for AR assessment after TAVI by using the LVOT method (LVOT-AR) of VD angiography. The assessment of LVOT-AR is feasible, reproducible and potentially predictive of one-year mortality.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| 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 it