CT derived ECV in severe aortic stenosis: prognosticator and screening test for co-existent transthyretin cardiac amyloidosis
Bibliographic record
Abstract
Introduction Prior to transcutaneous aortic valve replacement (TAVR), a CT is performed (TAVR-CT). With modification, the CT exam can measure myocardial extracellular volume (ECV). A small increase in ECV occurs in severe aortic stenosis. A large increase in ECV occurs when transthyretin cardiac amyloidosis (ATTR-CA) co-exists. We sought to determine the prognostic potential of ECV in severe aortic stenosis and test the utility of threshold ECV to instigate screening for ATTR-CA. Methods This was a prospective observation study of consecutive severe AS patients undergoing CT -TAVR. A delayed cardiac acquisition was acquired 5 min post TAVR-CT. Pre-contrast and delayed -images were used to determine ECV. When ECV ≥ 31 % 99m Tc-pyrophosphate (PYP) imaging was performed. The primary end point was all cause mortality. Results During the study, 161 patients underwent aortic valve replacement and were included in the analysis. Mean age was 81.6 (±6.2) years. During median follow up of 29 (21–36) months, 24 deaths occurred. In 30 patients ECV ≥ 31 %, 2 had positive 99m Tc-PYP imaging for ATTR-CA. On Cox regression analysis increased ECV associated with increased risk of all cause mortality (HR 2.54 (95 % CI 1.09–5.93) and was incremental to age, LV function and renal impairment ( p = 0.03). Conclusion In severe AS, elevated ECV was a risk for all cause mortality, but this was not related to co-existent ATTR-CA. Threshold-ECV testing for ATTR-CA demonstrated a low yield. Threshold testing may therefore not be warranted in all severe AS patients with an ECV ≥ 31 %.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".