Prognostic implications of cardiac damage classification based on computed tomography in severe aortic stenosis
Bibliographic record
Abstract
AIMS: An echocardiographic staging system of severe aortic stenosis (AS) based on additional extra-valvular cardiac damage has been associated with prognosis after transcatheter aortic valve implantation (TAVI). Multidetector row computed tomography (MDCT) is key in the evaluation of AS patients undergoing TAVI and can potentially detect extra-valvular cardiac damage. This study aimed at evaluating the prognostic implications of an MDCT staging system of severe AS in patients undergoing TAVI. METHODS AND RESULTS: A total of 405 patients (80 ± 7 years, 52% men) who underwent full-beat MDCT prior to TAVI were included. The extent of cardiac damage was assessed by MDCT and classified in five categories; Stage 0 (no cardiac damage), Stage 1 (left ventricular damage), Stage 2 (left atrium and mitral valve damage), Stage 3 (right atrial damage), and Stage 4 (right ventricular damage). Twenty-seven (7%) patients were stratified as Stage 0, 96 (24%) as Stage 1, 152 (38%) as Stage 2, 78 (19%) as Stage 3, and 52 (13%) as Stage 4. During a median follow-up of 3.7 (IQR 1.7-5.5) years, 150 (37%) died. On multivariable Cox regression analysis, cardiac damage Stage 3 (HR vs. Stage 0: 4.496, P = 0.039) and Stage 4 (HR vs. Stage 0: 5.565, P = 0.020) were independently associated with all-cause mortality. CONCLUSION: The MDCT-based staging system of cardiac damage in severe AS effectively identifies the patients who are at higher risk of death after TAVI.
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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) | 0.001 | 0.004 |
| 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".