High Prevalence of Cardiac Amyloidosis in Clinically Significant Aortic Stenosis: A Meta-Analysis
Bibliographic record
Abstract
Background: There is growing evidence of coexistence of aortic stenosis (AS) and transthyretin cardiac amyloidosis (CA). Not screening AS patients at the time of hospital/clinic visit for CA represents a lost opportunity. Methods: We surveyed studies that reported the prevalence of CA among AS patients. Studies that compared patients with aortic stenosis with cardiac amyloidosis (AS-CA) and AS alone were further analyzed, and meta-regression was performed. Results: We identified nine studies with 1,321 patients of AS, of which 131 patients had concomitant CA, with a prevalence of 11%. When compared to AS-alone, the patients with AS-CA were older, more likely to be males, had higher prevalence of carpal tunnel syndrome, right bundle branch block. On echocardiogram, patients with AS-CA had thicker interventricular septum, higher left ventricular mass index (LVMI), lower myocardial contraction fraction, and lower stroke volume index. Classical low-flow low-gradient (LFLG) physiology was more common among patients with AS-CA. Patients with AS-CA had higher all-cause mortality than patients with AS alone (33% vs. 22%, P = 0.02) in a follow-up period of at least 1 year. Conclusions: CA has a high prevalence in patients with AS and is associated with worse clinical, imaging, and biochemical parameters than patients with AS alone.
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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 | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.016 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".