Progression of aortic stenosis after an acute myocardial infarction
Bibliographic record
Abstract
Background Myocardial infarction (MI) has been shown to induce fibrotic remodelling of the mitral and tricuspid valves. It is unknown whether MI also induces pathological remodelling of the aortic valve and alters aortic stenosis (AS) progression. We thus compared AS progression after an acute MI and in patients with/without history of MI, and assessed post-MI pathobiological changes within the aortic valve leaflets in a sheep model. Methods Serial echocardiograms in human patients with AS were retrospectively analysed and compared between 3 groups: (1) acute MI at baseline (n=68), (2) prior history of MI (n=45) and (3) controls without MI (n=101). Annualised progression rates of AS severity were compared between these 3 groups. In addition, aortic valves were harvested from 15 sheep: (1) induced inferior MI (n=10) and (2) controls without MI (n=5), for biological and histological analyses. Results In humans, the acute MI, previous MI and control groups had comparable baseline AS severity. Indexed aortic valve area (AVA i ) declined faster in the acute MI group compared with controls (−0.07±0.06 vs −0.04±0.04 cm 2 /m 2 /year; p=0.004). After adjustment, acute MI status was significantly associated with faster AVA i progression (mean difference: −0.013 (95% CI −0.023 to −0.003) cm 2 /m 2 /year, p=0.008). In the post-MI experimental animal model, aortic valve thickness and qualitative/quantitative expression of collagen were significantly increased compared with controls. Conclusions The results of this study suggest that AS progression is accelerated following acute MI, which could be caused by increased collagen production and thickening of the aortic valve after the ischaemic event.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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) | 0.001 | 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 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".