Myocardial Fibrosis in Classical Low-Flow, Low-Gradient Aortic Stenosis
Bibliographic record
Abstract
Background Few data exist on the degree of interstitial myocardial fibrosis in patients with classical low-flow, low-gradient aortic stenosis (LFLG-AS) and its association with left ventricular flow reserve (FR) on dobutamine stress echocardiography. This study sought to evaluate the diffuse interstitial fibrosis measured by T1 mapping cardiac magnetic resonance technique in LFLG-AS patients with and without FR. Methods Prospective study including 65 consecutive patients (41 LFLG-AS [mean age, 67.1±8.4 years; 83% men] and 24 high-gradient aortic stenosis used as controls) undergoing dobutamine stress echocardiography to assess FR and cardiac magnetic resonance to determine the extracellular volume (ECV) fraction of the myocardium, indexed ECV (iECV) to body surface area and late gadolinium enhancement. Results Interstitial myocardial fibrosis measured by iECV was higher in patients with LFLG-AS with and without FR as compared with high-gradient aortic stenosis (35.25±9.75 versus 32.93±11.00 versus 21.19±6.47 mL/m 2 , respectively; P <0.001). However, both ECV and iECV levels were similar between LFLG-AS patients with and without FR ( P =0.950 and P =0.701, respectively). Also, FR did not correlate significantly with ECV (r=−0.16, P =0.31) or iECV (r=0.11, P =0.51). Late gadolinium enhancement mass was also similar in patients with versus without FR but lower in high-gradient aortic stenosis (13.3±10.2 versus 10.5±7.5 versus 4.8±5.9 g, respectively; P =0.018). Conclusions Patients with LFLG-AS have higher ECV, iECV, and late gadolinium enhancement mass compared with high-gradient aortic stenosis. Moreover, among patients with LFLG-AS, the degree of myocardial fibrosis was similar in patients with versus those without FR. These findings suggest that diffuse myocardial fibrosis may not be the main factor responsible for the absence of FR in LFLG-AS patients.
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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 | 0.000 | 0.001 |
| 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 | 0.001 |
| 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 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".