Cardiac myosin-binding protein C is a novel marker of myocardial injury and fibrosis in aortic stenosis
Bibliographic record
Abstract
OBJECTIVE: Cardiac myosin-binding protein C (cMyC) is an abundant sarcomeric protein and novel highly specific marker of myocardial injury. Myocyte death characterises the transition from hypertrophy to replacement myocardial fibrosis in advanced aortic stenosis. We hypothesised that serum cMyC concentrations would be associated with cardiac structure and outcomes in patients with aortic stenosis. METHODS: cMyC was measured in two cohorts in which serum had previously been prospectively collected: a mechanism cohort of patients with aortic stenosis (n=161) and healthy controls (n=46) who underwent cardiac MRI, and an outcome cohort with aortic stenosis (n=104) followed for a median of 11.3 years. RESULTS: per log unit increase in cMyC, P<0.001), fibrosis volume (adjusted β=8.0 g, P<0.001) and extracellular volume (adjusted β=1.3%, P=0.01) in patients with aortic stenosis but not in controls. In those with late gadolinium enhancement (LGE) indicative of myocardial fibrosis, cMyC concentrations were higher (32 (21-56) ng/L vs 17 (12-24) ng/L without LGE, P<0.001). cMyC was unrelated to coronary calcium scores. Unadjusted Cox proportional hazards analysis in the outcome cohort showed greater all-cause mortality (HR 1.49 per unit increase in log cMyC, 95% CI 1.11 to 2.01, P=0.009). CONCLUSIONS: Serum cMyC concentration is associated with myocardial hypertrophy, fibrosis and an increased risk of mortality in aortic stenosis. The quantification of serum sarcomeric protein concentrations provides objective measures of disease severity and their clinical utility to monitor the progression of aortic stenosis merits further study. CLINICAL TRIAL REGISTRATION: NCT1755936; Post-results.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".