Cardiac myosin‐binding protein <scp>C</scp> in the diagnosis and risk stratification of acute heart failure
Bibliographic record
Abstract
AIMS: Cardiac myosin-binding protein C (cMyC) seems to be even more sensitive in the quantification of cardiomyocyte injury vs. high-sensitivity cardiac troponin, and may therefore have diagnostic and prognostic utility. METHODS AND RESULTS: In a prospective multicentre diagnostic study, cMyC, high-sensitivity cardiac troponin T (hs-cTnT), and N-terminal pro-B-type natriuretic peptide (NT-proBNP) plasma concentrations were measured in blinded fashion in patients presenting to the emergency department with acute dyspnoea. Two independent cardiologists centrally adjudicated the final diagnosis. Diagnostic accuracy for acute heart failure (AHF) was quantified by the area under the receiver operating characteristic curve (AUC). All-cause mortality within 360 days was the prognostic endpoint. Among 1083 patients eligible for diagnostic analysis, 51% had AHF. cMyC concentrations at presentation were higher among AHF patients vs. patients with other final diagnoses [72 (interquartile range, IQR 39-156) vs. 22 ng/L (IQR 12-42), P < 0.001)]. cMyC's AUC was high [0.81, 95% confidence interval (CI) 0.78-0.83], higher than hs-cTnT's (0.79, 95% CI 0.76-0.82, P = 0.081) and lower than NT-proBNP's (0.91, 95% CI 0.89-0.93, P < 0.001). Among 794 AHF patients eligible for prognostic analysis, 28% died within 360 days; cMyC plasma concentrations above the median indicated increased risk of death (hazard ratio 2.19, 95% CI 1.66-2.89; P < 0.001). cMyC's prognostic accuracy was comparable with NT-proBNP's and hs-cTnT's. cMyC did not independently predict all-cause mortality when used in validated multivariable regression models. In novel multivariable regression models including medication, age, left ventricular ejection fraction, and discharge creatinine, cMyC remained an independent predictor of death and had no interactions with medical therapies at discharge. CONCLUSION: Cardiac myosin-binding protein C may aid physicians in the rapid triage of patients with suspected AHF.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".