High-Sensitive Cardiac Troponin for Prediction of Clinical Heart Failure
Bibliographic record
Abstract
Heart failure (HF) prevalence continues to rise, and projections show that in the next 2 decades, ≈45% more HF cases will occur, with a mortality rate remaining as high as 50% within 5 years of diagnosis and high healthcare costs.Hence, there is an unmet need to apply successful preventive programs and reduce HF incidence.Also, according to current guidelines, an effective HF preventive program requires adequately targeting the preclinical stages of the disease, including risk factors for HF, such as hypertension, diabetes mellitus, renal dysfunction, coronary artery disease, and abnormalities of cardiac structure/function associated with HF, such as left ventricular (LV) hypertrophy and low LV ejection fraction. 1ecently, efforts to better identify subjects at the highest risk were undertaken.Different biomarkers have been studied for this purpose.Although many candidate biomarkers have been described, few have made the difficult translation from initial promise to clinical application. 2mong biomarkers, high-sensitivity cardiac troponin (hs-cTn) can detect small amounts of myocyte injury.Using high-sensitivity assays, detectable levels of cardiac troponin have been demonstrated among apparently healthy individuals in the general population, including stage A HF, as well as in asymptomatic individuals with stable cardiovascular disease, stage B HF, with a prevalence of detectable levels, ranging from 60% to 80% in asymptomatic individuals. 3,4s-cTn elevation may be caused by multiple mechanisms, in addition to myocardial necrosis.These include cardiomyocyte damage from inflammatory cytokines or oxidative stress, apoptosis, increased cell membrane permeability induced by increased stretch or stress with troponin release by injured but still viable cells, fragmentation of altered troponins with release into the circulation of fragments with an affinity for the troponins immunoassays, and production of membranous blebs containing troponins that could release them in the bloodstream. 5Thus, hs-cTn release may not only occur in the setting of myocardial injury related to atherosclerotic coronary heart disease but may be also an expression of other structural phenotypes correlated to HF risk, such as increased LV mass. 3 Among 4221 participants in the Cardiovascular Health Study, those with the highest troponin T (TnT) concentrations had a 5-and 6-fold increase in the incidence of death and HF, respectively, compared with those with undetectable cTnT levels, and serial measurements further improved risk classification. 4Of note, it has been demonstrated that the predictive characteristics of hs-cTn for HF or major adverse cardiovascular events in the community are superior as compared with other biomarkers, such as galectin-3 and high-sensitivity C-reactive protein. 6Conversely, hs-cTn and NT-proBNP (N-Terminal Pro-B-Type Natriuretic Peptide) predictivity seem to be complementary, reflecting different mechanisms of HF, such as myocardial injury as compared with increased wall stress. 7High-Sensitive Cardiac Troponin for Prediction of Clinical Heart Failure Are We Ready for Prime Time?
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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 | 0.002 | 0.004 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".