Cardiac Biomarkers in Pediatrics: An Undervalued Resource
Bibliographic record
Abstract
BACKGROUND: The clinical use of common cardiac biomarkers, such as brain natriuretic peptides and troponins, has traditionally been limited to adult populations in the assessment of heart failure and acute coronary syndrome, respectively. While many have discounted the value of these markers in pediatric populations, emerging evidence suggests they may be useful in the diagnosis and prognostication of many cardiac and noncardiac pathologies in neonates, children, and adolescents, and an increasing number of pediatric hospitals are routinely measuring cardiac markers in their clinical practice. CONTENT: This review summarizes and critically evaluates the current literature regarding the application of cardiac biomarkers for clinical decision-making in the pediatric population. Main potential clinical indications discussed herein include primary cardiac disease, immune-related conditions, and noncardiac disease. Important diagnostic and interpretative challenges are also described in relation to each potential indication. SUMMARY: Despite a general lack of clinical awareness regarding the value of cardiac biomarkers in pediatrics, there is increasing literature to support their application in various contexts. Cardiac biomarkers should be considered an undervalued resource in the pediatric population with potential value in the diagnosis and prognosis of myocarditis, congenital heart disease, and heart failure, as well as in the assessment of severity and cardiac involvement in immune-related and other systemic conditions. While interpretation remains challenging in pediatrics due to the age- and sex-specific dynamics occurring throughout growth and development, this should not prevent their application. Future research should focus on defining evidence-based cut-offs for specific indications using the most up-to-date assays.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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".