Normative Values of High-Sensitivity Cardiac Troponin T and N-Terminal pro-B-Type Natriuretic Peptide in Children and Adolescents: A Study from the CALIPER Cohort
Bibliographic record
Abstract
BACKGROUND: Cardiac troponin (cTn) and N-terminal pro-B-type natriuretic peptide (NT-proBNP) are increasingly used clinically to evaluate and prognosticate acute myocardial infarction and heart failure, respectively. Pediatric reference intervals and cut-offs have not been established for Roche's Elecsys Troponin T hs (high sensitive) assay. Although pediatric reference intervals exist for NT-proBNP, cut-off values do not exist. In this study, we report reference intervals and 99th percentile cut-offs in a large, healthy Canadian pediatric population using the CALIPER cohort. METHODS: Blood samples from 484 healthy children and adolescents between 0 and <19 years old were recruited from hospital outpatient clinics and community settings. Serum samples were analyzed using Roche's Cobas e411 and evaluated for high-sensitivity cTnT (hs-cTnT) and NT-proBNP concentrations. 95% reference intervals and 99th percentile cut-off values were established. RESULTS: Three hs-cTnT age partitions were established (0 to <6 months, 6 months to <1 year, and 1 to <19 years) with highest concentrations observed in children under 1 year. Two NT-proBNP age partitions were established (0 to <1 year, and 1 to <19 years), also with higher concentrations in infants under 1 year of age. For each of these age partitions, the 99th percentile cut-off, 95% reference interval, and proportion of detectable concentrations were determined. CONCLUSIONS: This is the first study to examine hs-cTnT and NT-proBNP reference values together in a healthy pediatric cohort without other clinical indications. We present 99th percentile cut-offs, which will allow clinicians to appropriately evaluate cardiovascular disease in children and adolescents.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".