A Decade of NT-proBNP in Acute Kawasaki Disease, from Physiological Response to Clinical Relevance
Bibliographic record
Abstract
Kawasaki disease (KD) is an inflammatory febrile illness of early childhood and the primary cause of acquired heart disease during childhood. Coronary artery aneurysms (CAA) are a serious complication of KD, leading to ischemic heart disease, myocardial infarction, and sudden cardiac death. Timely diagnosis in the first ten days of fever is crucial to reduce the risk of coronary artery complications. Nitrogen-terminal B-type natriuretic peptide (NT-proBNP), originally used for the management of adults with heart disease, was shown to be useful in the diagnosis and management of patients with KD. NT-proBNP is released by cardiomyocytes in response to mechanical factors such as the dilation of cardiac chambers, and to pro-inflammatory cytokines. The utility of NT-proBNP as a biological marker in KD is based on the universal myocardial inflammatory component early in the course of the disease. Patients with KD have higher NT-proBNP at the time of diagnosis than febrile controls, with a pooled sensitivity of 89% (95% confidence interval 78⁻95), and a specificity of 72% (95% confidence interval 58⁻82). The positive likelihood ratio is 3.2:1 (95% confidence interval 2.1⁻4.8). Moreover, patients with resistance to intravenous immunoglobulin treatment and CAA were found to have higher levels of NT-proBNP, suggesting a prognostic role. Nevertheless, the non-specificity of NT-proBNP to KD limits its use as a stand-alone test. In this light, a tentative associative retrospective diagnostic algorithm was highly reliable for including all cases at risk of CAA, which warrants further prospective studies for a better diagnostic index of suspicion and risk stratification of patients.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".