Etanercept with IVIg for acute Kawasaki disease: a long-term follow-up on the EATAK trial
Bibliographic record
Abstract
BACKGROUND: The Etanercept as Adjunctive Treatment for Acute Kawasaki Disease, a phase-3 clinical trial, showed that etanercept reduced the prevalence of IVIg resistance in acute Kawasaki disease. In patients who presented with coronary artery involvement, it reduced the maximal size and short-term progression of coronary artery dilation. Following up with this patient group, we evaluated the potential long-term benefit of etanercept for coronary disease. METHODS: Patients were followed for at least 1 year after the trial. The size of dilated arteries (z-score ≥ 2.5) was measured at each follow-up visit. The z-score and size change from baseline were evaluated at each visit and compared between patients who received etanercept versus placebo at the initial trial. RESULTS: Forty patients who received etanercept (22) or placebo (18) in the Etanercept as Adjunctive Treatment for Acute Kawasaki Disease trial were included. All patients showed a persistent decrease in coronary artery size measurement: 23.3 versus 5.9% at the 6-month visit, 24 versus 13.1% at the 1-year visit, and 20.8 versus 19.3% at the ≥ 2-year visit for etanercept or placebo, respectively, with similar results for decrease in coronary artery z-scores. In a multivariate analysis, correcting for patients' growth, a greater size reduction for patients on the etanercept arm versus placebo was proved significant for the 6-month (p = 0.005) and the 1-year visits (p = 0.019) with a similar end outcome at the ≥ 2-year visit. DISCUSSION: Primary adjunctive therapy with etanercept for children with acute Kawasaki disease does not change the end outcome of coronary artery disease but may promote earlier resolution of artery dilation.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".