Abstract O.58: Medium-term Outcomes of Coronary Artery Aneurysms after Kawasaki Disease: A Study from the North American Kawasaki Disease Registry
Bibliographic record
Abstract
Background: One of the main impediments to conceiving and planning studies in children with coronary artery aneurysms (CAA) after Kawasaki disease (KD) is the lack of normative data regarding the prevalence of outcomes over time and risk factors. Methods: The North American Kawasaki Disease Registry was used to determine the prevalence of multiple clinically important outcomes of CAA after KD. All analyses were stratified by severity of CAA (small CAA with z-score = 2.5-5, medium with z-score = 5-10 and giant with z-score >10). All analyses were performed using non-parametric survival analysis. Results: n=621 patients submitted to the Registry had complete follow-up data and were included in the analysis (280 [45%] small CAA, 139 [22%] medium and 202 [33%] giant). Time-related freedom from multiple outcomes stratified by type of CAA are reported in the Table. Reduction in z-scores was strongly associated with the initial size of the lesion, with smaller lesions being more likely to decrease to a normal dimension over time. Thrombosis and stenosis were infrequent in patients without giant CAA. For those patients with giant CAA, the risk of thrombosis, myocardial infarction, angiographically-confirmed stenosis and revascularization was substantial and persisted up to 10 years after diagnosis. In addition to larger luminal diameter, other factors associated with increased risk of adverse outcomes included larger CAA longitudinal area and complex CAA (vs. isolated lesions). Conclusions: Only patients with giant CAA are at substantial risk of adverse clinical outcomes; future trials of pharmacological therapy targeting thrombosis and stenosis risk should focus on these patients.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".