Abstract 4143704: Systemic Arterial Aneurysms in Kawasaki Disease: An Important Evidence Gap
Bibliographic record
Abstract
Introduction: Non-coronary artery systemic arterial aneurysms (SAA) are a rare and under-reported sequelae of Kawasaki disease (KD), for which data and guidance are limited. Methods: A survey was sent to members of the International KD Registry (IKDR) regarding their experiences and practices with SAA in KD patients. For comparison, a systematic review was conducted following PRISMA methodology; after evaluation, a total of 21 studies with 75 patients total were included. Results were compared qualitatively. Results: Surveys were completed by 48 (56%) of 86 IKDR investigators; 35 (73%) respondents had >10 years of experience caring for KD patients. Experience with SAA was limited, with 33% not having cared for a patient with SAA. Reported screening practices included 81% screening only patients with coronary artery (CA) involvement, 8% reporting screening all patients with KD, and with 11% using other criteria. The degree of CA involvement influenced screening, with 56% screening only those with giant CA aneurysms, 20% also small/medium aneurysms, 6% included dilation and 18% not using any specific CA criteria. Additional factors reported included multiple or rapidly expanding CA aneurysms, clinical features such as prolonged/persistent fever, progressing/persistent elevation of inflammatory markers, and resistance to standard treatment. These screening practices were somewhat concordant with the characteristics of patients with SAA reported in the literature ( FIGURE ). Initial preferred assessment method was CT angiography for 48%, ultrasound 28% and MRI for 24% of respondents. In contrast, SAA reported in the review were most commonly assessed with conventional coronary artery angiography. From the review, SAA were associated with a high rate of regression (62-93%). Longer-term complications reported included SAA thrombosis, calcification, stenosis, occlusion and collateral formation. Clinical and management factors associated with SAA outcomes were not defined. Conclusion: While the development of SAA is a known but rare complication of acute KD, there remains a gap in evidence as to which patients are at risk, best practices for screening and management, and outcomes. Protocol driven cohort studies are needed.
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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 | 0.020 | 0.067 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.009 | 0.011 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".