Variation in the management and treatment of children with giant coronary artery aneurysm following Kawasaki disease
Bibliographic record
Abstract
OBJECTIVES: Giant coronary artery aneurysms are rare but potentially fatal complications of Kawasaki disease. The lack of evidence-based recommendations on their management and treatment cause guidelines and practices to differ. We aimed to assess these variations. METHODS: An anonymous online survey regarding surveillance, imaging, pharmacological management, and interventional practices was distributed among 134 physicians attending to Kawasaki disease patients worldwide. A p-value of <0.05 was deemed significant. RESULTS: The majority (60%) of respondents were general paediatric cardiologists, and 29% interventional specialists. The average years in practice was 15 ± 9.6. Physicians from Asia had the most experience with giant coronary artery aneurysms. American practitioners preferred combining anticoagulants with aspirin. Beta-blockers and statins were more likely used in teenagers versus younger children. Cardiac catheterisation was most (52%) chosen for coronary surveillance in patients with echocardiogram anomalies, followed by Coronary CT-angiography. The indications for coronary intervention were split among respondents, regardless of geographic region or experience. The preferred treatment of coronary stenosis was percutaneous intervention (69%) versus bypass surgery. For thrombosis, thrombolytics (50%) were preferred over percutaneous (39%) and surgical (11%) interventions. Most (92%) preferred intervening in young children in a paediatric facility but were split between a paediatric and adult facility for older children. Most chose combined management by adult and paediatric specialists for either age-scenarios (70, 82%). CONCLUSION: As identified by our study, the lack of large studies and evidence-based recommendations cause uncertainty and ambivalence towards certain treatments. International collaborative efforts are needed to provide more robust evidence in the management of these 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 | 0.001 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".