Long-term Management of Kawasaki Disease: Implications for the Adult Patient
Bibliographic record
Abstract
Coronary artery complications from Kawasaki disease (KD) range from no involvement to giant coronary artery aneurysms (CAA). Current long-term management protocols are calibrated to the degree of maximal and current coronary artery involvement reflecting the known likelihood of severe long-term cardiac complications. It has recently been suggested that all KD patients may be at potential risk of severe long-term cardiac complications. If this assertion was to be confirmed, current follow-up protocols would need to be extensively modified, with important implications both for the growing adult population with a previous history of KD and for the healthcare system. Based on the available evidence, patients with multiple large and/or giant CAA are at substantial risk of severe long-term cardiac complications and should have regular specialized follow-up. Patients with transient or no CAA have not been reported to be at risk of severe long-term cardiac complications. The influence of KD on the atherosclerotic process remains suboptimally defined, and should be the focus of future studies. Heightened cardiovascular risk factor surveillance and management is recommended regardless of coronary artery involvement. Based on the currently available evidence, existing long-term management protocols seem to be appropriately calibrated to the level of risk. Revised long-term management protocols should incorporate newer, noninvasive imaging methods and intensive management of atherosclerotic risk. There is insufficient evidence at this time to mandate long-term specialized follow-up and invasive testing for patients who have not had CAA.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".