The Long-term Cardiac and Noncardiac Prognosis of Kawasaki Disease: A Systematic Review
Bibliographic record
Abstract
CONTEXT: It is uncertain if children with Kawasaki Disease (KD) are at risk for non-cardiac diseases and if children with KD but without coronary artery aneurysms (CAA) are at risk for long-term cardiac complications. OBJECTIVE: To determine the long-term mortality and prognosis of children after KD. DATA SOURCES: Medline, Embase, and the Cochrane Central Register. STUDY SELECTION: Controlled trials and observational studies were included if they included children with KD and reported mortality, major adverse cardiovascular events (MACE), chronic cardiac or other disease over an average follow-up of ≥1 year. DATA EXTRACTION: Data extracted included sample size, age at diagnosis, the proportion with coronary artery aneurysms (CAA), follow-up duration, and outcome(s). RESULTS: Seventy-four studies were included. Thirty-six studies reported mortality, 55 reported a cardiac outcome, and 12 reported a noncardiac outcome. Survival ranged from 92% to 99% at 10 years, 85% to 99% at 20 years, and 88% to 94% at 30 years. MACE-free survival, mostly studied in those with CAA, varied from 66% to 91% at 10 years, 29% to 74% at 20 years, and 36% to 96% at 30 years. Seven of 10 studies reported an increased risk in early atherosclerosis. All 6 included studies demonstrated an increased risk in allergic diseases. LIMITATIONS: Our study may have missed associated chronic comorbidities because short-term studies were excluded. The majority of outcomes were evaluated in East-Asian patients, which may limit generalizability. Studies frequently excluded patients without CAA and did not compare outcomes to a comparison group. CONCLUSIONS: Studies demonstrate >90% survival up to 30 years follow-up. MACE is observed in children with CAA, but is not well studied in those without 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 | 0.006 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.006 |
| Bibliometrics | 0.007 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".