Abstract 2: Historical Trends in Kawasaki Disease over Three Decades in a Single Institution
Bibliographic record
Abstract
Purpose: Kawasaki disease (KD) awareness and therapy have evolved since its description in 1967. We explored historical trends since 1984 in patients (pts) treated for KD at a single institution. Methods: Inclusion criteria were 1) first episode of KD, and 2) treated with IVIG within 3 weeks of illness onset. Exclusion criteria were 1) evaluation solely for a second opinion, and 2) presence of congenital heart disease. We reviewed age at diagnosis, sex, race, presence of complete vs. incomplete (fever + <4 clinical criteria), days of fever at initial IVIG treatment, and incidence of retreatment. Changes in pt characteristics over time were evaluated using tests of trends. Results: Of 1739 pts, 1133 met eligibility criteria. Race included 61% White, 10% Black, 11% Asian: 6% other, and 12% unknown. At diagnosis, 16% were age <1 years (yrs), 58% were 1<5 yrs, 24% were 5<12 yrs, and 2% were ≥12 yrs. The median age at fever onset was 3 yrs and has not changed significantly over time. Male to female ratio was 59% to 41% and was stable over time. Median fever duration before IVIG treatment in the whole cohort was 7 days. Within the complete vs. incomplete KD groups, illness day at treatment was stable over time. However, median days of fever before IVIG treatment were lower in pts with complete vs. incomplete criteria (6 vs. 8 days, respectively, p<.001). The % of pts treated with IVIG for incomplete KD increased significantly over time. Before 1989, only 1 pt (2%) was treated with IVIG for incomplete KD. From 1990-1994, 11 pts (15%) pts had incomplete criteria, whereas from 2010-2014, 45 pts (27%) received IVIG treatment with incomplete clinical criteria (p=.001). The incidence of retreatment with IVIG also increased, from 9% (1984-1989) to 23% (2010-2014, p<.001). The use of adjunctive therapies (i.e., steroids, cyclosporine, cytoxan, abciximab and/or infliximab) were documented in 104/1133 pts (9%) and increased over time (p<.001). Conclusions: At a single center over 3 decades, treatment of incomplete KD, as well as retreatment with IVIG and use of adjunctive therapies have become increasingly common. Pts who had incomplete diagnostic criteria received IVIG later in their illness. Future studies should assess whether these secular trends have improved outcomes in pts with KD.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".