Kawasaki disease following immunization reported to the Canadian Immunization Monitoring Program ACTive (IMPACT) from 2013 to 2018
Bibliographic record
Abstract
Kawasaki disease (KD) is an acute systemic vasculitis primarily affecting children younger than 5 y of age that has been reported as an adverse event following immunization (AEFI). The Canadian Immunization Monitoring Program ACTive (IMPACT) conducts active surveillance for KD following immunization across Canada. We characterized KD cases reported to IMPACT between 2013 and 2018. Cases admitted to an IMPACT hospital with a physician diagnosis of complete or incomplete KD with onset 0-42 d following vaccination were reviewed. Cases meeting the Brighton Collaboration case definition (BCCD) levels of diagnostic certainty levels 1 a/b, 2a/b or 3a-e were defined as KD cases. Demographic and vaccination characteristics were compared between KD cases and non-cases. Of 84 cases reviewed, 58 met the BCCD: 47 (81%) cases met level 1a (Complete KD), 8 (14%) met level 1b (Incomplete KD), 2 (3%) met level 2a, and 1 (2%) met level 2c (Probable KD). Median age at admission was 13 months (interquartile range 7-26 months). A median of 9.5 cases were reported per year (range 4-14). Thirty-one (53%) KD cases were temporally associated with diphtheria-tetanus acellular pertussis containing vaccinations, followed by 21 (36%) cases with pneumococcal conjugate vaccines. Symptom onset was 0-14 d after vaccination in 32 (55%) cases. Echocardiogram results were available for 43 (74%) cases with 22 reported as abnormal. Age, sex, interval to symptom onset, and vaccines received were similar between KD cases and non-cases. No safety signals were detected in these data.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".