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Record W3076258403 · doi:10.1093/pch/pxaa068.110

111 Kawasaki disease in Ontario children from 1995-2017: A population-based descriptive analysis

2020· article· en· W3076258403 on OpenAlexaffabout
Megan Schlorff, Cal Robinson, Tapas Mondal, Catherine Demers, Elizabeth Darling, Sandeep Brar, Rulan S. Parekh, Hsien Seowh, Rahul Chanchlani, Michelle Batthish

Bibliographic record

VenuePaediatrics & Child Health · 2020
Typearticle
Languageen
FieldMedicine
TopicKawasaki Disease and Coronary Complications
Canadian institutionsUniversity of TorontoMcMaster University
Fundersnot available
KeywordsKawasaki diseaseMedicineIncidence (geometry)PediatricsPopulationHealth careCohortDiseaseSurgeryInternal medicineEnvironmental healthArtery

Abstract

fetched live from OpenAlex

Abstract Background Kawasaki disease (KD) is a common pediatric vasculitis with rising global incidence. Associated coronary artery aneurysms (CAA) can result in significant long-term morbidity and mortality. However, our understanding of the trends in incidence along with patient and disease characteristics for North American children over the past two decades remains limited, particularly in universal health care systems. This understanding can inform healthcare resource planning and identify knowledge gaps for educational initiatives. Objectives The objectives of this study were to: 1) compare patient, hospital and disease characteristics for children diagnosed with KD between two eras (1995-2001 and 2002-2017) and three age groups (0-4yr, 5-9yr, 10-18yr) and 2) determine trends in KD incidence across Ontario, Canada between 1995 to 2017. Design/Methods We used healthcare administrative databases housed at the Institute for Clinical Evaluative Sciences (ICES) to identify a population-based cohort of Ontario children (0-18 years) diagnosed with KD during hospital admission between April 1995 and March 2017. We excluded children with previous KD diagnosis. We compared eras and age groups by Chi-squared test. We determined the annual incidence of KD in Ontario, compared by Cochrane-Armitage test. Results We identified 4346 Ontario children diagnosed with KD between 1995-2017. The mean (SD) age at diagnosis was 3.4 years (± 2.9) and male:female ratio was 1.5:1. Median (IQR) length of hospital admission was 3 days (2-4) and 104 children (2.4%) required PICU admission. No child died within 90 days of diagnosis. Baseline CAA were observed in 106 children (2.4%). There was no difference in baseline CAA by era (2.3% [1995-2001] vs 2.5% [2002-2017], p=0.72). CAA were significantly more common in children aged 10-18 years (5.3% vs 2.4% [0-4yr] and 2.2% [5-9yr], p=0.03). Myo-/pericarditis occurred in 71 children (1.6%). Red blood cell transfusions were administered to 51 children (1.2%) and were significantly more common during 2002-2017 (≤0.5% vs 1.5%, p<0.001). The standardized incidence of KD increased significantly over the study period (p<0.0001), from 6.5 cases per 100,000 person-years (1995-2000) to 8.4 cases (2012-2017). Significant seasonal variation was observed; incidence was highest from November to March (OR 1.7 – 2.1, using August as reference month) and peaked in January (OR 2.1). Conclusion The incidence of KD has increased significantly over the past 20 years in Ontario, Canada which may reflect increased awareness and improved diagnosis. However, the frequency of baseline CAA has not changed. Baseline CAA are more common in children 10-18 years. This may suggest delayed diagnosis in this age group.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.072
Threshold uncertainty score0.144

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.005
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.026
GPT teacher head0.269
Teacher spread0.242 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations0
Published2020
Admission routes2
Has abstractyes

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