Kawasaki MATCH Trial
For patients and families
In plain language
An automatic summary of structured registry data. It is an orientation aid, not a substitute for the official protocol or a physician assessment.
- What is being studied
- The protocol lists: Kawasaki MATCH.
- Who it may be relevant to
- Registry conditions: Kawasaki Disease. Basic parameters: 30 Days — 17 years · All.
- What needs checking
- Age, condition and sex are only basic indicators. Prior treatment, laboratory values and other mandatory requirements appear in the eligibility criteria below.
- Where it takes place
- United States
- Next step
- Save the trial, show it to the treating physician, and confirm current recruitment with the study center. Costs, documents and travel →
Unsure about the terms? Read our patient guide →
Official title
Kawasaki MATCH: A Clinical Decision Support Tool to Detect KD
Overview
Evaluating the impact of a machine-learning clinical decision support tool on provider practice when evaluating febrile patients with Kawasaki Disease (KD) and non-KD illnesses.
Detailed description
Following laboratory evaluation, providers will be randomized to treat patients according to usual practice/standard of care vs. receiving clinical decision support from the Kawasaki MATCH tool - a previously validated machine-learning clinical decision support tool to identify Kawasaki Disease. The study aim is to evaluate the accuracy of Kawasaki MATCH prospectively when used at the point of care, as well as how this tool impacts clinical decisions including additional evaluation and hospital admission.
Interventions
- Other Kawasaki MATCH
Providers access the Kawasaki MATCH decision support tool. Patient information is entered into the tool and a risk score is indicated to the provider. Kawasaki MATCH is a previously validated machine-learning decision support tool for the diagnosis of Kawasaki Disease. This tool utilizes patient age, 18 laboratory features, and 5 clinical features to formulate a risk score.
Primary outcome measures
- Time to Kawasaki Disease treatment (KD patients only) [Time frame: 90 days]
Secondary outcome measures (8)
- Kawasaki MATCH score [Time frame: Day 1 (day of enrollment)]
- Hospital Admission Rate [Time frame: Day 1 (day of enrollment)]
- Kawasaki Disease consultation rate [Time frame: Day 1 (day of enrollment)]
- ED return visit [Time frame: 7 days]
- Additional interventions [Time frame: Day 1 (day of enrollment)]
- Provider assessment of KD likelihood - baseline [Time frame: Day 1 (day of enrollment)]
- Provider assessment of KD likelihood - after algorithm [Time frame: Day 1 (day of enrollment)]
- Algorithm helpfulness [Time frame: Day 1 (day of enrollment)]
Eligibility criteria
Inclusion criteria
- Measured or subjective fever for >= 3 calendar days
- One measured fever >= 38.0 C (home or in ED)
- One or more clinical feature of Kawasaki Disease including:
- Rash
- Conjunctival injection
- Oropharyngeal changes
- Extremity changes (erythema, edema, desquamation)
- Cervical adenopathy (>=1.5cm)
- Infants < 6 months of age with >= 7 days of fever eligible even if none of the above clinical features
- Requires IV/phlebotomy for clinical evaluation
Exclusion criteria
- Congenital or Acquired Immune function
- Genetic disorders
- Current systemic steroid, immunosuppression, or chemotherapy treatment (not including inhaled steroids)
Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.
Healthy volunteers: No
Study design
- Allocation
- Randomized
- Model
- Parallel assignment
- Masking
- Open label
- Primary purpose
- Diagnostic
Study locations
United States · 1 center
- Rady Children's Hospital, San Diego — San Diego
Publications
- Lam JY, Shimizu C, Gardiner MA, Giorgio T, Wright V, Baker A, Anderson MS, Heizer H, Mohandas S, Kazarians A, Kaneta K, Jone PN, Dominguez SR, Szmuszkovicz JR, Newburger JW, Tremoulet AH, Burns JC. External Validation of a Machine Learning Model to Diagnose Kawasaki Disease. J Pediatr. 2025 Jul;282:114543. doi: 10.1016/j.jpeds.2025.114543. Epub 2025 Mar 21. PMID 40122277
- Lam JY, Shimizu C, Tremoulet AH, Bainto E, Roberts SC, Sivilay N, Gardiner MA, Kanegaye JT, Hogan AH, Salazar JC, Mohandas S, Szmuszkovicz JR, Mahanta S, Dionne A, Newburger JW, Ansusinha E, DeBiasi RL, Hao S, Ling XB, Cohen HJ, Nemati S, Burns JC; Pediatric Emergency Medicine Kawasaki Disease Research Group; CHARMS Study Group. A machine-learning algorithm for diagnosis of multisystem inflammator PMID 36150781
Identifiers
NCT: NCT07291245 · 140220 · 68060