Kawasaki MATCH Trial (MATCH)

Kawasaki MATCH: A Clinical Decision Support Tool to Detect KD

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.

Study Overview

• Status: Recruiting
• Conditions: Kawasaki Disease
• Intervention / Treatment: Other: Kawasaki MATCH

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.

• Study Type: Interventional
• Enrollment (Estimated): 200
• Phase: Not Applicable

Contacts and Locations

• Study Contact: Name: Michael A Gardiner, MD; Phone Number: 949-310-4808; Email: magardiner@health.ucsd.edu

Study Locations

• United States
  • California
    • San Diego, California, United States, 92071
      • Recruiting
      • Rady Children's Hospital, San Diego
      • Contact: Michael A Gardiner, MD; Phone Number: 949-310-4808; Email: magardiner@health.ucsd.edu

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Child
• Accepts Healthy Volunteers: No

Description

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)

Study Plan

How is the study designed?

Design Details

• Primary Purpose: Diagnostic
• Allocation: Randomized
• Interventional Model: Parallel Assignment
• Masking: None (Open Label)

Number of Arms

2

Arms and Interventions

Participant Group / Arm	Intervention / Treatment
Experimental: Kawasaki MATCH; Providers encouraged to access and utilize the Kawasaki MATCH decision support tool when evaluating and managing patients in the Emergency Department	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.
No Intervention: Routine Care; Providers prompted to manage patients as per usual/routine care without additional decision support.

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Time to Kawasaki Disease treatment (KD patients only)	Time in days from initial ED evaluation to initial IVIG treatment in patients ultimately diagnosed with Kawasaki Disease	90 days

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Kawasaki MATCH score	MATCH score determined by entering patient clinical and laboratory information into the Kawasaki MATCH algorithm. Algorithm output is a decimal between 0 and 1. Scores less than 0.4 will be deemed a prediction of "not Kawasaki Disease" while scores of 0.4 or higher will be deemed "Kawasaki Disease"	Day 1 (day of enrollment)
Hospital Admission Rate	Proportion of patients admitted to the hospital from the Emergency Department (ED). Admitted patients = 1 Discharged patients = 0	Day 1 (day of enrollment)
Kawasaki Disease consultation rate	Proportion of patients receiving Kawasaki service consultation	Day 1 (day of enrollment)
ED return visit	Return to Emergency Department	7 days
Additional interventions	Additional ED orders for laboratory/imaging studies or additional procedures after the time of randomization	Day 1 (day of enrollment)
Provider assessment of KD likelihood - baseline	Visual analog scale of suspected likelihood of Kawasaki Disease. Scale between 0 (Definitely not Kawasaki Disease) and 100 (Definitely Kawasaki Disease) with higher values indicating higher provider suspicion for Kawasaki Disease. This outcome will be assessed on providers randomized to both study arms	Day 1 (day of enrollment)
Provider assessment of KD likelihood - after algorithm	Visual analog scale of suspected likelihood of Kawasaki Disease. Scale between 0 (Definitely not Kawasaki Disease) and 100 (Definitely Kawasaki Disease) with higher values indicating higher provider suspicion for Kawasaki Disease. This outcome only assessed for providers in the experimental arm.	Day 1 (day of enrollment)
Algorithm helpfulness	Visual analog scale of the perceived helpfulness of the Kawasaki MATCH algorithm. Scale between 0 (Not helpful) and 100 (Extremely helpful) with higher values indicating increased helpfulness. This outcome only assessed for providers in the experimental arm.	Day 1 (day of enrollment)

Collaborators and Investigators

• Sponsor: University of California, San Diego
• Collaborators: Rady Children's Hospital, San Diego; Gordon and Marilyn Macklin Foundation

Publications and helpful links

General 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.
• 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 inflammatory syndrome in children and Kawasaki disease in the USA: a retrospective model development and validation study. Lancet Digit Health. 2022 Oct;4(10):e717-e726. doi: 10.1016/S2589-7500(22)00149-2.

Study record dates

Study Major Dates

• Study Start (Actual): March 1, 2025
• Primary Completion (Estimated): October 31, 2026
• Study Completion (Estimated): October 31, 2026

Study Registration Dates

• First Submitted: November 24, 2025
• First Submitted That Met QC Criteria: December 4, 2025
• First Posted (Actual): December 18, 2025

Study Record Updates

• Last Update Posted (Actual): December 18, 2025
• Last Update Submitted That Met QC Criteria: December 4, 2025
• Last Verified: December 1, 2025

More Information

Terms related to this study

• Keywords: Point-of-care; Machine-learning; Artificial Intelligence (AI); Decision support; Kawasaki Disease
• Additional Relevant MeSH Terms: Vascular Diseases; Cardiovascular Diseases; Skin Diseases; Lymphatic Diseases; Skin Diseases, Vascular; Vasculitis; Skin and Connective Tissue Diseases; Hemic and Lymphatic Diseases; Mucocutaneous Lymph Node Syndrome
• Other Study ID Numbers: 140220; 68060 (Other Grant/Funding Number: Gordon and Marilyn Macklin Foundation)

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: NO
• IPD Plan Description: Not included in consent documents

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No