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Hosp Pediatr. 2019 Oct;9(10):749-756. doi: 10.1542/hpeds.2019-0049. Epub 2019 Sep 9.

Identifying Patients With Kawasaki Disease Safe for Early Discharge: Development of a Risk Prediction Model at a US Children's Hospital.

Author information

1
Departments of Hospital Medicine and gabrielle.hester@childrensmn.org.
2
Children's Research Institute, Children's Minnesota, Minneapolis, Minnesota.
3
Departments of Hospital Medicine and.
4
Pediatric Residency Program, University of Minnesota, Minneapolis, Minnesota; and.
5
Division of Emergency Medicine, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio.
6
Emergency Medicine and.

Abstract

OBJECTIVES:

To develop a model to predict risk of intravenous immunoglobulin (IVIg) nonresponse in patients with Kawasaki disease (KD) to assist in early discharge decision-making.

METHODS:

Retrospective cohort study of 430 patients 0 to 18 years old discharged from a US children's hospital January 1, 2010, through July 31, 2017 with a diagnosis of KD. IVIg nonresponse was defined as at least 1 of the following: temperature ≥38.0°C between 36 hours and 7 days after initial IVIg dose, receipt of a second IVIg dose after a temperature ≥38.0°C at least 20 hours after initial IVIg dose, or readmission within 7 days with administration of a second IVIg dose. Backward stepwise logistic regression was used to select a predictive model.

RESULTS:

IVIg nonresponse occurred in 19% (81 of 430) of patients. We identified a multivariate model (which included white blood cell count, hemoglobin level, platelet count, aspartate aminotransferase level, sodium level, albumin level, temperature within 6 hours of first IVIg dose, and incomplete KD) with good predictive ability (optimism-adjusted concordance index: 0.700) for IVIg nonresponse. Stratifying into 2 groups by a predictive probability cutoff of 0.10, we identified 26% of patients at low risk for IVIg nonresponse, with a sensitivity and specificity of 90% and 30%, respectively, and a negative predictive value of 93%.

CONCLUSIONS:

We developed a model with good predictive value for identifying risk of IVIg nonresponse in patients with KD at a US children's hospital. Patients at lower risk may be considered for early discharge by using shared decision-making. Our model may be used to inform implementation of electronic health record tools and future risk prediction research.

PMID:
31501220
DOI:
10.1542/hpeds.2019-0049

Conflict of interest statement

POTENTIAL CONFLICT OF INTEREST: The authors have indicated they have no potential conflicts of interest to disclose.

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