Harvey Cohen

Publication Details

  • Point-of-Care Differentiation of Kawasaki Disease from Other Febrile Illnesses JOURNAL OF PEDIATRICS Ling, X. B., Kanegaye, J. T., Ji, J., Peng, S., Sato, Y., Tremoulet, A., Burns, J. C., Cohen, H. J. 2013; 162 (1): 183-U219


    To test whether statistical learning on clinical and laboratory test patterns would lead to an algorithm for Kawasaki disease (KD) diagnosis that could aid clinicians.Demographic, clinical, and laboratory data were prospectively collected for subjects with KD and febrile controls (FCs) using a standardized data collection form.Our multivariate models were trained with a cohort of 276 patients with KD and 243 FCs (who shared some features of KD) and validated with a cohort of 136 patients with KD and 121 FCs using either clinical data, laboratory test results, or their combination. Our KD scoring method stratified the subjects into subgroups with low (FC diagnosis, negative predictive value >95%), intermediate, and high (KD diagnosis, positive predictive value >95%) scores. Combining both clinical and laboratory test results, the algorithm diagnosed 81.2% of all training and 74.3% of all testing of patients with KD in the high score group and 67.5% of all training and 62.8% of all testing FCs in the low score group.Our KD scoring metric and the associated data system with online (http://translationalmedicine.stanford.edu/cgi-bin/KD/kd.pl) and smartphone applications are easily accessible, inexpensive tools to improve the differentiation of most children with KD from FCs with other pediatric illnesses.

    View details for DOI 10.1016/j.jpeds.2012.06.012

    View details for Web of Science ID 000312915900040

    View details for PubMedID 22819274

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