Medical Research Department, Chi-Mei Medical Center, Tainan, Taiwan
Julie Chi Chow
Department of Paediatrics, Chi Mei medical center, Tainan, Taiwan
National Taiwan University School of Medicine, Taiwan
Department of Sports Management, College of Leisure and Recreation Management, Chia Nan University of Pharmacy and Science, Tainan, Taiwan ; NcphrologyDepartment, Chi-Mei Medical Center, Tainan, Taiwan
Background: Dengue fever (DF) is an important health problem in Asia. We examined it using its clinical symptoms to predict DF. Methods: We extracted statistically significant features from 17 DF-related clinical symptoms in 177 pediatric patients (69 diagnosed with DF) using (1) the unweighted summation score and (2) the non-parametric HT person fit statistic, which jointly combine (3) the weighted score (yielded by logistic regression) to predict DF risk. Results: Six symptoms (Family History, Fever ≥ 39°C, Skin Rash, Petechiae, Abdominal Pain, and Weakness) significantly predicted DF. When a cutoff point of −1.03 (p = 0.26) suggested combining the weighted score and the HT coefficient, the sensitivity was 0.91 and the specificity was 0.76. The area under the ROC curve was 0.88, which was a better predictor: specificity was 5.56% higher than for the traditional logistic regression. Conclusions: Six simple symptoms analyzed using logistic regression were useful and valid for early detection of DF risk in children. A better predictive specificity increased after combining the non-parametric HT coefficient to the weighted regression score. A self-assessment using patient smartphones is available to discriminate DF and may eliminate the need for a costly and time-consuming dengue laboratory test.
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