Srisuphanunt Mayuna, Puttaruk Palakorn, Kooltheat Nateelak, Katzenmeier Gerd, Wilairatana Polrat
Department of Medical Technology, School of Allied Health Sciences, Walailak University, Nakhon Si Thammarat 80160, Thailand.
Excellent Center for Dengue and Community Public Health, School of Public Health, Walailak University, Nakhon Si Thammarat 80160, Thailand.
Trop Med Infect Dis. 2022 Jul 31;7(8):162. doi: 10.3390/tropicalmed7080162.
This study aimed to develop simple diagnostic guidelines which would be useful for the early detection of severe dengue infections. Retrospective data of patients with dengue infection were reviewed. Patients with diagnosed dengue infection were categorized in line with the International Statistical Classification of Diseases (ICD-10): A90, dengue fever; A91, dengue hemorrhagic fever; and A910, dengue hemorrhagic fever with shock. A total of 302 dengue-infected patients were enrolled, of which 136 (45%) were male and 166 (55%) were female. Multivariate analysis was conducted to determine independent diagnostic predictors of severe dengue infection and to convert simple diagnostic guidelines into a scoring system for disease severity. Coefficients for significant predictors of disease severity generated by ordinal multivariable logistic regression analysis were transformed into item scores. The derived total scores ranged from 0 to 38.6. The cut-off score for predicting dengue severity was higher than 14, with an area under the receiver operating curve (AUROC) of 0.902. The predicted positive value (PPV) was 68.7% and the negative predictive value (NPV) was 94.1%. Our study demonstrates that several diagnostic parameters can be effectively combined into a simple score sheet with predictive value for the severity evaluation of dengue infection.
本研究旨在制定简单的诊断指南，以有助于早期发现严重登革热感染。对登革热感染患者的回顾性数据进行了审查。确诊的登革热感染患者根据《国际疾病统计分类》（ICD - 10）进行分类：A90，登革热；A91，登革出血热；以及A910，伴有休克的登革出血热。共纳入302例登革热感染患者，其中136例（45%）为男性，166例（55%）为女性。进行多变量分析以确定严重登革热感染的独立诊断预测因素，并将简单的诊断指南转换为疾病严重程度评分系统。将有序多变量逻辑回归分析得出的疾病严重程度显著预测因素的系数转换为项目得分。得出的总分范围为0至38.6。预测登革热严重程度的临界值高于14，受试者工作特征曲线下面积（AUROC）为0.902。预测阳性值（PPV）为68.7%，阴性预测值（NPV）为94.1%。我们的研究表明，几个诊断参数可以有效地组合成一个简单的评分表，对登革热感染的严重程度评估具有预测价值。
