Vellere Iacopo, Lagi Filippo, Spinicci Michele, Mantella Antonia, Mantengoli Elisabetta, Corti Giampaolo, Colao Maria Grazia, Gobbi Federico, Rossolini Gian Maria, Bartoloni Alessandro, Zammarchi Lorenzo
Department of Experimental and Clinical Medicine, University of Florence, 50134 Florence, Italy.
Infectious and Tropical Diseases Unit, Careggi University Hospital, 50134 Florence, Italy.
Microorganisms. 2020 Nov 4;8(11):1731. doi: 10.3390/microorganisms8111731.
Chikungunya (CHIKV), Dengue (DENV), and Zika (ZIKV) viruses present significant clinical and epidemiological overlap, making an accurate and rapid diagnosis challenging. Timely activation of preventive vector control measures is crucial to avoid outbreaks in non-endemic settings. Diagnosis is based on combination of serological and molecular assays which could be time consuming and sometimes disappointing.
We report the results of a retrospective case-control study carried out at a tertiary teaching hospital in Italy, including all febrile subjects returning from tropical countries during the period 2014-2019. Controls were travelers with other febrile illnesses who tested negative in laboratory analysis for CHIKV, DENV, ZIKV arbovirosis. A score weighted on the regression coefficients for the independent predictors was generated.
Ninety patients were identified: 34 cases (22 DENV, 4 CHIKV, and 8 ZIKV) and 56 controls. According to our results, myalgia, cutaneous rash, absence of respiratory symptoms, leukopenia, and hypertransaminasemia showed the strongest association with arbovirosis. Combining these variables, we generated a scoring model that showed an excellent performance (AUC 0.93). The best cut-off (>=2) presented a sensitivity of 82.35% and specificity of 96.43%.
A handy and simple score, based on three clinical data (myalgia, cutaneous rash and absence of respiratory symptoms) and two laboratory results (leukopenia and hypertransaminasemia), provides a useful tool to help diagnose arboviral infections and appropriately activate vector control measures in order to avoid local transmission.
基孔肯雅病毒(CHIKV)、登革热病毒(DENV)和寨卡病毒(ZIKV)在临床和流行病学上存在显著重叠,这使得准确快速的诊断具有挑战性。及时启动预防性病媒控制措施对于避免在非流行地区爆发疫情至关重要。诊断基于血清学和分子检测的组合,这可能耗时且有时不尽人意。
我们报告了在意大利一家三级教学医院进行的一项回顾性病例对照研究的结果,研究对象包括2014年至2019年期间从热带国家返回的所有发热患者。对照组为患有其他发热疾病且在实验室分析中CHIKV、DENV、ZIKV虫媒病毒检测呈阴性的旅行者。根据独立预测因素的回归系数生成一个加权分数。
共确定了90名患者:34例(22例DENV、4例CHIKV和8例ZIKV)和56例对照。根据我们的结果,肌痛、皮疹、无呼吸道症状、白细胞减少和转氨酶升高与虫媒病毒病的关联最为密切。结合这些变量,我们生成了一个评分模型,其表现优异(曲线下面积为0.93)。最佳临界值(>=2)的敏感性为82.35%,特异性为96.43%。
基于三项临床数据(肌痛、皮疹和无呼吸道症状)和两项实验室结果(白细胞减少和转氨酶升高)的简便评分提供了一个有用的工具,有助于诊断虫媒病毒感染并适当启动病媒控制措施,以避免局部传播。