Anhui Provincial Center for Disease Control and Prevention, Hefei, 230601, China.
Department of Infectious Diseases, The First Affiliated Hospital of Anhui Medical University, Hefei, 230032, China.
Acta Trop. 2019 Sep;197:104934. doi: 10.1016/j.actatropica.2019.02.020. Epub 2019 Feb 22.
We aimed to determine risk factors for developing severe illness in patients infected with imported Plasmodium falciparum, and identify factors that can be implemented in preventive public health actions. Data of patients in Anhui province were collected from the China Information System for Disease Control and Prevention and Information System for Parasitic Disease Control and Prevention from 2012 to 2018. Epidemiological characteristics, clinical severity, and preventive measures were analyzed using descriptive statistics. Risk factors for severe malaria were identified by logistic regression. During the study period, 8.01% (53/662) of patients infected with P. falciparum developed severe malaria; the annual severe incidence rate varied from 5.93% to 10.77% and the fatality rate was 0.6%. Two models were built to analyze the delay from symptom onset to treatment; one analyzed data by stage, whereas the other analyzed data combined from all stages. In model 1, multivariate analysis identified misdiagnosis at first medical visit and patient delay as risk factors for severe malaria (odds ratio: 3.108 and 3.385, respectively, all p < 0.01). In model 2, overall delay was a significant factor of severe malaria onset (odds ratio: 4.719, p = 0.000). In both models, patients with a history of previous infection had a significantly reduced risk of developing severe malaria; high parasitemia (≥2.5%) was associated with an increased risk of severe infection. Delay between symptom onset and treatment was an important cause for development of severe disease in Anhui province. Measures to reduce delays should be used and implemented in preventive public health actions.
我们旨在确定感染输入性恶性疟原虫的患者发生重症疾病的危险因素,并确定可用于预防公共卫生措施的因素。从 2012 年至 2018 年,我们从中国疾病预防控制信息系统和寄生虫病预防控制信息系统收集了安徽省患者的数据。采用描述性统计方法分析流行病学特征、临床严重程度和预防措施。使用逻辑回归识别重症疟疾的危险因素。在研究期间,8.01%(53/662)的恶性疟原虫感染患者发生重症疟疾;年重症发病率从 5.93%到 10.77%不等,死亡率为 0.6%。建立了两个模型来分析从症状出现到治疗的延迟;一个模型按阶段分析数据,另一个模型将所有阶段的数据合并分析。在模型 1 中,多变量分析确定初次就诊时误诊和患者延误是重症疟疾的危险因素(比值比分别为 3.108 和 3.385,均 P<0.01)。在模型 2 中,总延误是重症疟疾发病的一个显著因素(比值比:4.719,P=0.000)。在两个模型中,有既往感染史的患者发生重症疟疾的风险显著降低;高疟原虫血症(≥2.5%)与严重感染风险增加相关。症状出现与治疗之间的延迟是安徽省发生严重疾病的重要原因。应在预防公共卫生措施中使用和实施减少延误的措施。