摘要
目的:探讨手足口病患者重症化的预测因素,为手足口病的诊治提供科学依据。方法:采用病例对照研究的方法,以2014-01-2015-09我院诊治的重症手足口病患儿作为病例组(n=78),以年龄、性别作为匹配因素,按1∶2的比例抽取同期在我院治疗的未发生重症化的手足口病患儿作为对照组(n=156)。收集2组患儿的社会人口学资料、临床症状和实验室检查等数据,采用多因素条件Logistic回归分析筛选手足口病重症化的危险因素。结果:所有患儿年龄8个月-9岁,平均(4.7±2.6)岁;男134例,占57.2%,女100例,占42.7%。多因素条件Logistic回归分析结果显示,抽搐(OR=4.183)、最高体温≥39℃(OR=1.158)、白细胞计数异常(OR=2.861)、乳酸脱氢酶异常(OR=6.997)、肌酸激酶同工酶异常(OR=9.164)、N-末端脑钠肽原异常(OR=4.128)是手足口病患儿进展危重症手足口病相关。结论:抽搐、最高体温、白细胞计数、乳酸脱氢酶、肌酸激酶同工酶、N-末端脑钠肽原是手足口病患儿重症化的预测因素。临床医生在手足口病诊治过程中应注意识别这些危险因素。
Objective:To identify the predictive factors of acquiring severe hand foot mouth disease(HFMD).Method:We performed a case control study using patients admitted to our hospital from January 2014 to September 2015.Cases were patients with severe HFMD disease while controls were age and sex matched patients obtained from the same year,in a 2∶1 ratio.Data comprising demographic characteristics,clinical symptoms and signs,and lab findings were collected.Conditional multivariate logistic regression was performed to determine predictive factors for severe HFMD disease.Result:A total of 78 cases of severe HFMD were identified and matched with 156 controls in study period.The average age was(4.7±2.6)years(range from 8 month to 9 years)and 57.2% were male.Multifactor conditional logistic regression analysis showed that seizure(OR=4.183),temperature ≥39℃(OR=1.158),abnormal white blood cell count(OR=2.861),abnormal lactate dehydrogenase(OR=6.997),abnormal creatine kinase isoenzyme(OR=9.164),abnormal N-terminal brain natriuretic peptide(OR=4.128)were significantly associated with severe course of HFMD.Conclusion:Seizure,temperature,white blood cell count,lactate dehydrogenase,creatine kinase isoenzyme,N-terminal brain natriuretic peptide were predictive factors severe HFMD.Physicians should consider these factors to help identify patients at risk of severe disease.
出处
《临床急诊杂志》
CAS
2016年第4期261-264,共4页
Journal of Clinical Emergency
基金
儿科应急救治相关技术的研究与推广应用(No:2012BAI04B02)
湖南省医药卫生科研计划项目(No:B2014-118)
关键词
重症手足口病
预测
危险因素
severe hand foot mouth disease
predict
risk factor