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2017-2018年四川省克山病病例检出情况分析 被引量:2

Analysis on the Detection Rate of Keshan Diseases in Sichuan Province in 2017 to 2018
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摘要 目的了解2017-2018年四川省克山病病区的克山病病例检出情况,为达到四川省克山病消除标准提供科学依据。方法2017-04/2018-12按全国统一调查方案对四川省内28个病区县常住人口进行流行病学调查、临床内科查体、心电图检查,对其中的疑似克山病病例摄2 m后前位X线胸片及心脏超声检查。数据采用SPSS 19.0软件进行卡方检验、等级相关进行统计分析,检验水准α=0.05。结果2017-2018年四川省28县(市)从调查点共调查28469人,检出克山病共15例(检出率0.05%),其中急型克山病0例,亚急型克山病0例,慢型克山病3例(检出率0.01%),潜在型克山病12例(检出率0.04%)。结论2017-2018年四川省克山病检出率低于2014-2015年,整体病情保持平稳态势;下一步应继续加强监测,做好现症患者的治疗和管理。 Objective To understand the prevalence of Keshan diseases in Sichuan Province from 2017 to 2018 in order to provide scientific basis for the eradication of Keshan diseases in Sichuan Province.Methods From April 2017 to December 2018,an epidemiological investigation,clinical physical examination and ECG examination were conducted on the residents in 28 affected areas and counties in Sichuan Province according to the national unified investigation plan.Posterior and anterior chest X-ray and ultrasonic cardiogram examination were performed on suspected cases of Keshan diseases.Chi-square test and rank correlation were used for statitical tanalysis.The test level wasα=0.05.Results Totally,28469 people were surveyed in 28 counties.A total of 15 cases of Keshan disease were detected with the detection rate of 0.05%,including 0 cases of acute Keshan disease,0 cases of subacute Keshan disease,3 cases of chronic Keshan disease(the detection rate was 0.01%),and 12 cases of latent Keshan disease(the detection rate was 0.04%).Conclusion The detection rate of Keshan disease in Sichuan Province in 2017 to 2018 was lower than that in2014 to 2015,and the overall situation remained stable.In the next step,we should continue to strengthen the monitoring,and do a good job in the treatment and management of current patients.
作者 李锋 蔡卫 李津蜀 LI Feng;CAI Wei;LI Jinshu(Sichuan Center for Disease Control and Prevention,Chengdu 610041,Sichuan Province,China)
出处 《预防医学情报杂志》 CAS 2021年第10期1337-1339,共3页 Journal of Preventive Medicine Information
关键词 克山病 检出 分析 Keshan disease detection analysis
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