青海省2016—2019年结核分枝杆菌耐药特征及空间聚集性  

Drug resistance characteristics and spatial clustering of Mycobacterium tuberculosis in Qinghai Province from 2016 to 2019

作　　者：王兴斌 蒋明霞[3] 赵昌明 马永成[3] 张祖豪 黄秋丽 王玲 刘旷怡 张亚欣 王兆芬[1] WANG Xingbin;JIANG Mingxia;ZHAO Changming;MA Yongcheng;ZHANG Zuhao;HUANG Qiuli;WANG Ling;LIU Kuangyi;ZHANG Yaxin;WANG Zhaofen(Department of Public Health,College of Medicine,Qinghai University,Xi'ning,Qinghai 810001,China;Xiguan Community Health Service Center,Chengxi District,Xining City,Xi'ning,Qinghai 810001,China;Qinghai Provincial Center for Disease Control and Prevention,Xi'ning,Qinghai 810007,China)

机构地区：[1]青海大学医学院公共卫生系,青海西宁810001 [2]西宁市城西区西关社区卫生服务中心,青海西宁810001 [3]青海省疾病预防控制中心,青海西宁810007

出　　处：《中国热带医学》2023年第8期815-821,共7页China Tropical Medicine

基　　金：国家自然科学基金项目(No.81860593)。

摘　　要：目的分析青海省2016—2019年结核分枝杆菌(Mycobacterium tuberculosis,MTB)对6种常用抗结核药物的耐药情况及其空间分布规律,为结核病治疗和耐药结核病防控提供参考依据。方法收集青海省2016—2019年1182株经过鉴定的结核分枝杆菌菌株,采用比例法对6种抗结核药物进行药敏试验及菌种鉴定。运用ArcMap10.7和SaTScan10.1软件对MTB耐药情况进行地图可视化展示和空间自相关分析以及空间扫描,确定青海省MTB耐药聚集区域。结果2016—2019年青海省结核分枝杆菌总耐药率为23.77%(281/1182),单耐药率为11.08%(131/1182),多耐药率为3.89%(46/1182),耐多药率为8.80%(104/1182),广泛耐药率为0.85%(10/1182),其中耐多药率、广泛耐药率、总耐药率呈逐年下降趋势(P<0.01)。耐药谱共有21种组合。复治患者总耐药率、耐多药率高于初治患者,差异有统计学意义(χ^(2)_(总耐药率)=22.784,χ^(2)_(耐多药率)=45.082,P<0.01)。人群特征来看,总耐药率男性高于女性,中年人群高于其他年龄组人群,差异均有统计学意义(χ^(2)=7.541,10.825,P<0.05)。全局自相关分析结果显示,2016—2019青海省MTB耐药在区域范围内自相关关系无统计学意义(P>0.05),无明显空间聚集性,属于随机分布;时空扫描结果显示,发现各存在1个一类聚集区,但聚集效应无统计学意义(P>0.05),呈随机分布。结论2016—2019年青海MTB总体耐药情况呈现逐年下降趋势;与全国平均水平相比,耐多药率、广泛耐药率仍较高,且由利福平、异烟肼耐药所导致的耐多药占比较大,耐药人群以复治、男性、中青年群体为主。耐药菌株在空间中,无明显聚集性,呈随机分布。Objective To analyze the resistance and spatial distribution of Mycobacterium tuberculosis(MTB)to six commonly used anti-tuberculosis drugs in Qinghai Province from 2016 to 2019,so as to provide a reference for tuberculosis treatment and drug-resistant tuberculosis control.Methods A total of 1182 identified strains of Mycobacterium tuberculosis in Qinghai Province from 2016 to 2019 were collected,and 6 anti-tuberculosis drugs were subjected to drug susceptibility tests and strain confirmed by the proportional method.By means of ArcMap10.7 and SaTScan10.1 software,map visualization,spatial autocorrelation analysis and spatial scanning of MTB drug resistance were performed to identify MTB drug resistance clusters in Qinghai Province.Results From 2016 to 2019,the total drug resistance(TDR)rate of 1182 Mycobacterium tuberculosis strains in Qinghai Province was 23.77%(281/1182),with a mono-resistance(MR)rate of 11.08%(131/1182),a poly-resistance(PDR)rate of 3.89%(46/1182),a multi-drug resistance(MDR)rate of 8.80%(104/1182),and an extensive drug resistance(XDR)rate of 0.85%(10/1182).The rates of MDR,XDR and TDR all showed a decreasing trend year by year(P<0.01).The drug resistance spectrum displayed 21 combinations.The TDR rate and MDR rate in the retreatment patients were higher than those of the initial treated patients,and the difference was statistically significant(χ^(2)_(TDR)=22.784,χ^(2)_(MDR)=45.082,P<0.01).In terms of demographic characteristics,the TDR rate in males was higher than that in females,and the middle-aged group was higher than other age groups,and the differences were statistically significant(χ^(2)=7.541,10.825,P<0.05).The results of global spatial autocorrelation analysis showed that there was no statistical significance in the autocorrelation and obvious spatial clustering of MTB drug resistance in Qinghai Province from 2016 to 2019(P>0.05),which indicated a random distribution.The results of spatiotemporal scanning showed that there was a kind of clustering area,but the clustering effect wa

关 键 词：结核分枝杆菌 耐药特征 空间聚集性 空间自相关分析 空间扫描 

分 类 号：R52[医药卫生—内科学]