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Article(id=1240738482633634710, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1240738480549065614, articleNumber=null, orderNo=null, doi=10.20043/j.cnki.MPM.202412527, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1735142400000, receivedDateStr=2024-12-26, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1773744706066, onlineDateStr=2026-03-17, pubDate=1746806400000, pubDateStr=2025-05-10, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1773744706066, onlineIssueDateStr=2026-03-17, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1773744706066, creator=13701087609, updateTime=1773744706066, updator=13701087609, issue=Issue{id=1240738480549065614, tenantId=1146029695717560320, journalId=1227665162245664772, year='2025', volume='52', issue='9', pageStart='1537', pageEnd='1728', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1773744705569, creator=13701087609, updateTime=1773744787657, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1240738824918192654, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1240738480549065614, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1240738824922386959, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1240738480549065614, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=1556, endPage=1561, ext={EN=ArticleExt(id=1240738483048870814, articleId=1240738482633634710, tenantId=1146029695717560320, journalId=1227665162245664772, language=EN, title=Analysis of the epidemiological characteristics and trends of drug-resistant tuberculosis in Guizhou province from 2016 to 2023, columnId=1240413921954295836, journalTitle=Modern Preventive Medicine, columnName=Epidemiology and Statistical Methods, runingTitle=null, highlight=null, articleAbstract=
Objective

To analyze the epidemiological characteristics and trends of drug-resistant tuberculosis (DR-TB) patients in Guizhou Province from 2016 to 2023, providing scientific evidence and support for DR-TB prevention and control strategies.

Methods

Using the “Tuberculosis Management Information System”, a subsystem of the “Chinese Disease Prevention and Control Information System”, descriptive epidemiological methods were employed to analyze the epidemiological characteristics and trends of DR-TB patients in Guizhou Province.

Results

A total of 3 580 DR-TB patients were reported in Guizhou Province from 2016 to 2023; the male-to-female ratio was 2.15:1, with 2 976 cases (77.12%) among the Han ethnic group. The age group of 40-60 years accounted for the highest proportion, with 1 507 cases (42.09%). Compared to 2016, the proportion of patients aged 60 and above increased in 2023 (24.23% vs. 10.56%). Farmers represented the majority of the patients, totaling 1 844 cases (51.51%). The top three regions were Bijie city (676 cases, 18.88%), Guiyang city (571 cases, 15.95%), and Tongren city (531 cases, 14.83%). Compared to 2016, the proportions in Bijie and Tongren cities increased in 2023 (20.52% vs. 9.94%and 11.34% vs. 3.72%, respectively). The predominant drug resistance type was rifampicin resistance (98.41%), while the proportion of multidrug-resistant cases decreased in 2023 compared to 2016 (45.88% vs. 98.14%), and the proportion of pre-extensively drug-resistant cases increased (7.32% vs. 0%). The top three categories of registration were new patients, treatment failures, and relapses, with 1 317 cases (26.79%), 893 cases (24.94%), and 874 cases (24.41%), respectively. Compared to 2016, the proportions of new patients and relapses increased in 2023 (44.85% vs. 6.83% and 30.10% vs. 18.63%).

Conclusion

The prevention and control efforts for DR-TB in Guizhou Province from 2016 to 2023 have achieved certain results, but the situation remains severe. Future work should focus on continuously improving the application of molecular biological testing technologies, reducing relapses, optimizing resource allocation, and strengthening prevention and control measures for key populations and regions, ensuring timely and effective diagnosis and treatment services across all areas.

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目的

本研究通过分析贵州省2016—2023年耐药结核病(drugresistant tuberculosis，DR-TB)患者的流行特征和变化趋势，为耐药结核病防控策略提供科学依据和支持。

方法

基于“中国疾病预防控制信息系统”的子系统“结核病管理信息系统”，采用描述性流行病学方法，对贵州省DR-TB患者的流行特征及变化趋势进行分析。

结果

2016—2023年贵州省DR-TB患者共3 580例，男女比例2.15∶1，汉族2 976例(77.12%)，40～60岁组占比最高，为1 507例(42.09%)；与2016年相比，2023年≥60岁组占比有所增加(24.23% vs. 10.56%)；职业以农民为主1 844例(51.51%)。占比前三位的地区分别为：毕节市676例(18.88%)、贵阳市571例(15.95%)、铜仁市531例(14.83%)，与2016年相比，2023年毕节市、铜仁市占比增加(20.52% vs. 9.94%，11.34% vs. 3.72%)。耐药类型以利福平耐药为主，占98.41%，与2016年相比，2023年耐多药占比有所降低(45.88% vs. 98.14%)，而准广泛耐药有所增加(7.32% vs. 0)。登记分类占比前三位是新患者、初治失败和复发患者，分别为1 317例(26.79%)、893例(24.94%)、874例(24.41%)，与2016年相比，2023年新患者、复发患者占比增加(44.85% vs. 6.83%，30.10% vs. 18.63%)。

结论

2016—2023年贵州省DR-TB防控工作取得了一定成效，但其防控形势依然严峻。未来的工作应着重于持续提升分子生物学检测技术的应用，减少复发，优化资源配置，强化重点人群、重点地区的耐药防控措施，确保各地都能得到及时有效的诊疗服务。

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李进岚，E-mail:
, copyrightStatement=本刊刊出的所有文章不代表中华预防医学会和本刊编委会的观点，除非特别声明。, copyrightOwner=中华预防医学会和四川大学华西公共卫生学院, extLink=null, articleAbsUrl=null, sourceXml=xHIGer3Mlstudsk4/YAwEg==, magXml=7FHZ0M6nx+qMOy1/wMiRcA==, pdfUrl=null, pdf=56QWpXLjaoc6yswh4+k3sQ==, pdfFileSize=655361, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=wHwKs/9avvtxhp0+ji0ezg==, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=5iPT+7cyo4boeycvJf9hfw==, mapNumber=null, authorCompany=null, fund=null, authors=

饶文（1999—），女，硕士在读，研究方向：疾病预防与控制

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饶文（1999—），女，硕士在读，研究方向：疾病预防与控制

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饶文（1999—），女，硕士在读，研究方向：疾病预防与控制

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Chinese Journal of Antituberculosis, 2022, 44(10): 1028-1036.(In Chinese), articleTitle=Analysis of influencing factors of recurrence in cured patients with multidrug-resistant pulmonary tuberculosis, refAbstract=null)], funds=[Fund(id=1241081872944525371, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240738482633634710, awardId=2020-181-131, language=CN, fundingSource=贵州省发改委省级基本建设前期工作项目(2020-181-131), fundOrder=null, country=null), Fund(id=1241081873074548805, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240738482633634710, awardId=2024-E-7, language=CN, fundingSource=贵州省疾病预防控制中心2024年青年科学基金项目(2024-E-7), fundOrder=null, country=null)], companyList=[AuthorCompany(id=1241081864077767264, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240738482633634710, xref=1., ext=[AuthorCompanyExt(id=1241081864081961569, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240738482633634710, companyId=1241081864077767264, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=School of Public Health and Health, Guizhou Medical University, Guiyang, Guizhou 561113, China), AuthorCompanyExt(id=1241081864090350179, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240738482633634710, companyId=1241081864077767264, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1.贵州医科大学公共卫生与健康学院，贵州 贵阳 561113)]), AuthorCompany(id=1241081864195207788, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240738482633634710, xref=2., ext=[AuthorCompanyExt(id=1241081864203596397, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240738482633634710, companyId=1241081864195207788, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2.贵州省疾病预防控制中心结防所，贵州 贵阳 550004)])], figs=[ArticleFig(id=1241081871480714170, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240738482633634710, language=EN, label=Figure 1, caption=Trends of six types of DR-TB in Guizhou Province, 2016—2023, figureFileSmall=iZO9PGTSxNcUl1PHWr6WPw==, figureFileBig=J+LbZpKJ26rZ4ZVyDdpvFg==, tableContent=null), ArticleFig(id=1241081871631709121, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240738482633634710, language=CN, label=图1, caption=2016—2023年贵州省六种DR-TB变化趋势, figureFileSmall=iZO9PGTSxNcUl1PHWr6WPw==, figureFileBig=J+LbZpKJ26rZ4ZVyDdpvFg==, tableContent=null), ArticleFig(id=1241081871782704081, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240738482633634710, language=EN, label=Table 1, caption=

Basic characteristics of DR-TB patients in Guizhou Province, 2016—2023

, figureFileSmall=null, figureFileBig=null, tableContent=
变量例数构成比（%）变量例数构成比（%）
性别复治2 26363.21
男2 44268.21登记分类
女1 13831.79新患者1 31736.79
民族初治失败89324.94
汉族2 74376.62复发87424.41
少数民族83723.38复治失败1574.39
年龄(岁)返回1544.30
<201865.20初治2、3月末阳性832.32
20～391 18233.02其他1022.85
40～591 50742.09检测方法
≥6070519.69分子生物学2 99983.77
职业传统药敏58116.23
农民1 84451.51治疗模式
家务及待业1 04729.25门诊治疗2 37766.40
学生1484.13住院治疗1193.32
离退人员862.41其他1 08430.28
固定职业人员752.09治疗转归
工人381.06成功治疗1 51642.34
其他3429.55治愈1 02428.60
患者来源失访63917.85
转诊1 33437.26完成疗程49213.74
因症就诊61717.24死亡2045.70
追踪59516.62失败1945.42
其他1 03428.88其他3549.89
治疗分类不详67318.80
初治1 31736.79
), ArticleFig(id=1241081871891755995, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240738482633634710, language=CN, label=表1, caption=

2016—2023年贵州省DR-TB患者基本情况

, figureFileSmall=null, figureFileBig=null, tableContent=
变量例数构成比（%）变量例数构成比（%）
性别复治2 26363.21
男2 44268.21登记分类
女1 13831.79新患者1 31736.79
民族初治失败89324.94
汉族2 74376.62复发87424.41
少数民族83723.38复治失败1574.39
年龄(岁)返回1544.30
<201865.20初治2、3月末阳性832.32
20～391 18233.02其他1022.85
40～591 50742.09检测方法
≥6070519.69分子生物学2 99983.77
职业传统药敏58116.23
农民1 84451.51治疗模式
家务及待业1 04729.25门诊治疗2 37766.40
学生1484.13住院治疗1193.32
离退人员862.41其他1 08430.28
固定职业人员752.09治疗转归
工人381.06成功治疗1 51642.34
其他3429.55治愈1 02428.60
患者来源失访63917.85
转诊1 33437.26完成疗程49213.74
因症就诊61717.24死亡2045.70
追踪59516.62失败1945.42
其他1 03428.88其他3549.89
治疗分类不详67318.80
初治1 31736.79
), ArticleFig(id=1241081872038556650, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240738482633634710, language=EN, label=Table 2, caption=

Age distribution and trends of DR-TB in Guizhou Province, 2016—2023 ［n（%）］

, figureFileSmall=null, figureFileBig=null, tableContent=
年份（年）<20岁20～39岁40～59岁≥60岁
20165(3.11)81(50.31)58(36.02)17(10.56)
201717(9.71)70(40.00)69(39.43)19(10.86)
201823(6.65)132(38.15)133(38.44)58(16.76)
201913(5.22)85(34.14)121(48.59)30(12.05)
202027(5.78)168(35.97)189(40.47)83(17.78)
202136(5.39)208(31.14)281(42.06)143(21.41)
202232(5.88)164(30.15)228(41.91)120(22.06)
202333(3.40)274(28.25)428(44.12)235(24.23)
合计186(5.20)1 182(33.02)1 507(42.09)705(19.69)
χ2值0.03731.2113.69614.896
P值0.847<0.0010.055<0.001
), ArticleFig(id=1241081872147608564, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240738482633634710, language=CN, label=表2, caption=

2016—2023年贵州省DR-TB的年龄分布及变化趋势［n（%）］

, figureFileSmall=null, figureFileBig=null, tableContent=
年份（年）<20岁20～39岁40～59岁≥60岁
20165(3.11)81(50.31)58(36.02)17(10.56)
201717(9.71)70(40.00)69(39.43)19(10.86)
201823(6.65)132(38.15)133(38.44)58(16.76)
201913(5.22)85(34.14)121(48.59)30(12.05)
202027(5.78)168(35.97)189(40.47)83(17.78)
202136(5.39)208(31.14)281(42.06)143(21.41)
202232(5.88)164(30.15)228(41.91)120(22.06)
202333(3.40)274(28.25)428(44.12)235(24.23)
合计186(5.20)1 182(33.02)1 507(42.09)705(19.69)
χ2值0.03731.2113.69614.896
P值0.847<0.0010.055<0.001
), ArticleFig(id=1241081872231493633, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240738482633634710, language=EN, label=Table 3, caption=

Regional distribution and trends of DR-TB in Guizhou Province, 2016—2023 ［n（%）］

, figureFileSmall=null, figureFileBig=null, tableContent=
年份（年）毕节市贵阳市铜仁市遵义市黔东南州六盘水市黔南州安顺市黔西南州
201616(9.94)111(68.94)6(3.72)15(9.32)5(3.11)2(1.24)5(3.11)0(0.00)1(0.62)
201727(15.43)62(35.43)12(6.86)50(28.56)7(4.00)3(1.71)4(2.29)5(2.86)5(2.86)
201873(21.10)61(17.63)40(11.56)52(15.03)41(11.85)26(7.52)27(7.80)16(4.62)10(2.89)
201948(19.28)30(12.05)24(9.64)47(18.86)35(14.06)18(7.23)30(12.05)11(4.42)6(2.41)
2020115(24.63)49(10.49)51(10.92)36(7.71)74(15.85)46(9.85)29(6.21)37(7.92)30(6.42)
2021117(17.51)69(10.33)191(28.59)70(10.48)40(5.99)60(8.98)35(5.24)38(5.69)48(7.19)
202281(14.89)52(9.56)97(17.83)76(13.97)52(9.56)55(10.11)39(7.17)55(10.11)37(6.80)
2023199(20.52)137(14.12)110(11.34)147(15.15)97(10.00)81(8.35)82(8.46)72(7.42)45(4.64)
合计676(18.88)571(15.95)531(14.83)493(13.77)351(9.80)291(8.13)251(7.02)234(6.54)182(5.08)
χ2值10.035242.4008.6963.8357.99910.2605.56212.7635.714
P值0.002<0.0010.0030.0500.0050.0010.018<0.0010.017
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2016—2023年贵州省DR-TB的地区分布及变化趋势［n（%）］

, figureFileSmall=null, figureFileBig=null, tableContent=
年份（年）毕节市贵阳市铜仁市遵义市黔东南州六盘水市黔南州安顺市黔西南州
201616(9.94)111(68.94)6(3.72)15(9.32)5(3.11)2(1.24)5(3.11)0(0.00)1(0.62)
201727(15.43)62(35.43)12(6.86)50(28.56)7(4.00)3(1.71)4(2.29)5(2.86)5(2.86)
201873(21.10)61(17.63)40(11.56)52(15.03)41(11.85)26(7.52)27(7.80)16(4.62)10(2.89)
201948(19.28)30(12.05)24(9.64)47(18.86)35(14.06)18(7.23)30(12.05)11(4.42)6(2.41)
2020115(24.63)49(10.49)51(10.92)36(7.71)74(15.85)46(9.85)29(6.21)37(7.92)30(6.42)
2021117(17.51)69(10.33)191(28.59)70(10.48)40(5.99)60(8.98)35(5.24)38(5.69)48(7.19)
202281(14.89)52(9.56)97(17.83)76(13.97)52(9.56)55(10.11)39(7.17)55(10.11)37(6.80)
2023199(20.52)137(14.12)110(11.34)147(15.15)97(10.00)81(8.35)82(8.46)72(7.42)45(4.64)
合计676(18.88)571(15.95)531(14.83)493(13.77)351(9.80)291(8.13)251(7.02)234(6.54)182(5.08)
χ2值10.035242.4008.6963.8357.99910.2605.56212.7635.714
P值0.002<0.0010.0030.0500.0050.0010.018<0.0010.017
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Registration classification and detection methods of DR-TB in Guizhou Province, 2016—2023 ［n（%）］

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年份（年）登记分类检测方法
新患者初治失败复发复治失败返回初治2和
3月末阳性		其他传统药敏分子生物学
201611(6.83)84(52.17)30(18.63)29(18.01)1(0.62)3(1.87)3(1.87)59(36.65)102(63.35)
201724(13.72)100(57.14)12(6.86)34(19.43)1(0.57)2(1.14)2(1.14)64(36.58)111(63.42)
201866(19.08)179(51.73)72(20.80)20(5.78)5(1.45)2(0.58)2(0.58)59(17.05)287(82.95)
201954(21.69)70(28.11)72(28.92)29(11.65)10(4.02)12(4.81)2(0.80)39(15.66)210(84.34)
2020190(40.68)132(28.26)99(21.20)21(4.50)14(3.00)11(2.36)0(0.00)78(16.71)389(83.29)
2021311(46.56)120(17.96)137(20.51)19(2.85)51(7.63)25(3.74)5(0.75)164(24.55)504(75.45)
2022226(41.54)91(16.73)160(29.41)2(0.37)31(5.70)11(2.02)23(4.23)50(9.19)494(90.81)
2023435(44.85)117(12.06)292(30.10)3(0.31)41(4.23)17(1.75)65(6.70)68(7.01)902(92.99)
合计1 317(36.79)893(24.94)874(24.41)157(4.39)154(4.30)83(2.32)102(2.85)2 999(83.77)581(16.23)
χ2值83.541152.0318.920151.0305.021—5.719121.661
P值<0.001<0.0010.003<0.0010.0250.559a0.017<0.001
), ArticleFig(id=1241081872676089893, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240738482633634710, language=CN, label=表4, caption=

2016—2023年贵州省DR-TB的登记分类与检测方法及其变化趋势［n（%）］

, figureFileSmall=null, figureFileBig=null, tableContent=
年份（年）登记分类检测方法
新患者初治失败复发复治失败返回初治2和
3月末阳性		其他传统药敏分子生物学
201611(6.83)84(52.17)30(18.63)29(18.01)1(0.62)3(1.87)3(1.87)59(36.65)102(63.35)
201724(13.72)100(57.14)12(6.86)34(19.43)1(0.57)2(1.14)2(1.14)64(36.58)111(63.42)
201866(19.08)179(51.73)72(20.80)20(5.78)5(1.45)2(0.58)2(0.58)59(17.05)287(82.95)
201954(21.69)70(28.11)72(28.92)29(11.65)10(4.02)12(4.81)2(0.80)39(15.66)210(84.34)
2020190(40.68)132(28.26)99(21.20)21(4.50)14(3.00)11(2.36)0(0.00)78(16.71)389(83.29)
2021311(46.56)120(17.96)137(20.51)19(2.85)51(7.63)25(3.74)5(0.75)164(24.55)504(75.45)
2022226(41.54)91(16.73)160(29.41)2(0.37)31(5.70)11(2.02)23(4.23)50(9.19)494(90.81)
2023435(44.85)117(12.06)292(30.10)3(0.31)41(4.23)17(1.75)65(6.70)68(7.01)902(92.99)
合计1 317(36.79)893(24.94)874(24.41)157(4.39)154(4.30)83(2.32)102(2.85)2 999(83.77)581(16.23)
χ2值83.541152.0318.920151.0305.021—5.719121.661
P值<0.001<0.0010.003<0.0010.0250.559a0.017<0.001
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2016—2023年贵州省耐药结核病流行特征及变化趋势分析
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饶文 1 , 王大福 1 , 马晓雪 2 , 李福栋 1 , 夏梓浩 1 , 龚婷婷 1 , 洪峰 1 , 李世军 2 , 李进岚 2, 1
现代预防医学 | 流行病与统计方法 2025,52(9): 1556-1561
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现代预防医学 | 流行病与统计方法 2025, 52(9): 1556-1561
2016—2023年贵州省耐药结核病流行特征及变化趋势分析
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饶文1, 王大福1, 马晓雪2, 李福栋1, 夏梓浩1, 龚婷婷1, 洪峰1, 李世军2, 李进岚2, 1
作者信息
  • 1.贵州医科大学公共卫生与健康学院，贵州 贵阳 561113
  • 2.贵州省疾病预防控制中心结防所，贵州 贵阳 550004

    • 饶文（1999—），女，硕士在读，研究方向：疾病预防与控制

通讯作者:

李进岚，E-mail:
Analysis of the epidemiological characteristics and trends of drug-resistant tuberculosis in Guizhou province from 2016 to 2023
Wen RAO1, Da-fu WANG1, Xiao-xue MA2, Fu-dong LI1, Zi-hao XIA1, Ting-ting GONG1, Feng HONG1, Shi-jun LI2, Jin-lan LI2, 1
Affiliations
  • School of Public Health and Health, Guizhou Medical University, Guiyang, Guizhou 561113, China
出版时间: 2025-05-10 doi: 10.20043/j.cnki.MPM.202412527
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摘要
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目的

本研究通过分析贵州省2016—2023年耐药结核病(drugresistant tuberculosis，DR-TB)患者的流行特征和变化趋势，为耐药结核病防控策略提供科学依据和支持。

方法

基于“中国疾病预防控制信息系统”的子系统“结核病管理信息系统”，采用描述性流行病学方法，对贵州省DR-TB患者的流行特征及变化趋势进行分析。

结果

2016—2023年贵州省DR-TB患者共3 580例，男女比例2.15∶1，汉族2 976例(77.12%)，40～60岁组占比最高，为1 507例(42.09%)；与2016年相比，2023年≥60岁组占比有所增加(24.23% vs. 10.56%)；职业以农民为主1 844例(51.51%)。占比前三位的地区分别为：毕节市676例(18.88%)、贵阳市571例(15.95%)、铜仁市531例(14.83%)，与2016年相比，2023年毕节市、铜仁市占比增加(20.52% vs. 9.94%，11.34% vs. 3.72%)。耐药类型以利福平耐药为主，占98.41%，与2016年相比，2023年耐多药占比有所降低(45.88% vs. 98.14%)，而准广泛耐药有所增加(7.32% vs. 0)。登记分类占比前三位是新患者、初治失败和复发患者，分别为1 317例(26.79%)、893例(24.94%)、874例(24.41%)，与2016年相比，2023年新患者、复发患者占比增加(44.85% vs. 6.83%，30.10% vs. 18.63%)。

结论

2016—2023年贵州省DR-TB防控工作取得了一定成效，但其防控形势依然严峻。未来的工作应着重于持续提升分子生物学检测技术的应用，减少复发，优化资源配置，强化重点人群、重点地区的耐药防控措施，确保各地都能得到及时有效的诊疗服务。

耐药结核病  /  肺结核  /  特征分析  /  贵州省
Objective

To analyze the epidemiological characteristics and trends of drug-resistant tuberculosis (DR-TB) patients in Guizhou Province from 2016 to 2023, providing scientific evidence and support for DR-TB prevention and control strategies.

Methods

Using the “Tuberculosis Management Information System”, a subsystem of the “Chinese Disease Prevention and Control Information System”, descriptive epidemiological methods were employed to analyze the epidemiological characteristics and trends of DR-TB patients in Guizhou Province.

Results

A total of 3 580 DR-TB patients were reported in Guizhou Province from 2016 to 2023; the male-to-female ratio was 2.15:1, with 2 976 cases (77.12%) among the Han ethnic group. The age group of 40-60 years accounted for the highest proportion, with 1 507 cases (42.09%). Compared to 2016, the proportion of patients aged 60 and above increased in 2023 (24.23% vs. 10.56%). Farmers represented the majority of the patients, totaling 1 844 cases (51.51%). The top three regions were Bijie city (676 cases, 18.88%), Guiyang city (571 cases, 15.95%), and Tongren city (531 cases, 14.83%). Compared to 2016, the proportions in Bijie and Tongren cities increased in 2023 (20.52% vs. 9.94%and 11.34% vs. 3.72%, respectively). The predominant drug resistance type was rifampicin resistance (98.41%), while the proportion of multidrug-resistant cases decreased in 2023 compared to 2016 (45.88% vs. 98.14%), and the proportion of pre-extensively drug-resistant cases increased (7.32% vs. 0%). The top three categories of registration were new patients, treatment failures, and relapses, with 1 317 cases (26.79%), 893 cases (24.94%), and 874 cases (24.41%), respectively. Compared to 2016, the proportions of new patients and relapses increased in 2023 (44.85% vs. 6.83% and 30.10% vs. 18.63%).

Conclusion

The prevention and control efforts for DR-TB in Guizhou Province from 2016 to 2023 have achieved certain results, but the situation remains severe. Future work should focus on continuously improving the application of molecular biological testing technologies, reducing relapses, optimizing resource allocation, and strengthening prevention and control measures for key populations and regions, ensuring timely and effective diagnosis and treatment services across all areas.

Drug-resistant tuberculosis  /  Pulmonary tuberculosis  /  Characteristic analysis  /  Guizhou Province
饶文, 王大福, 马晓雪, 李福栋, 夏梓浩, 龚婷婷, 洪峰, 李世军, 李进岚. 2016—2023年贵州省耐药结核病流行特征及变化趋势分析. 现代预防医学, 2025 , 52 (9) : 1556 -1561 . DOI: 10.20043/j.cnki.MPM.202412527
Wen RAO, Da-fu WANG, Xiao-xue MA, Fu-dong LI, Zi-hao XIA, Ting-ting GONG, Feng HONG, Shi-jun LI, Jin-lan LI. Analysis of the epidemiological characteristics and trends of drug-resistant tuberculosis in Guizhou province from 2016 to 2023[J]. Modern Preventive Medicine, 2025 , 52 (9) : 1556 -1561 . DOI: 10.20043/j.cnki.MPM.202412527
正文
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耐药结核病(drugresistant tuberculosis，DR-TB)仍然是当前的全球健康威胁，其特点是治疗周期长、治疗成本高、治疗难度大、死亡率高等[1]。2024年全球结核病报告显示[2]，2023年全球约有40万人患上利福平DR-TB(rifampicinresistant tuberculosis, RR-TB)或者耐多药结核病（multidrug resistant tuberculosis,MDR-TB）。中国是MDR-TB/RR-TB高负担国家，患者数约占全球总数7.3%，高居第四位。贵州省作为结核病高发地区之一，近年来MDR-TB/RR-TB患者数量呈逐年上升趋势[3]，防控DR-TB的发生与传播已然成为贵州省结核病防治工作中的重点问题。因此，本研究旨在揭示贵州省DR-TB流行特征和发展趋势，为进一步完善DR-TB的防控策略提供参考依据。
1　资料与方法
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1.1　资料来源
从“中国疾病预防控制信息系统”的子系统“结核病管理信息系统”，共收集2016年1月1日—2023年12月31日贵州省登记确诊3 618例DR-TB患者的病案信息，包括患者一般情况、治疗信息、检测方法、耐药分类等。排除关键信息缺失的个案38例，最终纳入研究分析共3 580例患者。
1.2　研究方法
1.2.1　相关定义
（1）DR-TB分为单DR-TB、多DR-TB、MDR-TB、准广泛DR-TB（preextensively drugresistant tuberculosis, PreXDR-TB）、广泛DR-TB（extensively drugresistant tuberculosis, XDR-TB）、RR-TB。（2）登记分类分为新患者、初治失败、复发、复治失败、返回、初治2和3月末阳性以及其它。（3）治疗分类分为初治、复治。（4）治疗转归分为：治愈、完成治疗、成功治疗、治疗失败、死亡、失访和其他。以上分类标准参照《中国结核病防治工作技术指南（2021版）》[4]。
1.2.2　统计分析方法
数据导入SPSS 23.0进行统计分析。对于非正态分布的计量资料，采用中位数（四分位数）进行描述，计数资料使用构成比描述，构成比的组间比较用χ2检验或Fisher确切概率法，检验水准α=0.05。
2　结果
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2.1　一般情况
在3 580例DR-TB患者中，以男性和汉族为主，分别为2 442（68.21%）和2 743例（76.62%），中位年龄46（30～57）岁。职业以农民和家务及待业为主，分别为1 844（51.51%）和1 047例（29.25%）。患者来源多为转诊（1 334例，37.26%）。复治患者占63.21%（2 263例）。门诊治疗为主，为2 377例（66.40%），成功治疗1 516例（42.34%）。见表1。
2.2　DR-TB变化趋势
2.2.1　年龄分布
3 580例DR-TB患者，<20岁、20～39岁、40～59岁和≥60岁年龄组分别占5.20%、33.02%、42.09%、19.69%，组间差异有统计学意义（χ2=1 483.343，P<0.001）。其中2023年20～39岁组患者占比相较2016年有所下降(28.25% vs. 50.31%，χ2=31.211，P<0.001)，而≥60岁组患者占比则有所增加(24.23% vs. 10.56%，χ2=14.896，P<0.001)。见表2。
2.2.2　地区分布
DR-TB在9个市(州)的分布构成情况有所差异(χ2=686.536，P<0.001)，前三位的分别为：毕节市676例(18.88%)、贵阳市571例(15.95%)、铜仁市531例(14.83%)。与2016年相比，2023年贵阳市占比有所降低(14.12% vs. 68.94%，χ2=242.400，P<0.001)，而毕节市、铜仁市、黔东南州、六盘水市、黔南州、安顺市、黔西南州占比呈不同程度增长(P<0.05)。见表3。
2.2.3　耐药类型分布
3 580例患者耐药类型以RR-TB、MDR-TB、多耐药为主，分别为3 523例(98.41%)、2 109例(58.91%)、151例(4.22%)，差异有统计学意义(χ2=15 173.547，P<0.001)。在RR-TB占比高居不下的同时，MDR-TB占比从2 016年的98.14%下降至2023年的45.88%(χ2=151.514，P<0.001)，而PreXDR-TB占比从2016年的0增至2023年的7.32%(χ2=12.574，P<0.001)。见图1。
2.3　登记分类情况
各登记分类的占比有所不同(χ2=3 491.496，P<0.001)，以新患者占比最高，为1 317例(36.79%)，其次为初治失败和复发患者，分别为893(24.94%)和874例(24.41%)。其中，相较于2016年，2023年新患者及复发患者的占比有所增加(44.85%vs. 6.83%，30.10% vs. 18.63%)，初治失败、复治失败的占比则降低(12.06% vs. 52.17%，0.31% vs. 18.01%)。见表4。
2.4　检测方法
主要通过分子生物学检测(χ2=3 266.326，P<0.001)，为2 999例(83.77%)，传统药敏检测581例(16.23%)，且分子生物学检测占比从2016年的63.35%增至2023年的92.99%(χ2=121.661，P<0.001)，见表4。
3　讨论
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DR-TB的出现给患者及其家庭乃至整个社会带来了沉重的疾病负担，使结核病防控工作面临前所未有的挑战。本研究描述性分析2016—2023年贵州省DR-TB的流行特征及变化趋势，结果显示贵州省DR-TB患者中以男性、中青年、农民及复治为主，与湖南、云南、新疆等地一致[5-7]，该人群是家庭的主要劳动力，外出流动性大，可能由于就医行为、服药依从性及抽烟酗酒等个人卫生习惯差等原因而面临更高的获得性耐药、治疗失败和复发风险[7-8]。此外，近年来贵州省加强重点人群结核病筛查力度，将老年人（≥60岁组）和学生人群（<20岁组）结核病免费主动筛查工作纳入政府民生实事等措施[9]，加强了该人群的主动发现与管控。家务及待业人群DR-TB的发生，可能与家庭内传播的重要性以及缺乏定期健康检查的机会有关。提示未来还需持续优化筛查策略，加强基层医疗卫生机构的服务能力，针对家庭密切接触者做好宣传教育、筛查及随访，减少DR-TB的家庭内传播[10-11]。另外，贵阳市占比有所下降，这可能因为其作为省会城市，具备较好的医疗资源和诊疗水平，且分子生物学检测技术推广应用最早[3]，得以实现对DR-TB患者的早发现、早诊断、早治疗，有效控制疫情的发展与传播。然而，毕节市、铜仁市、黔东南州、六盘水市、黔南州、安顺市、黔西南州占比均呈不同程度增长，这可能除了与各地结核病患者基数有关外[12]，还与其地处偏远地区，医疗资源相对较少且近年来人口流动性增大[13]等有关。提示需重点关注疫情有所上升的地区，在不同地区采取差异化的防控策略。
MDR-TB占比有所下降，这一积极的变化主要归功于“十三五”以来实施的结核病综合防控措施：一是在全省9个市州建立11家耐多药结核病定点医院，提高了患者就医的可及性；二是将RR-TB纳入医保门诊慢性特殊病的保障范围，减轻了患者的经济负担，提高了患者的依从性[14]；三是成立省级结核病诊疗质量专家组对全省的结核病诊疗质量进行现场评估，并定期为结防医护人员提供培训，提升了医疗机构的诊疗能力；四是推广分子生物学检测设备和技术应用，极大地提升了检测能力和覆盖范围，通过早期快速准确地识别结核杆菌的耐药性[15]，对患者采取及时的诊断与治疗。然而，RR-TB占比高居不下且PreXDR-TB占比有所上升，反映了利福平和氟喹诺酮类药物耐药性的增加。近年来贵州省高度重视DR-TB的防控工作，对所有病原学阳性肺结核患者进行了耐药筛查，并大力推广应用分子生物学检测技术，这有效地提高了RR-TB检出率，尤其是那些原本未被识别的利福平单耐药病例。提示需加强对普通结核病患者的治疗管理，以减少治疗中断和不当使用抗生素的行为；需持续监测DR-TB的流行趋势，特别是利福平和氟喹诺酮类药物的耐药性，以及时调整防控策略；对RR-TB患者开展氟喹诺酮类药敏检测，可以实现对PreXDR-TB患者早期精准治疗以及对传播的控制[16]。
登记分类以新患者占比最大，再是初治失败和复发。其中初治失败和复治失败的占比有所下降，这可能是因为近年来贵州省不断提高全省结核病定点医院的诊治水平，如大力推广固定剂量复合制剂（FDC）的使用，并实施个体化治疗方案；针对结核病定点医院定期举办DR-TB诊断、治疗等相关知识培训，并选派医务人员到复旦大学附属华山医院、贵阳市公卫中心、遵义医科大学进行临床培训；实施全省结核病定点医院诊疗质量评估工作等[17-18]，提升地区的诊治水平，从而有效地减少了治疗失败的情况。相反，新患者、复发患者的占比有所增加。可能是由于近年来贵州省检测技术的进步、耐药筛查人群范围的扩大以及DR-TB的社会传播等，共同促进了新患者的发现；后者则反映被传播和复发患者在完成治疗后再次感染或复发的情况。提示需持续加强结核病危害与传播情况的健康教育工作，扩大分子生物学检测技术的覆盖范围并加强耐药筛查工作的实施，确保疑似耐药患者能得到及时准确的诊断，并强化结核病患者在治愈后的随访和管理,以便早期发现结核病复发并及时治疗[19]。
本研究尚存在一定局限性，所使用的数据来源于DR-TB监测系统，由于监测网络的覆盖范围有限，可能存在未被识别的DR-TB患者。
综上所述，贵州省DR-TB防控工作取得了一定成效，但其DR-TB的防控形势依然严峻。未来的工作应着重于持续提升分子生物学检测技术的应用，减少复发，优化资源配置，强化重点人群、重点地区的耐药防控措施，确保各地都能得到及时有效的诊疗服务。
基金
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  • 贵州省发改委省级基本建设前期工作项目(2020-181-131)
  • 贵州省疾病预防控制中心2024年青年科学基金项目(2024-E-7)
文献
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2025年第52卷第9期
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doi: 10.20043/j.cnki.MPM.202412527
  • 接收时间：2024-12-26
  • 首发时间：2026-03-17
  • 出版时间：2025-05-10
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  • 收稿日期：2024-12-26
基金
贵州省发改委省级基本建设前期工作项目(2020-181-131)
贵州省疾病预防控制中心2024年青年科学基金项目(2024-E-7)
作者信息
    1.贵州医科大学公共卫生与健康学院，贵州 贵阳 561113
    2.贵州省疾病预防控制中心结防所，贵州 贵阳 550004

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李进岚，E-mail:
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https://castjournals.cast.org.cn/joweb/xdyfyx/CN/10.20043/j.cnki.MPM.202412527
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2种不同金属材料的力学参数
科
Family		 属数
Number of
genus		 种数
Number of
species		 占总种数比例
Percentage of
total species (%)		 属
Genus		 种数
Number of
species		 占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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