某医院广泛耐药结核病住院患者耐药特点及危险因素分析
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摘要
目的分析广泛耐药结核病(extensively drug-resistant tuberculosis, XDR-TB)患者对一、二线抗结核药物耐药情况及危险因素。方法收集结核分枝杆菌培阳的住院结核患者,采用分枝杆菌微孔板法药敏检测试可信区间剂盒筛出XDR-TB患者,采用Logistic回归分析XDR-TB患者一、二线抗结核药耐药危险因素。结果利福平、异烟肼和利福喷丁耐药率100%,链霉素、利福布汀、乙硫异烟肼、左氧氟沙星和卷曲霉素耐药率90～100%,卡那霉素和对氨基水杨酸耐药率70～80%,阿米卡星耐药率60～70%,丙硫异烟肼耐药率50～60%,乙胺丁醇和莫西沙星耐药率40～50%,克拉霉素耐药率10～20%,氯法齐明耐药率5.2%。XDR-TB中有92.1%的患者对10种以上抗结核药物,耐药种类最少的患者耐6种抗结核药物。Logistic回归分析XDR-TB对一、二线抗结核药物耐药的危险因素包括年龄[20～40岁为(OR=6.318, 95%CI:1.204～33.15,P=0.029;40～60岁为(OR=4.772, 95%CI:0.973～23.392,P>0.05); 60岁以上为(OR=41.366, 95%CI:2.909～588.265,P=0.006)]和抗结核治疗史为复治(OR=28.013, 95%CI:3.357～233.766,P=0.002)。结论 XDR-TB患者耐药情况严重,但有药可治,耐药种类多,其危险因素主要来源于年龄和抗结核治疗史。
Objective To analyze the drug resistance profile and risk factors for extensively drug resistant tuberculosis(XDR-TB) patients. Methods XDR-TB cases were identified by sixteen anti-TB drug susceptibility kits among inpatients with a diagnosis of laboratory-confirmed mycobacterium tuberculosis. Single-factor and Logistic analysis were used to analyze the risk factors for drug resistant of the first and second-line anti-TB drugs in XDR-TB patients. Results Resistant rate of rifampin, isoniazid and rifampicin were 100%, Resistant rate of streptomycin, rifampicin and dean, b sulfur isoniazid, levofloxacin and capreomycin were from 90% to 100%, resistant rate of kanamycin and amino salicylic acid were from 70% to 80%, resistant rate of amikacin from 60% to 70%, resistant rate of sulfur isoniazid was from 50% to 60%, resistant rate of ethambutol and moxifloxacin were from 40% to 50%, resistant rate of clarithromycin was from 10% to 20%, resistant rate of clofazimine 5.2%. 92.1% of XDR-TB patients were resistant to more than 10 anti-TB drugs, and the least of the patients were resistant to 6 anti-TB drugs.Logistic regression analysis showed the risk factors for XDR-TB first-and second-line anti-tb drugs included age [20-40 year(OR=6.318, 95% CI: 1.204-33.15, P=0.029;40-60 year(OR=4.772, 95% CI: 0.973-23.392, P=0.054); 60 year(OR=41.366, 95% CI: 2.909-588.265, P=0.006)] and anti-TB treatment history was retreatment(OR=28.013, 95% CI: 3.357-233.766, P=0.002). Conclusions XDR-TB patients have serious drug resistance, but there were some drug treatable drug resistance types, and the risk factors mainly come from age and anti-TB treatment history.
Objective To analyze the drug resistance profile and risk factors for extensively drug resistant tuberculosis(XDR-TB) patients. Methods XDR-TB cases were identified by sixteen anti-TB drug susceptibility kits among inpatients with a diagnosis of laboratory-confirmed mycobacterium tuberculosis. Single-factor and Logistic analysis were used to analyze the risk factors for drug resistant of the first and second-line anti-TB drugs in XDR-TB patients. Results Resistant rate of rifampin, isoniazid and rifampicin were 100%, Resistant rate of streptomycin, rifampicin and dean, b sulfur isoniazid, levofloxacin and capreomycin were from 90% to 100%, resistant rate of kanamycin and amino salicylic acid were from 70% to 80%, resistant rate of amikacin from 60% to 70%, resistant rate of sulfur isoniazid was from 50% to 60%, resistant rate of ethambutol and moxifloxacin were from 40% to 50%, resistant rate of clarithromycin was from 10% to 20%, resistant rate of clofazimine 5.2%. 92.1% of XDR-TB patients were resistant to more than 10 anti-TB drugs, and the least of the patients were resistant to 6 anti-TB drugs.Logistic regression analysis showed the risk factors for XDR-TB first-and second-line anti-tb drugs included age [20-40 year(OR=6.318, 95% CI: 1.204-33.15, P=0.029;40-60 year(OR=4.772, 95% CI: 0.973-23.392, P=0.054); 60 year(OR=41.366, 95% CI: 2.909-588.265, P=0.006)] and anti-TB treatment history was retreatment(OR=28.013, 95% CI: 3.357-233.766, P=0.002). Conclusions XDR-TB patients have serious drug resistance, but there were some drug treatable drug resistance types, and the risk factors mainly come from age and anti-TB treatment history.
引文
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[11] 马晓梅,闫国立,段广才,等. 决策树模型在手足口病合并脑膜脑炎重症化危险因素中的应用[J].中华疾病控制杂志, 2018,22(9): 961-964. DOI: 10.16462/j.cnki.zhjbkz.2018.09.021. Ma XM, Yan GL, Duan GC. et al. Application of decision tree in the analysis and prediction of risk factors of severe hand,foot and mouth disease combined with meningocephalitis [J]. Chin J Dis Control Prev, 2018,22(9): 961-964. DOI: 10.16462/j.cnki.zhjbkz.2018.09.021.
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[14] Lee CH, Wang JY, Lin HC, et al. Treatment delay and fatal outcomes of pulmonary tuberculosis in advanced age: a retrospective nationwide cohort study [J]. BMC Infect Dis, 2017,17(1): 449-473. DOI: 10.1186/s12879-017-2554-y.
[15] Irfan U, Arshad J, Zarfishan T, et al. Pattern of drug resistance and risk factors associated with development of drug resistant mycobacterium tuberculosis in Pakistan [J]. PLOS ONE, 2016, 11(1):e0147529. DOI:10.1371/journal.pone.0147529.
[2] 李静,沈鑫,张阳奕,等. 上海地区MDR-TB患者二线药物耐药危险因素分析 [A]. 2011年中国防痨协会全国学术会议论文集, 2011:5. Li J, Shen X, Zhang YY, et al. Risk factors for second-line drug resistance in MDR-TB patients in Shanghai [A]. Papers Collection of The National Academic Conference Form Chinese Anti-tuberculosis Association 2011, 2011:5.
[3] Abubakar I, Moore J, Drobniewski F, et al. Extensively drug resistant tuberculosis in the UK:1995-2007 [J]. Thorax, 2009,64(6):512-515. DOI: 10.1136/thx.2008.108712.
[4] 陆伟,周扬,陈诚,等. 江苏省社区人群结核杆菌耐药状况及影响因素研[J]. 中华疾病控制杂志, 2013,17( 7):560-563. Lu W, ZhouY, Chen C, et al. Prevalence and risk factors for drug resistance tuberculosis in Jiangsu Province: a population based study [J]. Chin J Dis Control Prev, 2013,17( 7):560-563.
[5] 全国结核病耐药性基线调查报告,中国人民共和国卫生部 [M]. 人民卫生出版社.2010. National baseline survey report on TB resistance, Ministry of health of the People's Republic of China [M]. People's Medical Publishing House.2010.
[6] 初乃惠. 抗结核药物研究进展 [J]. 中国实用内科杂志,2015,35(8):655-660. DOI:10.7504/nk2015070105. Chu NH. Research progress of anti-tuberculosis drugs [J]. Chin J Pract Int Med, 2015,35(8):655-660. DOI:10.7504/nk2015070105.
[7] 解燕,缪昌东,张德坤. 2012-2014年泰州市痰培养阳性肺结核患者耐药结果分析 [J]. 现代预防医学, 2016,43(21):4005-4008. Xie Y, Miao CD, Zhang DK.Drug resistance of tuberculosis among patients with positive sputum culture, Taizhou City,2012-2014 [J]. Modern Preventive Medicine, 2016,43(21): 4005-4008.
[8] Kliiman K, Altraja A. Predictors of extensively drug resistant pulmonary tuberculosis [J]. Ann Intern Med, 2009,150(11):766-775. DOI: 10.7326/0003-4819-150-11-200906020-00004.
[9] Saukkonen JJ, Cohn DL, Jasmer RM, et al. An official ATS statement: hepatotoxicity of antituberculosis therapy [J]. Am J Respir Crit Care Med, 2006,174(8):935-952. DOI: 10.1164/rccm.200510-1666ST.
[10] 郭秀花. 医学统计学与SPSS软件实现方法 [M]. 科学出版社,2015. Guo XH. Medical statistics and SPSS software implementation method [M]. Science Press.2015.
[11] 马晓梅,闫国立,段广才,等. 决策树模型在手足口病合并脑膜脑炎重症化危险因素中的应用[J].中华疾病控制杂志, 2018,22(9): 961-964. DOI: 10.16462/j.cnki.zhjbkz.2018.09.021. Ma XM, Yan GL, Duan GC. et al. Application of decision tree in the analysis and prediction of risk factors of severe hand,foot and mouth disease combined with meningocephalitis [J]. Chin J Dis Control Prev, 2018,22(9): 961-964. DOI: 10.16462/j.cnki.zhjbkz.2018.09.021.
[12] Walter ND, Strong M, Belknap R, et al. Translating basic science insight into public health action for multidrug and extensively drug-resistant tuberculosis [J]. Respirology, 2012, 17(5): 772–791. DOI: 10.1111/j.1440-1843.2012.02176.x.
[13] Cadosch D, Pia AZW, Kouyos R, et al.The role of adherence and retreatment in de novo emergence of MDR-TB [J]. Plos Computational Biology,2016, 12(3):e1004749. DOI: 10.1371/journal.pcbi.1004749.
[14] Lee CH, Wang JY, Lin HC, et al. Treatment delay and fatal outcomes of pulmonary tuberculosis in advanced age: a retrospective nationwide cohort study [J]. BMC Infect Dis, 2017,17(1): 449-473. DOI: 10.1186/s12879-017-2554-y.
[15] Irfan U, Arshad J, Zarfishan T, et al. Pattern of drug resistance and risk factors associated with development of drug resistant mycobacterium tuberculosis in Pakistan [J]. PLOS ONE, 2016, 11(1):e0147529. DOI:10.1371/journal.pone.0147529.