目的 评估AMA-M2、SP100和GP210三种自身抗体在诊断原发性胆汁性肝硬化(primary biliary cirrhosis,PBC)中的应用价值。方法 收集我院近3年就诊患者的AMA-M2、SP100、GP210、ALP和GGT检测数据,其中PBC患者50例,非PBC肝胆疾病或自身免疫病患者226例,正常对照290例。分析这些检测指标对PBC诊断的敏感度和特异度。结果 AMA-M2、SP100和GP210诊断原发性胆汁性肝硬化的敏感度分别为96.00%、36.00%、8.00%,特异度分别为98.26%、97.87%、99.03%。PBC组病人的ALP和GGT检测结果高于非PBC病人组。结论 AMA-M2、SP100和GP210对PBC的临床诊断特异度较高;AMA-M2的敏感度高,但SP100和GP210敏感度低。
Objective To evaluate the diagnostic accuracy of AMA-M2, SP100 and GP210 for the primary biliary cirrhosis (PBC).Methods A total of 50 patients with PBC and 226 patients with other liver diseases or autoimmune diseases were enrolled in this study and 290 healthy individuals were included as normal controls. The data of AMA-M2, SP100, GP210, ALP and GGT were collected and analyzed for sensitivity and specificity in the diagnosis of PBC.Results The sensitivity and specificity of AMA-M2, SP100 and GP210 in the diagnosis of PBC were 96.00%, 36.00%, 8.00% and 98.26%, 97.87%, 99.03%, respectively. Compared to PBC group, the concentrations of ALP and GGT in non-PBC patients and controls were low.Conclusion AMA-M2 is quite accurate with high specificity and sensitivity in the diagnosis of PBC. However, SP100 and GP210 have high sensitivity but low sensitivity.
目的 通过高通量测序法对多重耐药大肠埃希菌HX43进行耐药分子机制的研究。方法 用Illumina Miseq平台对HX43进行高通量测序,用Edena、RAST、ResFinder、MLST和BLAST等生物信息学工具或数据库进行数据分析,获得耐药基因相关序列数据。结果 HX43对多种临床常用抗生素均不敏感,仅对碳氢霉烯类药物敏感。对高通量测序数据的分析研究发现,该菌存在多种耐药基因,包括β-内酰胺类耐药基因3个(blaCMY-42、blaCTX-M-14和blaOXA-30),氨基糖苷类耐药基因5个(aac(3)-IIa、aadA5、 strA、 strB和aac(6′)-Ib-cr),喹诺酮类耐药基因1个(aac(6′)-Ib-cr),磺胺及甲氧苄啶类耐药基因3个(sul1、sul2和dfrA17),四环素耐药基因1个(tet(B)),氯霉素耐药基因2个(catB3和cmlA1),大环内酯类耐药基因2个(erm(B)和mph(A))。对包含blaCMY-42的contigs进行分析,发现该基因与ISEcp1插入序列、blc和sugE等基因相关联。质粒分型发现HX43携带5种不相容群的质粒。多位点序列分型(MLST)分析发现HX43属于ST3835,为国内外较少见的序列型。结论 高通量测序技术可准确获得临床菌株抗生素耐药的相关基因信息,为临床抗菌治疗提供重要的实验室数据支持。
Objective To investigate the molecular resistance mechanism of Escherichia coli HX43 by high-throughput sequencing. Methods HX43 was sequenced by the Illumina Miseq platform, and sequencing data were analyzed by the Edena, RAST, ResFinder, MLST and BLAST softwares and databases. Results HX43 was resistant to most common clinical antibiotics except carbapenems. Analysis of data revealed resistance genes to β-lactams (blaCMY-42, blaCTX-M-14 and blaOXA-30), aminoglycosides (aac(3)-IIa, aadA5, strA, strB and aac(6′)-Ib-cr), quinolones (aac(6′)-Ib-cr), trimethoprim/sulfonamides(sul1, sul2 and dfrA17), tetracyclines (tet(B)), chloramphenicol (catB3 and cmlA1), macrolides(erm(B) and mph(A)). Sequence analysis of the contig containing blaCMY-42 identified correlations of the gene with ISEcp1 insertion sequences, blc and sugE genes. Plasmid typing identified 5 plasmid incompatibility groups in HX43. MLST analysis found that HX43 belonged to ST3835, a relatively rare sequence type in the world. Conclusion Information of resistance genes can be obtained by high-throughput sequencing, which provides important experimental data for clinical antimicrobial treatment.
目的 分析我院2011—2015年我院儿科住院患者下呼吸道病原菌分布及其耐药性。方法 采用全自动生化鉴定仪对痰标本分离株进行鉴定,用全自动微生物药敏系统和纸片扩散法对病原菌的耐药性进行检测,并用头孢硝噻吩纸片法对β-内酰胺酶进行检测。结果 2011—2015年共分离得到下呼吸道病原菌518株,包括肺炎链球菌(21.62%)、金黄色葡萄球菌(16.99%)、流感嗜血杆菌(14.48%)、肺炎克雷伯菌(11.97%)、大肠埃希菌(8.11%)、卡他莫拉菌(5.41%)、鲍曼不动杆菌(3.86%)和铜绿假单胞菌(3.86%)等。药敏结果显示,肺炎链球菌对克林霉素(90.18%)、红霉素(92.86%)和复方新诺明(87.50%)的耐药率较高,金黄色葡萄球菌则对青霉素G(90.91%)和红霉素(68.18%)有较强耐药性,未发现对万古霉素或利奈唑胺耐药的革兰阳性球菌。流感嗜血杆菌对氨苄西林耐药率为32%,与其β-内酰胺酶阳性率较一致,肺炎克雷伯菌和大肠埃希菌对头孢类药物(17.33%~45.33%)和喹诺酮类药物(34.67%~50.67%)耐药性较高,并发现1株碳青霉烯耐药的肺炎克雷伯菌。结论 本院下呼吸道感染病原菌谱较广,主要包括多种革兰阳性球菌和革兰阴性杆菌,并对多种抗菌药物表现出较强耐药性,临床应注重合理应用相关抗生素,严格防控病原菌的医院感染及传播。
Objective To analyze the antimicrobial resistance and the profile of pathogens from lower respiratory tract infections in pediatric in patients. Methods Sputum bacterial isolates were identified by an automated biochemical identification system. Antimicrobial resistance was detected by an automated drug susceptibility detection system and the disc diffusion method. The β-lactamases was tested by the nitrocefin disc detection method. Results Five hundred and eighteen bacterial pathogens were isolated from sputum samples during 2011-2015, including streptococcus pneumoniae(21.62%), staphylococcus aureus(16.99%), haemophillus influenzae(14.48%), klebsiella pneumoniae(11.97%), escherichia coli(8.11%), moraxelle catarrhalis(3.8%), acinetobacter baumanii(3.86%) and pseudomonas aeruginosa(3.86%). High resistant rates were detected for S. pneumoniae to clindamycin(90.18%), erythromycin(92.86%) and sulfamethoxazole (85.50%), while S. aureus was highly resistant to penicillin G(90.91%) and erythromycin(68.18%). Resistance to vancomycin and linezolid was not detected for gram positive cocci. The resistant rate to ampicillin was 32% for H. influenzae, which was in concordance with the production of β-lactamases. Relatively high resistance was detected for K. pneumoniae and E. coli to cephalosporins and quinolones. A carbapenem-resistant K. pneumoniae isolate was also detected. Conclusion Multiple bacterial species were isolated from lower respiratory tract infections in our hospital, including different species of gram positive cocci and gram negative bacilli, and these isolates exhibited high resistance to antibiotics tested. The clinical use of antibiotics and hospital infection and transmission of these pathogens should be controlled.
目的 统计分析2011—2014年我院分离的肠杆菌科细菌数据,探讨耐碳青霉烯肠杆菌科细菌(CRE)的流行特征。方法 收集肠杆菌科细菌,根据药敏结果筛选出CRE菌株,并对相关临床资料进行统计分析。结果 共分离得到CRE菌株187株,标本来源依次为尿液(32.6%)、痰液(28.9%)和血液(10.7%)。从科室分布来看,39.0%的菌株来自重症监护室病区,23.0%的菌株来自泌尿外科病区,在其它病区呈散发分布。菌株的种属分布方面,肺炎克雷伯菌的比例为39.6%, 大肠埃希菌的比例为20.9%;从病人年龄构成来看,50岁以上高龄患者的分离比例达74.4%。CRE的分离数目随年份的递增而不断升高。结论 耐碳青霉烯肠杆菌科细菌的流行率呈现逐年递增的趋势,临床应合理使用相关抗生素,预防和控制CRE在医院环境中的流行。
Objective To investigate the epidemiological features of carbapenem resistant Enterobacteriaceae in a collection of clinical Enterobacteriaceae strains isolated during 2011-2014 from our hospital. Methods The Enterobacteriaceae strains were collected and CRE strains were screened by their resistance to carbapenems. Clinical information was analyzed to characterize the epidemiological traits of CRE strains. Results The total number of CRE isolates was 187. These CRE strains were isolated from various clinical specimens, including urine(32.6%), sputum (28.9%), blood (10.7%), and so on. These strains were frequently isolated from intensive care units (ICU) (39.0%) and department of Urology (23.0%). The most frequently isolated species were Klebsiella pneumoniae (39.6%), Escherichia coli (20.9%). The isolation rate is much higher in elderly patients more than 50 years old (74.4%). The percentage of CRE isolates were kept on increasing by years. Conclusion The prevalence carbapenem resistant Enterobacteriaceae in our hospital is increasing every year and it is important to prevent and control the transmission and outbreaks of CRE in the hospital by proper use of related antibiotics in clinical treatment.
目的 利用基质辅助激光解吸电离飞行时间质谱系统(VITEK-MS)对体液培养阳性瓶进行直接鉴定,探索快速诊断临床致病菌的新策略。方法 收集体液培养阳性瓶,不经琼脂平板培养,直接利用VITEK-MS进行鉴定,并与传统生化鉴定的方法进行比较分析。结果 50例体液培养阳性瓶中,传统细菌鉴定法检出47株阳性菌,3例阴性;而VITEK-MS直接鉴定法检出31株阳性菌,同样3例阴性。VITEK-MS直接鉴定法灵敏度达65.96%,特异度为100%,临床符合率为68%。鉴定时间从24小时缩短到2小时。结论 利用VITEK-MS质谱系统直接鉴定体液培养阳性标本中的病原菌,能有效缩短细菌鉴定时间,准确快速地诊断临床致病菌。
Objective To find a fast method for detection of pathogens in positive culture bottles by using the VITEK-MS system. Methods VITEK-MS microbial identification system was used to directly identify the bacteria in the positive culture bottles, without culture on agar plates. The identification results were further compared with those by the traditional biochemical identification. Results Forty-seven bacterial strains were identified by traditional biochemical methods among 50 positive culture bottles, and 3 of them were negative. Of these 50 samples, thirty-one bacterial strains were identified by VITEK-MS and 3 were also negative. The sensitivity and specificity for direct VITEK-MS identification were 65.96% and 100%, and the clinical coincidence rate was 68%. The turn around time for identification was reduced from 24 to 2 hours. Conclusion Direct identification of bacterial pathogens in positive culture bottles by VITEK-MS could reduce turn around time, and lead to accurate and fast diagnosis.
