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Objective@#To establish and evaluate a microfluidic chip platform for the rapid diagnosis of post-neurosurgical bacterial infection. @*Methods@#The pathogens isolated from patients with post-neurosurgical bacterial infection in Beijing Tiantan Hospital Affiliated to Capital Medical University during 2007 and 2016 and the epidemiological data from China drug resistance monitoring network CHINET were analyzed retrospectively. Based on the retrospective data and the molecular epidemiological information of drug-resistant bacteria reported in the literature, target pathogens and drug resistance gene parameters were selected. The microbial identification parameters from 10 different bacteria, including Klebsiella pneumoniae, Acinetobacter baumannii, Staphylococcus epidermidis, Enterobacter cloacae, Staphylococcus aureus, Escherichia coli, Enterococcus faecium, Enterococcus faecalis, Stenotrophomonas maltophilia and Pseudomonas aeruginosa, and the parameters of 15 drug resistance genes, including mecA, vanA, vanB, aacC1, aadA1, bla CTX-M-1 , bla CTX-M-9 , bla GES-1 , bla OXA-23 , bla OXA-24 , bla OXA-58 , bla OXA-66 , bla KPC-2 , bla IMP-4 and bla VIM-2 , were selected for designing a microfluidic chip platform. Using MAIDI-TOF MS for bacterial identification, multiplex PCR for the detection of drug resistance genes, micro-broth dilution method for the detection of drug resistance phenotypes and ESBLs screening test as reference methods, 13 known bacteria were used to evaluate the preliminary performance of the established microfluidic chip platform, and 108 cerebrospinal fluid bacterial culture positive specimens were used to evaluate the clinical application value of the microfluidic chip platform. @*Results@#The identification rates of 13 known strains and the coincidence rate of drug resistance genes were 100%. The coincidence rate of identification results for 108 cerebrospinal fluid bacterial culture positive specimens between the microfluidic chip platform and the MALDI-TOF MS method was as high as 94.44%. The coincidence rates of drug resistance phenotype of carbapenems, oxacillin, vancomycin, ESBLs and genotype between the microfluidic chip platform and the micro-broth dilution method or ESBLs screening test were above 90%. @*Conclusion@#The established microfluidic chip platform is fast and accurate, and has application value in microbial identification and the prediction of drug resistance, which may be used as an important supplementary method in the diagnosis of post-neurosurgical bacterial infection.
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Objective To investigate the diagnostic value of procalcitonin ( PCT) and lactate in cerebrospinal fluid (CSF) combined with conventional biomarkers for post-neurosurgical bacterial meningitis (PBM).Methods Clinical data of 213 patients with post-neurosurgical meningitis admitted in Beijing Tiantan Hospital, Capital Medical University from March 2017 to December 2017 were retrospectively analyzed, including 85 cases of PBM and 128 cases of post-neurosurgical aseptic meningitis ( PAM).The diagnostic value of CSF procalcitonin , lactate and other 12 conventional biomarkers for PBM was analyzed by multivariate logistic regression.A prediction algorithm was generated and its diagnostic value for PBM was assessed with receiver operating characteristic curve (ROC).Results The univariate analysis showed that CSF cell count, CSF leukocyte count , CSF protein concentration , CSF glucose concentration, CSF glucose／blood glucose ratio, CSF PCT and CSF lactate were significantly associated with PBM.Multivariate logistic regression analysis showed that CSF PCT , CSF lactate, CSF protein concentration and CSF glucose ／blood glucose ratio were independent predictive factors for PBM.The predictive algorithm score ＝4.315 ×CSF PCT+0.822×CSF Lactate+0.009×CSF protein concentration -5.480×CSF glucose／blood glucose ratio-3.074.The predictive algorithm has the largest area under the ROC curve ( AUC ＝0.947), and the sensitivity and specificity of the predictive algorithm score were 90.60% and 85.10%, respectively.The positive predictive value , negative predictive value and the accurate rate of the algorithm in diagnosis of PBM were 84.06%, 94.44% and 90.40%, respectively.Conclusion The predictive algorithm based on the combination of CSF PCT and CSF lactate with CSF protein concentration and CSF glucose ／blood glucose ratio has a good diagnostic value for PBM.It can shorten the diagnosis time of PBM and improve the clinical outcomes.
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Objective To explore the differences in antibiotic resistance among pathogenic bacteria isolated from respiratory tract and cerebrospinal fluid specimens in neurosurgery wards .Methods Antibiotic resist-ance tests were performed to analyze the antibiotic sensitivities of pathogenic bacteria isolated from respiratory tract and cerebrospinal fluid specimens in the neurosurgery wards at Beijing tiantan hospital affiliated to cap-ital medical university ,from January 2012 to December 2016 .Statistical analysis was performed using the t test or M-W test to determine the differences between the two independent samples were statistically significant . Results From January 2012 to December 2016 ,6 091 strains isolated from respiratory tract and 1 597 strains isolated from CSF specimens were obtained from patients in the neurosurgery wards of a hospital .Based on the results of the t test ,differences in the antibiotic sensitivities of pathogenic bacteria isolated from these two specimens were statistically significant .Three Gram-negative bacteria ,Pseudomonas aeruginosa ,Klebsiella pneumoniae and Acinetobacter baumannii ,showed statistically significant differences in antibiotic sensitivities between respiratory tract and cerebrospinal fluid specimens (P＜0 .05) ,but this difference was not statistically significant in Staphylococcus aureus (P＞0 .05) .Pathogenic bacteria isolated from two specimens showed sta-tistically significant differences in sensitivity to β-lactam antibiotics ,polymyxin B ,vancomycin and linezolid (P＜0 .05) .Conclusion The sensitivity differences between bacteria isolated from respiratory tract and cere-brospinal fluid specimens are statistically significant .Several reasons ,such as antibiotic-induced antibiotic re-sistance ,horizontal gene transfer are responsible for this result .
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Objective To study on the contribution and cut-off value of coagulase negative staphylococcus (CoNS) in laboratory tests of postoperative infection in neurosurgery and optimize the diagnostic criteria of infection.Methods It made a retrospective study of 650 cerebrospinal fluid (CSF)specimens from neurosurgical patients,who were infected CoNS in Beijing Tiantan Hospital affiliated to Capital Medical University during 2013-2015.The epidemiological data were collected and 8 routine clinical laboratory tests were performed.T test was used to compare the difference among the groups.By making receiver operating characteristic (ROC) curve,the area under the curve (AUC),cut-off value,sensitivity and specificity were obtained.Results A total of 19 756 CSF specimens were collected and 650 CoNS were isolated.The separation rate of CoNS was 3.3％ which was the most frequently isolated bacteria.The differences of cerebrospinal fluid white blood cell count (3 598.6 ± 1 884.3,678.1 ± 629.1,t =2.662,P =0.012),multinucleated cell ratio in cerebrospinal fluid(76.0 ±32.6,46.8 ±29.9,t =9.593,P =0.001),cerebrospinal fluid glucose concentration (5.9 ± 2.12,6.2 ± 1.92,t =-16.296,P =0.001) and cerebrospinal fluid glucose concentration/blood glucose concentration (0.3 ± 0.16,0.63 ± 0.31,t =-11.968,P =0.000) among groups were statistically significant.The AUCs of cerebrospinal fluid white blood cell count,cerebrospinal fluid glucose and cerebrospinal fluid glucose/blood glucose were more than 0.8,and the sensitivities of the three indicators were more than 80.0％.In addition,the specificity of cerebrospinal fluid glucose concentration/blood glucose concentration was more than 0.9.Conclusions CoNS was the main pathogenic bacteria of neurosurgical infections in a hospital.Cerebrospinal fluid white blood cell count,cerebrospinal fluid glucose and the ratio of cerebrospinal fluid glucose and blood glucose could be used for auxiliary diagnosis of CoNS infections in neurosurgical patients.
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Objective To investigate the distribution and antimicrobial resistance of Coagulase-negative staphylococci ( CoNS) isolated from cerebrospinal fluids in neurosurgical patients.Methods CoNS strains isolated from cerebrospinal fluids of neurosurgical patients were collected from Beijing Tiantan Hospital of Capital Medical University during January 2013 and December 2015.CoNS infection was diagnosed according to the standards of US Centers for Disease Control and Prevention, and the distribution and antimicrobial resistance of pathogenic CoNS strains were analyzed. Results A total of 19 756 cerebrospinal fluid specimens were collected and 1 386 bacterial strains were isolated, in which 650 (46.9%) were CoNS.Among 650 CoNS strains, 130 were diagnosed as the pathogen, and the top 4 CoNS species were Staphylococcus epidermidis (77/130, 59.2%), Staphylococcus hominis (18/130, 13.8%), Staphylococcus haemolyticus (11/130, 8.5%) and Staphylococcus capitis (9/130, 6.9%).The rest 520 CoNS strains were contaminating strains.According to antimicrobial susceptibility test, there were 103 strains of methicillin-resistant CoNS (MR-CoNS) accounting for 79.1% (103/130).And among 77 Staphylococcus epidermidis isolates, 67 were MR-CoNS strains (87.0%) .More than 90.0%Staphylococcus epidermidis isolates were sensitive to vancomycin and linezolid, and the rest CoNS strains were also highly sensitive to these two antibacterial agents.Conclusions CoNS plays an important role in post-surgery infection in neurosurgical patients, and Staphylococcus epidermidis is the dominant CoNS species.Most CoNS strains are methicillin-resistant, but are highly sensitive to vancomycin and linezolid.
