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Sepsis has been a focus and difficulty in both clinical and laboratory research. Early pathogen identification, host immune status assessment, and abnormal coagulation function, the three critical issues in the laboratory diagnosis of sepsis, have made continuous breakthroughs in recent years. Many challenges in the field remain. An in-depth analysis of these key issues in sepsis can improve the understanding of the importance of sepsis diagnosis and assist in increasing the survival rate of patients.
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Objective:To establish a performance validation method for mNGS applied in BALF samples.Method:Hela cells were used as a representative of host cells, and simulated BALF samples were prepared by adding different concentrations of Hela cells, seven species of isolated pathogens (including Streptococcus pneumonia, Hemophilus influenza, Klebsiella pneumonia, Candida albicans, Cryptococcus neoformans, Aspergillus fumigatus, and Adenovirus), and interfering substances to sterile normal saline. Clinical BALF samples were collected simultaneously, and the results of mNGS were evaluated using traditional detection methods as a reference. The limit of detection (LOD), precision, anti-interference ability, stability, and accuracy of mNGS were determined. Results:In the simulated samples, the LOD of Streptococcus pneumoniae, Haemophilus influenzae, Klebsiella pneumoniae, Candida albicans, Cryptococcus neoformans, Aspergillus fumigatus, and Adenovirus were 150, 262, 102, 67, 96, 83 CFU/ml, and 439 copies/ml, respectively. The repeatability of the detection results for all pathogens of simulated positive BALF samples was 100%. The anti-interference test showed that the higher the concentration of human DNA, the fewer pathogen sequences detected by mNGS. Escherichia coli and Shigella sonnei were used to evaluate the ability of mNGS to distinguish closely related species. The results showed that the system could stably distinguish Escherichia coli and Shigella sonnei when the concentration of Shigella sonnei was 4, 000 CFU/ml. The stability test results showed that there was no significant change in the number of pathogen sequences detected whether after 1 to 3 freeze-thaw cycles or storage at 4 ℃, -20 ℃, or -80 ℃ for 36 h. Compared with traditional detection methods, the accuracy of 17 clinical samples was 82.4%(14/17). Continuous evaluation of clinical BALF samples simultaneously tested by mNGS and traditional methods at Tongji Hospital from October 25, 2021, to September 14, 2022, showed that the accuracy of mNGS compared to bacterial culture, fungal culture, mycobacterial culture, Mycobacterium tuberculosis culture, and conventional PCR techniques was 67.5%(472/699), 81.5%(570/699), 92.3%(335/363), 96.4%(350/363), and 86.8%(132/152), respectively. Compared with conventional PCR techniques, the accuracy of mNGS for detecting Pneumocystis jirovecii, Adenovirus, and Mycoplasma pneumoniae was 89.4%(84/94), 93.3%(56/60), and 87.1%(61/70), respectively. Conclusion:By preparing simulated BALF samples and using traditional detection methods as a reference, the performance characteristics of mNGS in detecting BALF samples can be preliminarily evaluated.
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Objective:To evaluate the performance of an artificial intelligent (AI)-based automated digital cell morphology analyzer (hereinafter referred as AI morphology analyzer) in detecting peripheral white blood cells (WBCs).Methods:A multi-center study. 1. A total of 3010 venous blood samples were collected from 11 tertiary hospitals nationwide, and 14 types of WBCs were analyzed with the AI morphology analyzers. The pre-classification results were compared with the post-classification results reviewed by senior morphological experts in evaluate the accuracy, sensitivity, specificity, and agreement of the AI morphology analyzers on the WBC pre-classification. 2. 400 blood samples (no less than 50% of the samples with abnormal WBCs after pre-classification and manual review) were selected from 3 010 samples, and the morphologists conducted manual microscopic examinations to differentiate different types of WBCs. The correlation between the post-classification and the manual microscopic examination results was analyzed. 3. Blood samples of patients diagnosed with lymphoma, acute lymphoblastic leukemia, acute myeloid leukemia, myelodysplastic syndrome, or myeloproliferative neoplasms were selected from the 3 010 blood samples. The performance of the AI morphology analyzers in these five hematological malignancies was evaluated by comparing the pre-classification and post-classification results. Cohen′s kappa test was used to analyze the consistency of WBC pre-classification and expert audit results, and Passing-Bablock regression analysis was used for comparison test, and accuracy, sensitivity, specificity, and agreement were calculated according to the formula.Results:1. AI morphology analyzers can pre-classify 14 types of WBCs and nucleated red blood cells. Compared with the post-classification results reviewed by senior morphological experts, the pre-classification accuracy of total WBCs reached 97.97%, of which the pre-classification accuracies of normal WBCs and abnormal WBCs were more than 96% and 87%, respectively. 2. The post-classification results reviewed by senior morphological experts correlated well with the manual differential results for all types of WBCs and nucleated red blood cells (neutrophils, lymphocytes, monocytes, eosinophils, basophils, immature granulocytes, blast cells, nucleated erythrocytes and malignant cells r>0.90 respectively, reactive lymphocytes r=0.85). With reference, the positive smear of abnormal cell types defined by The International Consensus Group for Hematology, the AI morphology analyzer has the similar screening ability for abnormal WBC samples as the manual microscopic examination. 3. For the blood samples with malignant hematologic diseases, the AI morphology analyzers showed accuracies higher than 84% on blast cells pre-classification, and the sensitivities were higher than 94%. In acute myeloid leukemia, the sensitivity of abnormal promyelocytes pre-classification exceeded 95%. Conclusion:The AI morphology analyzer showed high pre-classification accuracies and sensitivities on all types of leukocytes in peripheral blood when comparing with the post-classification results reviewed by experts. The post-classification results also showed a good correlation with the manual differential results. The AI morphology analyzer provides an efficient adjunctive white blood cell detection method for screening malignant hematological diseases.
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Objective:To explore the predictive efficacy of prothrombin time (PT) with regarding for the severity and prognosis of septic patients, along with comparing with other routine coagulation parameters.Methods:A retrospective analysis was conducted. The clinical data of 302 septic patients who were admitted to the intensive care unit (ICU) of Tongji Hospital, Tongji Medical College of Huazhong University of Science and Technology from January 1 to December 31 in 2019 were enrolled. Demographic and basic clinical data were collected. Laboratory data, including PT, activated partial thromboplastin time (APTT), thrombin time (TT), fibrinogen (FIB), D-dimer, fibrin (fibrinogen) degradation product (FDP), antithrombin (AT), platelet count (PLT) at ICU admission were recorded, and sequential organ failure assessment (SOFA) score, acute physiology and chronic health evaluation Ⅱ (APACHEⅡ) score within 24 hours of admission to ICU were also collected. What's more, some major clinical events, such as septic shock, disseminated intravascular coagulation (DIC), etc. during ICU stay were also monitored. A follow-up 28 days observation of prognosis was performed. The patients were divided into the septic shock group and the non-septic shock group according to the occurrence of septic shock, and they were divided into the survival group and the non-survival group according to the 28-day prognosis. The differences in terms of above parameters between each two groups were compared. Spearman correlation method was used to analyze the correlation between routine coagulation parameters and SOFA score or APACHEⅡ score. Receiver operator characteristic curve (ROC curve) was plotted to determine the predictive efficacy of each routine coagulation parameter with regarding to predict septic shock and 28-day mortality. Based on the cut-off value of PT, the septic patients were divided into two risk stratifications, and then the major clinical and end point outcome were compared. Kaplan-Meier survival curve analysis was applied to investigate the difference of the 28-day cumulated survival rate based on the different risk stratifications of PT level. Finally, multivariate Logistic regression analysis was used to explore whether prolonged PT level was an independent risk factor for septic shock and 28-day mortality.Results:The 302 patients were all enrolled, including 120 patients with septic shock and 182 patients without. Seventy-five patients died within 28 days, while 227 survived. Comparing with the non-septic shock group or the survival group, the septic shock group or the non-survival group patients both had longer PT, APTT and TT, higher D-dimer, FDP and lower PLT, FIB and AT. Correlation analysis revealed that PT and PLT were better correlated with SOFA score ( r values were 0.503 and -0.524, both P < 0.01), and PT was better correlated with APACHEⅡ score ( r = 0.407, P < 0.01). ROC curve analysis showed that PT had the most powerful predictive efficacy for septic shock and 28-day mortality. The area under the ROC curve (AUC) and 95% confidence interval (95% CI) were 0.831 (0.783-0.879) and 0.739 (0.674-0.805), respectively. The cut-off value were 16.8 s and 16.3 s, respectively, with the sensitivity of 64.2%, 72.0% and the specificity of 89.0%, 70.9%, respectively. Risk stratification based on PT level revealed that the patients with PT > 16.5 s ( n = 103) had higher rate of 28-day mortality, incidence of septic shock and DIC, and score of SOFA and APACHEⅡ comparing to those with PT ≤ 16.5 s ( n = 199). Kaplan-Meier survival curve analysis showed that the 28-day cumulative survival rate was significantly lower in the patients with PT > 16.5 s than those with PT ≤ 16.5 s (52.43% vs. 86.93%; Log-Rank test: χ 2 = 49.428, P < 0.001). Multivariate Logistic regression analysis revealed that PT > 16.5 s was an independent risk factor both for septic shock and 28-day mortality [model 1 (enrolled SOFA score): odds ratio ( OR) and 95% CI were 6.003 (3.040-11.855), 4.842 (2.114-11.089); model 2 (enrolled APACHEⅡ score): OR and 95% CI were 7.675 (4.007-14.702), 5.160 (2.258-11.793)]. Conclusions:Compared with other routine coagulation parameters, PT has the potential best predictive value for evaluating the severity of sepsis and the prognosis. When a patient is diagnosed with sepsis and has a result of PT longer than 16.5 s at ICU admission, the patient may have a higher risk of progression to septic shock and short-term death.
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Coronavirus disease 2019 (COVID-19), which is caused by SARS-CoV-2, varies with regard to symptoms and mortality rates among populations. Humoral immunity plays critical roles in SARS-CoV-2 infection and recovery from COVID-19. However, differences in immune responses and clinical features among COVID-19 patients remain largely unknown. Here, we report a database for COVID-19-specific IgG/IgM immune responses and clinical parameters (COVID-ONE humoral immune). COVID-ONE humoral immunity is based on a dataset that contains the IgG/IgM responses to 21 of 28 known SARS-CoV-2 proteins and 197 spike protein peptides against 2,360 COVID-19 samples collected from 783 patients. In addition, 96 clinical parameters for the 2,360 samples and information for the 783 patients are integrated into the database. Furthermore, COVID-ONE humoral immune provides a dashboard for defining samples and a one-click analysis pipeline for a single group or paired groups. A set of samples of interest is easily defined by adjusting the scale bars of a variety of parameters. After the "START" button is clicked, one can readily obtain a comprehensive analysis report for further interpretation. COVID-ONE-humoral immune is freely available at www.COVID-ONE.cn.
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Coronavirus disease 2019 (COVID-19), which is caused by SARS-CoV-2, varies with regard to symptoms and mortality rates among populations. Humoral immunity plays critical roles in SARS-CoV-2 infection and recovery from COVID-19. However, differences in immune responses and clinical features among COVID-19 patients remain largely unknown. Here, we report a database for COVID-19-specific IgG/IgM immune responses and clinical parameters (COVID-ONE humoral immune). COVID-ONE humoral immunity is based on a dataset that contains the IgG/IgM responses to 21 of 28 known SARS-CoV-2 proteins and 197 spike protein peptides against 2,360 COVID-19 samples collected from 783 patients. In addition, 96 clinical parameters for the 2,360 samples and information for the 783 patients are integrated into the database. Furthermore, COVID-ONE humoral immune provides a dashboard for defining samples and a one-click analysis pipeline for a single group or paired groups. A set of samples of interest is easily defined by adjusting the scale bars of a variety of parameters. After the "START" button is clicked, one can readily obtain a comprehensive analysis report for further interpretation. COVID-ONE-humoral immune is freely available at www.COVID-ONE.cn.
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Objective:To retrospectively analyze the clinical characteristics and drug resistance among COVID-19 patients with bacterial and fungal infections.Methods:Clinical data of COVID-19 patients whose blood, urine, sputum and alveolar lavage fluid samples were positive for bacteria and fungi were collected in Tongji Hospital from February 10 to March 31, 2020. WHONET5.6 software was used to analyze drug susceptibility test results.Results:A total of 95 COVID-19 patients positive for pathogenic bacteria were enrolled and among them, 23 were non-critical patients and 72 were critical patients. The main symptoms in these patients included fever, cough with sputum, fatigue and dyspnea. Male and female critical patients accounted for 63.89% and 36.11%, respectively. Most of the patients with bacterial and fungal infections were critical type, accounting for 23.61%. The mortality rates of non-critical and critical patients were 13.04% and 61.11%, respectively. A total of 179 strains of pathogenic bacteria were isolated. The positive rate of Escherichia coli in non-critical patients was 37.50%, which was higher than that in critical patients. However, the positive rates of Acinetobacter baumannii and Klebsiella pneumoniae in critical patients were both 29.87%, higher than those in non-critical patients. There was no significant difference in the positive rate of gram-positive bacteria or fungi between non-critical and critical patients. It was noteworthy that the positive rate of Candida parapsilosis in blood samples of critical patients was relatively high, reaching 36.40%. Drug susceptibility test results showed that no carbapenem-resistant Escherichia coli stains were detected and 60.87% of Klebsiella pneumoniae strains were resistant to carbapenems. Acinetobacter baumannii strains were 100% resistant to three antimicrobial drugs. Methicillin-resistant Staphylococcus aureus strains accounted for 71.43%, but no vancomycin-resistant gram-positive cocci were found. Conclusions:Critical COVID-19 patients were mostly male and prone to multiple bacterial and fungal infections. The mortality of critical patients was higher than that of non-critical patients. Critical COVID-19 was often complicated by hospital acquired infections caused by bacteria including Acinetobacter baumannii and Klebsiella pneumoniae with high drug resistance.
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The immunogenicity of SARS-CoV-2 proteome is largely unknown, especially for non-structural proteins and accessory proteins. Here we collected 2,360 COVID-19 sera and 601 control sera. We analyzed these sera on a protein microarray with 20 proteins of SARS-CoV-2, built an antibody response landscape for IgG and IgM. We found that non-structural proteins and accessory proteins NSP1, NSP7, NSP8, RdRp, ORF3b and ORF9b elicit prevalent IgG responses. The IgG patterns and dynamic of non-structural/ accessory proteins are different from that of S and N protein. The IgG responses against these 6 proteins are associated with disease severity and clinical outcome and declined sharply about 20 days after symptom onset. In non-survivors, sharp decrease of IgG antibodies against S1 and N protein before death was observed. The global antibody responses to non-structural/ accessory proteins revealed here may facilitate deeper understanding of SARS-CoV-2 immunology. HighlightsO_LIAn antibody response landscape against SARS-CoV-2 proteome was constructed C_LIO_LINon-structural/accessory proteins elicit prevalent antibody responses but likely through a different mechanism to that of structural proteins C_LIO_LIIgG antibodies against non-structural/accessory proteins are more associated with disease severity and clinical outcome C_LIO_LIFor non-survivors, the levels of IgG antibodies against S1 and N decline significantly before death C_LI
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The COVID-19 global pandemic is far from ending. There is an urgent need to identify applicable biomarkers for early predicting the outcome of COVID-19. Growing evidences have revealed that SARS-CoV-2 specific antibodies evolved with disease progression and severity in COIVD-19 patients. We assumed that antibodies may serve as biomarkers for predicting disease outcome. By taking advantage of a newly developed SARS-CoV-2 proteome microarray, we surveyed IgG responses against 20 proteins of SARS-CoV-2 in 1,034 hospitalized COVID-19 patients on admission and followed till 66 days. The microarray results were further correlated with clinical information, laboratory test results and patient outcomes. Cox proportional hazards model was used to explore the association between SARS-CoV-2 specific antibodies and COVID-19 mortality. We found that nonsurvivors induced higher levels of IgG responses against most of non-structural proteins than survivors on admission. In particular, the magnitude of IgG antibodies against 8 non-structural proteins (NSP1, NSP4, NSP7, NSP8, NSP9, NSP10, RdRp, and NSP14) and 2 accessory proteins (ORF3b and ORF9b) possessed significant predictive power for patient death, even after further adjustments for demographics, comorbidities, and common laboratory biomarkers for disease severity (all with p trend < 0.05). Additionally, IgG responses to all of these 10 non-structural/accessory proteins were also associated with the severity of disease, and differential kinetics and serum positive rate of these IgG responses were confirmed in COVID-19 patients of varying severities within 20 days after symptoms onset. The AUCs for these IgG responses, determined by computational cross-validations, were between 0.62 and 0.71. Our findings have important implications for improving clinical management, and especially for developing medical interventions and vaccines.
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System-wide molecular characteristics of COVID-19, especially in those patients without comorbidities, have not been fully investigated. We compared extensive molecular profiles of blood samples from 231 COVID-19 patients, ranging from asymptomatic to critically ill, importantly excluding those with any comorbidities. Amongst the major findings, asymptomatic patients were characterized by highly activated anti-virus interferon, T/natural killer (NK) cell activation, and transcriptional upregulation of inflammatory cytokine mRNAs. However, given very abundant RNA binding proteins (RBPs), these cytokine mRNAs could be effectively destabilized hence preserving normal cytokine levels. In contrast, in critically ill patients, cytokine storm due to RBPs inhibition and tryptophan metabolites accumulation contributed to T/NK cell dysfunction. A machine-learning model was constructed which accurately stratified the COVID-19 severities based on their multi-omics features. Overall, our analysis provides insights into COVID-19 pathogenesis and identifies targets for intervening in treatment.
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Neutralization antibodies and vaccines for treating COVID-19 are desperately needed. For precise development of antibodies and vaccines, the key is to understand which part of SARS-CoV-2 Spike protein is highly immunogenic on a systematic way. We generate a linear epitope landscape of Spike protein by analyzing serum IgG response of 1,051 COVID-19 patients with a peptide microarray. We reveal two regions that rich of linear epitopes, i.e., CTD and a region close to the S2 cleavage site and fusion peptide. Unexpectedly, we find RBD is lack of linear epitope. Besides 3 moderate immunogenic peptides from RBD, 16 highly immunogenic peptides from other regions of Spike protein are determined. These peptides could serve as the base for precise development of antibodies and vaccines for COVID-19 on a systematic level. One sentence summaryA linear epitope landscape of SARS-CoV-2 Spike protein is generated by analyzing serum IgG response of 1,051 COVID-19 patients.
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ImportanceAsymptomatic COVID-19 infections have a long duration of viral shedding and contribute substantially to disease transmission. However, the missing asymptomatic cases have been significantly overlooked because of imperfect sensitivity of nucleic acid testing. We aimed to investigate the humoral immunity in asymptomatics, which will help us develop serological tests and improve early identification, understand the humoral immunity to COVID-19, and provide more rational control strategies for the pandemic. ObjectiveTo better control the pandemic of COVID-19, dynamics of IgM and IgG responses to 23 proteins of SARS-CoV-2 and neutralizing antibody in asymptomatic COVID-19 infections after exposure time were investigated. Design, setting, and participants63 asymptomatic individuals were screened by RT-qPCR and ELISA for IgM and IgG from 11,776 personnel returning to work, and close contacts with the confirmed cases in different communities of Wuhan by investigation of clusters and tracing infectious sources. 63 healthy contacts with both negative results for NAT and antibodies were selected as negative controls. 51 mild patients without any preexisting conditions were also screened as controls from 1056 patients during hospitalization in Tongji Hospital. A total of 177 participants were enrolled in this study and serial serum samples (n=213) were collected. The research was conducted between 17 February 2020 and 28 April 2020. Serum IgM and IgG profiles of 177 participants were further probed using a SARS-CoV-2 proteome microarray. Neutralizing antibody responses in different population were detected by a pseudotyped virus neutralization assay system. The dynamics of IgM and IgG antibodies and neutralizing antibodies were analyzed with exposure time or symptoms onset. ResultsAsymptomatics were classified into four subgroups based on NAT and serological tests. In particular, only 19% had positive NAT results while approximately 81% detected positive IgM/IgG responses. Comparative SARS-CoV-2 proteome microarray further demonstrated that there was a significantly difference of antibody dynamics responding to S1 or N proteins among three populations, although IgM and IgG profiles could not be used to differentiate them. S1 specific IgM responses were elicited in asymptomatic individuals as early to the seventh day after exposure and peaked on days from 17d to 25d, which might be used as an early diagnostic biomarker and give an additional 36.5% seropositivity. Mild patients produced stronger both S1 specific IgM and neutralizing antibody responses than asymptomatic individuals. Most importantly, S1 specific IgM/IgG responses and the titers of neutralizing antibody in asymptomatic individuals gradually vanished in two months. Conclusions and relevanceOur findings might have important implications for the definition of asymptomatic COVID-19 infections, diagnosis, serological survey, public health and immunization strategies.
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Objective:To monitor the susceptibility of common used antimicrobial agents against nosocomial Gram-negative bacilli in 2018 across China.Methods:Prospective collection of Gram-negative bacilli from 13 teaching hospitals nationwide from January to December 2018. The minimal inhibitory concentration (MICs) of antibiotics such as meropenem was determined by agar dilution methods and broth microdilution methods. Interpretation of results using the Clinical and Laboratory Standards Institute(CLSI) 2019 M100S (29th Edition) standard. Data were analyzed by using WHONET-5.6 software.Results:A total of 1 214 non-repetitive Gram-negative bacilli were collected, accounting for 96.7% (1 174/1 214) of blood and sterile body fluid samples. The activity of antimicrobial agents against 871 strains of Enterobacteriaceae was as follows in descending order of susceptible rate: amikacin (93.2%, 812/871), meropenem (92.0%, 801/871), ertapenem (88.9%, 774/871), imipenem (88.4%, 770/871), piperacillin-tazobactam (84.0%, 732/871), cefoperazone-sulbactam (83.1%, 724/871), cefepime (71.4%, 622/871), minocyline (68.9%, 600/871), ceftazidime (66.9%, 583/871), levofloxacin (54.4%, 474/871).The resistance rates of Escherichia coli to the third generation cephalosporins were 61.5% (155/252) (ceftriaxone) and 60.7% (153/252) (cefotaxime), respectively. The resistance rates of Klebsiella pneumoniae to the third generation cephalosporins were 56.6% (126/222) (ceftriaxone) and 57.9% (129/222) (cefotaxime), respectively. The incidence of extended-spectrum β lactamase (ESBLs) positive E. coli and K. pneumoniae was 50.2% (127/252) and 18.2% (40/222), respectively. Over 95% of all the ESBLs positive strains were susceptible to imipenem and meropenem. The incidence of carbapenem-resistant Escherichia coli and Klebsiella pneumoniae was 2.8% (7/252) and 20.4% (45/222), respectively. For Enterobacter cloacae, Klebsiella aerogenes, Citrobacter freundii, the most susceptible agent were tigecycline (96.3%-100%), followed by amikacin (94.9%-97.1%), meropenem (89.8%-96.6%)and imipenem (89.8%-94.9%).The susceptibility of Proteus mirabilis, Morganella morganii and Serratia marcescens to meropenem and amikacin was over 90%.A total of 67 strains of carbapenems resistant enterobacteriaceae(CRE) were detected. Modified carbapenem inactivation method showed, 45 strains were serine carbapenemase and 20 were metalloenzymes. The susceptibility of Pseudomonas aeruginosa to meropenem and imipenem were 73.2% (112/153) and 66.0% (101/153), respectively. Acinobacter baumannii has the highest sensitivity to colistin (100%, 163/163), followed by tigecycline (87.1%, 142/163).Compared with other sources of infection, specimens of bloodstream infections were less resistant to Klebsiella pneumoniae (17.6%, 27/153 vs 21.7%, 15/69) and Acinetobacter baumannii (68.3%, 71/104 vs 71.2%, 42/59). Escherichia coli (2.5%,4/198 vs 0%,0/54) and Pseudomonas aeruginosa (37%, 33/89 vs 18.8%, 12/64) have a high proportion of carbapenem resistance. Conclusions:Carbapenems still maintain high antibacterial activity against Enterobacteriaceae bacteria, especially strains producing only ESBLs. Carbapenem-resistant Klebsiella pneumoniae should be given sufficient attention. Carbapenemase is the most important drug resistance mechanism of carbapenem-resistant Enterobacteriaceae in China.
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Objective To investigatethe relationship between urinary catecholamine levels and type Ⅱ diabetic nephropathy and neuropathy. Methods Allsubjects were collected fromTongji Hospital, Tongji Medical College, Huazhong University of Science and Technology,and were divided into two groups:type Ⅱ diabetic patients (For 24 h urine, n=130, aged 27-81 years old, 75 men, 55 female; for random urine, n=115, aged 27-77 years old, 75 men, 40 female) and healthy control (For 24 h urine, n=118, aged 27-76 years old, 67 men, 51 female; for random urine, n=93, aged 25-74 years old, 57 men, 36 female).Based on the results of urinary albumin excretion, type Ⅱ diabetic patients were prospectively divided into two independent groups: patients with nephropathy (For 24 h urine, n=37; for random urine, n=32) and patients without nephropathy (For 24 h urine, n=32; for random urine, n=35). According to questionnaires, quantitative sensory testing and autonomic function test, type Ⅱ diabetic patients were divided into two different groups: patients with neuropathy (For 24 h urine, n=31; for random urine, n=23) and patients without neuropathy (For 24 h urine, n=30; for random urine, n=35). Urinary catecholamines(CAs) levels, including epinephrine (E), norepinephrine (NE), dopamine (DA) and total catecholamines (total CAs) levels, were measured using liquid chromatography tandem mass spectrometry (LC-MS / MS). The CAs levels in different groups have been discussed. The results were analyzed using χ2 test, independent t test and Mann-Whitney non-parametric test. Results Type Ⅱ diabetic patients with nephropathy show lower E (0.74±0.24) μg/24 h,NE(9.22±4.02) μg/24 h,DA(64.77±21.68) μg/24 h and total CAs(74.72±25.65) μg/24 h in 24-hour urine in comparison with the group without nephropathy(For E, 4.23±0.50 μg/24 h, U=10, P<0.001; for NE, (32.31±1.74) μg/24 h, t=-2.72, P=0.011; for DA, (219.58±27.51) μg/24 h, t=-2.88, P=0.007;fro CAs, (256.02±30.65) μg/24 h, t=-3.02, P=0.005) and the differences were statistically significant (P<0.05). The differences of NE, DA and total CAs between type Ⅱ diabetic patients with nephropathyand without nephropathy were statistically significant in random urine(P<0.05). Conclusion These results suggested that urine CAs levels in diabetic patients with nephropathy is lower than that in patients without nephropathy, which may be related to the occurrence and development of diabetic nephropathy.
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Objective To learn the distribution, epidemiology and antimicrobial susceptibility of diarrheagenic Escherichia coli (DEC) isolated from patients with acute diarrhea among children less than 5 years old. Methods Totally 684 stool samples collected from Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology between August 1, 2015 and September 30, 2016 were tested by culture and identified the common pathogens. PCR was applied to detect the virulence genes of DEC. Meanwhile, serotyping of enteropathogenic E. coli (EPEC) was performed by slide agglutination tests for all the isolates of EPEC. An antimicrobial sensitivity test was performed using the agar dilution method. Results A total of 149 (21.7%) enteric bacteria pathogens were isolated from 684 specimens. DEC was found in 54 cases, ranked 2nd among the pathogenic bacteria. DEC tended to occur in summer/autumn periods. EPEC was the most frequent DEC genotype, accounted for 50% (27/54). Among EPEC, atypical EPEC was dominant, accounted for 77.8% (21/27) and typical EPEC only accounted for 22.2% (6/27). Followed by enteroaggregative E. coli 20.4%(11/54), enterotoxigenic E. coli 14.8%(8/54), enteroinvasive E. coli and Shiga toxin-producing E. coli 3.7%(2/54), 7.4%(4/54) cases were co-infected with more than one DEC genotypes. About 17/18 of suspicious DEC isolates can get the same genotypes by commercial multiplex PCR kit and single PCR test. Among the 27 EPEC strains, only 11(40.7%) strains can be detected by the slide agglutination serotyping method. More than 50% (27/54) of DEC isolates were resistant to conventional first-line antibiotics (ampicillin, trimethoprim-sulfamethoxazole) and cefazolin, cefuroxime, cefotaxime, but relatively low resistance to cefoxitin, amikacin, piperacillin/tazobactam, imipenem and meropenem. However, there was still a 9.2% (5/54) resistance rate to carbapenems. Conclusions DEC strains exhibited a high frequency of resistance to many antibiotics. Empirical antimicrobial therapy of severe DEC infection faces the challenge from the high resistance to ampicillin, trimethoprim-sulfamethoxazole. Even worse, some strains were resistant to relatively efficient drugs imipenem and meropenem. It is necessary to strengthen the epidemiological survey and antimicrobial resistance of DEC.
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Objective To investigate the antimicrobial resistance profile of the clinical isolates collected from selected hospitals across China. Methods Twenty-nine general hospitals and five children's hospitals were involved in this program. Antimicrobial susceptibility testing was carried out according to a unified protocol using Kirby-Bauer method or automated systems. Results were interpreted according to CLSI 2017 breakpoints. Results A total of 190 610 clinical isolates were collected from January to December 2017, of which gram negative organisms accounted for 70.8% (134 951/190 610) and gram positive cocci 29.2% (55 649/190 610). The prevalence of methicillin-resistant strains was 35.3% in S. aureus (MRSA) and 80.3% in coagulase negative Staphylococcus (MRCNS) on average. MR strains showed much higher resistance rates to most of the other antimicrobial agents than MS strains. However, 91.6% of MRSA strains were still susceptible to trimethoprim-sulfamethoxazole, while 86.2% of MRCNS strains were susceptible to rifampin. No staphylococcal strains were found resistant to vancomycin. E. faecalis strains showed much lower resistance rates to most of the drugs tested (except chloramphenicol) than E. faecium. Vancomycin-resistant Enterococcus (VRE) was identified in both E. faecalis and E. faecium. The identified VRE strains were mainly vanA, vanB or vanM type based on phenotype or genotype. The proportion of PSSP or PRSP strains in the non-meningitis S.pneumoniae strains isolated from children decreased but the proportion of PISP strains increased when compared to the data of 2016. Enterobacteriaceae strains were still highly susceptible to carbapenems. Overall, less than 10% of these strains (excluding Klebsiella spp.) were resistant to carbapenems. The prevalence of imipenem-resistant K. pneumoniae increased from 3.0% in 2005 to 20.9% in 2017, and meropenem-resistant K. pneumoniae increased from 2.9% in 2005 to 24.0% in 2017, more than 8-fold increase. About 66.7% and 69.3% of Acinetobacter (A. baumannii accounts for 91.5%) strains were resistant to imipenem and meropenem, respectively. Compared with the data of year 2016, P. aeruginosa strains showed decreasing resistance rate to carbapenems. Conclusions Bacterial resistance is still on the rise. It is necessary to strengthen hospital infection control and stewardship of antimicrobial agents. The communication between laboratorians and clinicians should be further improved in addition to surveillance of bacterial resistance.
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Objective To investigate antimicrobial resistance among nosocomial gram-negative bacilli in 2016 across China.Methods About 1 394 consecutive and non-repetitive gram-negative bacilli were isolated from 14 teaching hospitals from March to August in 2016 across China.All of these isolates were sent to the central laboratory for reidentification and susceptibility testing.The minimal inhibitory concentration(MICs)of meropenem and other antibacterial agents were determined by agar dilution method.The data were analyzed by using WHONET-5.6 software.Results The activity of antimicrobial agents against Enterobacteriaceae was as follows in descending order of susceptible rate: meropenem (95.2%,891/936), amikacin (94.6%,885/936), ertapenem (92.1%,862/936), piperacillin/tazobactam (88.1%,825/936), imipenem (88.0%,823/936), cefoperazone-sulbactam (83.1%,778/936), cefepime (72.2%,676/936), cefiazidime (72.2%,676/936), levofloxacin(68.8%,644/936), ciprofloxacin (63.2%,592/936), minocyline (62.9%,589/936), cefiriaxone (54.9%,514/936), cefotaxime (54.0%,505/936), cefoxitin (44.3%,415/936).The sensitivities of E.coli to carbapenems, amikacin, piperacillin-tazobactam, polymyxin B and cefoperazone-sulbactam were over 80%.The more sensitive antibiotic to Klebsiella pneumoniae was polymyxin B (99.0%), followed by amikacin (84.9%), meropenem (84.4%) and imipenem (82.0%).The prevalence of extended-spectrum β-lactamase was 62.8%(137/218)in Escherichia coli and 28.3%(58/205)in Klebsiella pneumonia.The activity of antimicrobial agents against E.cloacae, E.aerogenes and Citrobacter freundii was as follows in descending order of susceptible rate: meropenem (97.0%-98.5%), amikacin (95.8%-98.3%), imipenem (94.5%-97.5%), polymyxin B (96.4%-100%), cefoperazone-sulbactam (76.5%-90.0%), ertapenem (73.3%-90.1%), piperacillin/tazobactam (82.4%-88.3%).The most active agents against Pseudomonas aeruginosa were polymyxinB (100%), followed by amikacin (89.3%) and ciprofloxacin (82.4%).The most active agents against Acinetobacter baumannii were polymyxinB (100%).The sensitivities of Acinetobacter baumannii to meropenem, imipenem, minocycline and cefoperazone-sulbactam were 20.3%(39/202), 19.3%(41/202), 66.3%(134/202) and 24.8%(50/202), respectively.Conclusions Carbapenems remain high sensitive against Enterobacteriaceae.Controlling carbapenem resistant Klebsiella pneumoniae is urgent.Drug antimicrobial resistance in A.baumanni is a still serious problem.
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Objective To investigate the incidence of prozone phenomenon of rapid plasma reagin (RPR) test in syphilis serolog-ic testing and its correlation with the intensity of chemiluminescent microparticle immunoassay (CMIA) results.Methods A total of 101493 patients in our hospital from January 2014 to December 2015 were performed syphilis serologic testing by CMIA ,RPR and treponema pallidum particle agglutination (TPPA).The incidence rate of prozone phenomenon in RPR testing was evaluated.Its in-fluencing factors were investigated by using the Logistic regression.Results Among 101493 serum samples ,2180 cases were posi-tive by CMIA and 767 cases were positive by RPR ,the incidence rate of prozone phenomenon was 3.3% (26/767)in RPR.The Lo-gistic regression results indicated that the incidence of prozone phenomenon was significantly correlated with CMIA S /CO values and RPR titer ,but had no correlation with sex ,age and seasonality.Conclusion Although the incidence of prozone phenomenon is low in syphilis serologic testing ,but it is enough important.The patients with higher S/CO value in CMIA test have a higher inci-dence rate of RPR prozone phenomenon.
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Objective To explore the distribution and antimicrobial resistance of pathogens causing lower respiratory tract infection in patients, and provide basis for rational choice of antimicrobial agents in clinic.Methods All bronchoalveolar lavage fluid specimens in a hospital from January 1, 2013 to December 31, 2014 were performed culture, antimicrobial susceptibility testing of isolated strains was performed with Kirby-Bauer method.Results A total of 999 strains were isolated from 7 702 bronchoalveolar lavage fluid specimens, 398 (5.17%), 326 (4.23%), and 275(3.57%) strains were bacteria, fungus, and Mycobacterium respectively.The main bacteria were Pseudomonas aeruginosa(P.aeruginosa, n=97), Acinetobacter baumannii(A.baumannii, n=87), Klebsiella pneumoniae(K.pneumoniae, n=62), Staphylococcus aureus(S.aureus, n=44), and Haemophilus influenzae (n=28);the main fungi were Candida albicans (n=161), Aspergillus fumigatus (n=41), and Aspergillus flavus(n=38);the main Mycobacterium were Mycobacterium tuberculosis(n=271).Antimicrobial susceptibility testing results showed that resistance rates of P.aeruginosa to the commonly used antimicrobial agents (except ticarcillin/clavulanic acid and levofloxacin) were all80.00%, but to the other commonly used antimicrobial agents were 36.84%-60.53%.Among 62 strains of K.pneumoniae, 20 were extended-spectrum β-lactamases(ESBLs)-producing strains.Antimicrobial resistance rates of ESBLs-producing strains were obviously higher than non-ESBLs-producing strains.Among 44 S.aureus strains, 26 were methicillin-resistant S.aureus (MRSA), resistance rate of S.aureus to penicillin was 97.73%, to vancomycin, teicoplanin, and linezolid were all 0, to the other antimicrobial agents were 9.09%-61.36%.Conclusion Bacteria is the major pathogen causing lower respiratory tract infection in hospitalized patients, but fungus and Mycobacterium can not be ignored.Resistance rates of P.aeruginosa to commonly used antimicrobial agents is relatively low, but resistance of A.baumannii is more serious.
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Objective To analyze the resistance proifle of bacterial strains isolated from geriatric patients in 17 hospitals across China from 2005 to 2014.Methods A total of 17 representative general hospitals were involved in this program. Bacterial susceptibility testing was carried out by means of a uniifed protocol using Kirby-Bauer method and MIC determination. The results were analyzed according to CLSI 2014 breakpoints.Results The proportion of the strains isolated from geriatric patients among all the clinical isolates increased with time from 30.0% in 2005 to 32.7% in 2014. A total of 159 888 clinical isolates were collected from geriatric patient during the period from 2005 to 2014, about 33.1% of the whole patient population. Gram negative organisms and gram positive cocci accounted for 77.1% (123 229/159 888) and 22.9% (36 659/159 888), respectively. Majority (92.8%, 148 376/159 888) of the isolates were from inpatients and more than half (55.2%, 88 201/159 888) of the isolates were from sputum or other respiratory tract specimens. Methicillin-resistant strains inS. aureus (MRSA) and coagulase negativeStaphylococcus (MRCNS) accounted for an average of 67.1% and 75.9%, respectively. The resistance rates of methicillin-resistant strains to β-lactams and other antimicrobial agents were much higher than those of methicillin-susceptible strains. No staphylococcal strains were found resistant to vancomycin, teicoplanin or linezolid. Some strains ofE. faecalis (0.4%) andE. faecium (4.6%) were resistant to vancomycin, which was higher than average national level (0.3%, 3.2%). Vancomycin-resistant strains ofE. faecalisandE. faecium were mainly VanA type and VanB type based on their phenotype. The prevalence of penicillin-susceptibleS. pneumoniae strains was 78.2%, slightly lower than the 95.0% in Chinese adults in year 2014. The prevalence of ESBLs-producing strains was 67.5% inE. coli, 40.4% inKlebsiella (K. pneumoniae andK. oxytoca) and 34.3% inProteus mirabilis isolates on average. The strains ofEnterobacteriaceae were still highly susceptible to carbapenems (<10% resistant), followed by amikacin and the beta-lactam and beta-lactamase inhibitor combinations. Overall, 35.9% and 33.0% of theP. aeruginosa strains were resistant to imipenem and meropenem. More than 50% of theA. baumannii strains were resistant to imipenem and meropenem. The prevalence of extensively drug-resistant (XDR)P. aeruginosa (4.0%-1.8%) was higher than the average national level (2.1%-1.6%). The prevalence of XDR A. baumannii (19.2%-15.5%) and XDREnterobacteriaceae (0.1%-1.0%) was lower than the average national level (21.4%-19.7% and 0.3%-3.2%).Conclusions The proportion of clinical isolates from geriatric patients is different from average national level at the same period. The isolates from geriatric patients are more likely from inpatients, respiratory tract specimens and more likely non-fermentative gram-negative bacilli compared to average national level. The proportion of fastidious bacteria andEnterobacteriaceae species is generally lower than average national level. MRSA, VRE, ESBLs-producing strains and XDRP. aeruginosa are more prevalent in geriatric patients than in general Chinese patient population. This study suggests that surveillance of antimicrobial resistance for the clinical isolates from geriatric patients is very important for rational antimicrobial therapy.