[Study on the etiological characteristics and prevention and control of adult community-acquired pneumonia in hospitalized patients in a hospital in Beijing from 2015 to 2019].

Objective: To explore the distribution characteristics of pathogens in adult patients with community-acquired pneumonia (CAP) and to provide basis for the diagnosis, treatment, prevention of CAP. Methods: 1 446 inpatients with CAP were prospectively enrolled in a third-class hospital in Beijing in recent 5 years (from January 2015 to December 2019). Respiratory tract samples were collected for smear, culture, nucleic acid, antigen and antibody detection to identify the pathogen of CAP. Mann-Whitney U test was used for continuous variables and χ2 test or Fisher's exact test was used for categorical data for statistical analysis. Results: Among the 1 446 patients, 822 (56.85%) patients were infected with a single pathogen, 231 (15.98%) patients were infected with multiple pathogens, and 393 (27.18%) patients were not clear about the pathogen. Influenza virus is the first pathogen of CAP (20.95%, 303/1 446), mainly H1N1 (8.51%, 123/1 446), followed by mycoplasma pneumoniae (7.19%, 104/1 446), Mycobacterium tuberculosis (5.33%, 77/1 446) and Streptococcus pneumoniae (5.05%, 73/1 446). The outbreak of H1N1 occurred from December 2018 to February 2019, and the epidemic of mycoplasma pneumoniae pneumonia was monitored from August to November 2019. Patients under 65 years old had high detection rates of Mycoplasma pneumoniae (14.41% vs. 2.41%, χ²=74.712,P<0.001), Streptococcus pneumoniae (8.16% vs. 2.99%, χ²=18.156, P<0.001), rhinovirus (6.08% vs. 3.56%, χ²=5.025, P<0.025), Chlamydia pneumoniae (5.90% vs. 1.15%, χ²=26.542, P<0.001) and adenovirus (3.13% vs. 0.92%, χ²=9.547, P=0.002). The severe disease rate of CAP was 14.66% (212/1 446), and the average mortality rate was 3.66% (53/1 446). The severe illness rate and mortality rate of bacterial-viral co-infection were 28.97% (31/107) and 19.63% (21/107), respectively. Conclusions: Influenza virus is the primary pathogen of adult CAP. Outbreaks of Mycoplasma pneumoniae and H1N1 were detected in 2018 and 2019, respectively. The remission rate and mortality rate of virus-bacteria co-infection were significantly higher than those of single pathogen infection. Accurate etiological basis not only plays a role in clinical diagnosis and treatment, but also provides important data support for prevention and early warning.

[Clinical application value of γ-IFN release assay combined with CA-125 in diagnosis of active pulmonary tuberculosis].

Objective: To evaluate the diagnosis of interferon gamma release assay (IGRA) combined with tumor marker carbohydrate antigen-125 (CA-125) in active pulmonary tuberculosis (PTB). Methods: One hundred and three patients with active PTB (48 definite and 55 clinical diagnosed), 646 patients with non-PTB pulmonary disease and 60 normal controls hospitalized in Beijing Tongren Hospital, Capital Medical University between January 2014 and December 2016 were retrospectively investigated. Blood samples were collected to determine the IGRA and CA-125 level by enzyme-linked immunosorbent assay and electrochemiluminescence, respectively. The CA-125 level of patients with active PTB, non-PTB pulmonary disease and normal controls were compared. Subsequently, the best cut-off value of CA-125 for diagnosing PTB was calculated based on 60 active PTB cases and 60 normal controls. Methodological evaluation of IGRA, CA-125 and combination of these two tests (both positive) for active PTB diagnosing were performed based on 43 active PTB cases and all the non-PTB pulmonary disease cases. Results: The median values of CA-125 among definite and clinical diagnosis groups of active PTB were 55.00 (25.35, 156.90) U/ml and 81.50 (39.40, 138.00) U/ml, respectively. There was no difference between the two groups (U=1 093.00, P>0.05). And the CA-125 level of male and female PTB patients were also undifferentiated (U=1 124.00, P>0.05). There were statistically significant differences in CA-125 levels between the active PTB group and all other non-PTB groups (all P<0.001), including those who had ever closely contacted with TB patients. The area under the ROC curve constructed by CA-125 for diagnosing active PTB was 0.933. And the best cut-off value of CA-125 was 22.00 U/ml. Based on this cut-off value, the accuracy, sensitivity and specificity of CA-125 for diagnosing active PTB were 70.5% (486/689), 86.0% (37/43) and 69.5% (449/646). The accuracy, sensitivity and specificity of IGRA for diagnosing active PTB were 73.3% (480/689), 90.7% (39/43) and 68.3%(441/64). The accuracy, sensitivity and specificity of IGRA combined with CA-125 for diagnosing active PTB were 90.6% (624/689), 76.7% (33/43), 91.5% (591/646). Both of the accuracy and the false positive ratio of this combinational method (8.5%, 55/646) were significantly lower than two indexes individually used (χ(2)=94.461, 88.261, P<0.001). However, the false negative ratio was increased to 23.3% (10/43) by combinational method. Conclusion: IGRA combined with CA-125 has a certain clinical value in diagnosis of active PTB, especially when the evidences of bacterial is not available.

[Analysis of the protein expression differences between colonized and infectious multidrug-resistant acinetobacter baumannii].

Objective: To analyze the protein expression differences between colonized multidrug-resistant acinetobacter baumannii (MDR-AB) and infectious MDR-AB using comparative proteomics and matrix assisted laser desorption ionization time of flight mass spectrometry (MALDI-TOF MS) and to explore the molecular characteristics of MDR-AB infections. Methods: A total of 59 MDR-AB strains including 23 of bloodstream infections MDR-AB and 36 of nasal, pharyngeal or environmental colonization MDR-AB were collected from Beijing Tongren Hospital between January 2008 and December 2011. MALDI-TOF MS cluster analysis was applied to identify the differences of protein expression between infection strains and colonization strains (including patient colonization and environmental colonization) of MDR-AB. Two-dimensional protein differences electrophoresis and MALDI-TOF-TOF MS were used to analyze the protein expression differences between bloodstream infection strain and nasal colonization strain isolated from the same patient. Results: ST92 was the main multiple locus sequence typing of 23 bloodstream infections MDR-AB. Cluster analysis showed that there were differences of protein fingerprint of MADLI-TOF MS between colonized and infectious MDR-AB. Proteomic differences were found between colonization strain and infection strain which were isolated from the same patient. And 9 major different protein spots were identified. They were trigger factor (score of identification was 10 218 and coverage rate was 44%), inosine-5'-monophosphate dehydrogenase (score of identification was 1 919 and coverage rate was 60%), phosphoglycerate kinase (score of identification was 947 and coverage rate was 49%), outer membrane protein 38 (score of identification was 572 and coverage rate was 23%) and so on. Conclusion: There were differences of protein expression between MDR-AB infection strains and colonization strains. And such different proteins could provide experimental evidence for molecular markers research of MDR-AB infections.

Direct identification of bacteria causing urinary tract infections by combining matrix-assisted laser desorption ionization-time of flight mass spectrometry with UF-1000i urine flow cytometry.

Rapid identification of bacterial pathogens from clinical specimens is essential to establish an adequate empirical antibiotic therapy to treat urinary tract infections (UTIs). We used matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) combined with UF-1000i urine flow cytometry of urine specimens to quickly and accurately identify bacteria causing UTIs. We divided each urine sample into three aliquots for conventional identification, UF-1000i, and MALDI-TOF MS, respectively. We compared the results of the conventional method with those of MALDI-TOF MS combined with UF-1000i, and discrepancies were resolved by 16S rRNA gene sequencing. We analyzed 1456 urine samples from patients with UTI symptoms, and 932 (64.0%) were negative using each of the three testing methods. The combined method used UF-1000i to eliminate negative specimens and then MALDI-TOF MS to identify the remaining positive samples. The combined method was consistent with the conventional method in 1373 of 1456 cases (94.3%), and gave the correct result in 1381 of 1456 cases (94.8%). Therefore, the combined method described here can directly provide a rapid, accurate, definitive bacterial identification for the vast majority of urine samples, though the MALDI-TOF MS software analysis capabilities should be improved, with regard to mixed bacterial infection.