ObjectiveTo investigate the distribution of bacteria detected from blood culture of pediatric patients and to observe the blood culture contamination rate. MethodsA total of 6 530 blood samples, collected from January 2011 to December 2012 were detected by BacT/Alert 3D automated blood culture system. We found out the contamination bacteria according to clinical data, laboratory data and microbiology knowledge. ResultsA total of 314 bacteria strains were isolated from 6 530 blood samples, and the positive rate was 4.8%, 228 of which were gram-positive bacteria. The isolates were mainly coagulase-negative staphylococci (43.9%), followed by Staphylococcus aureus (2.9%). In addition, 86 cases were gram-negative bacteria, the majority of which were Escherichia coli (9.6%), followed by Klebsiella pneumonia (8.3%). The overall blood culture contamination rate was 49.7% (156 bacteria were identified). The top two were coagulase-negative staphylococci (31.2%), followed by Bacillus sp. (6.4%). ConclusionThe contamination rate is high in children's blood culture, and coagulase-negative staphylococci are the main bacteria. It's necessary to use clinical data and laboratory data to determine its clinical significance, and avoid unnecessary use of antibiotics.
Objective To evaluate the basic performance and clinical application value of nanopore sequencing, in order to provide new ideas for the rapid detection of clinical etiology. Methods From December 2021 to May 2022, blood samples from inpatients suspected of bloodstream infection in Renmin Hospital of Wuhan University were collected, and the nanopore sequencing platform and blood culture method were used to simultaneously identify the pathogenic bacteria in the blood samples of the selected patients, and identify the pathogenic bacteria in the blood samples of the selected patients. The basic performance and clinical utility of nanopore sequencing were evaluated. Results A total of 251 patients were included, and 119 patients (47.4%) were found to have pathogens by nanopore sequencing, which was higher than that of 23 patients (9.2%) by blood culture (χ2=79.167, P<0.001). The results of the two methods are not consistent (kappa=0.052, P=0.175). Nanopore sequencing has a certain missed detection rate. In terms of the types of pathogenic bacteria detected, 47 bacteria and 15 fungi were detected by nanopore sequencing. Conclusion Compared with blood culture, nanopore sequencing has a higher detection rate and more types of pathogens. This technology has obvious advantages in the rapid diagnosis of bloodstream infection pathogens.
ObjectiveTo analyze the prognostic factors of patients with bacterial bloodstream infection sepsis and to identify independent risk factors related to death, so as to potentially develop one predictive model for clinical practice. Method A non-intervention retrospective study was carried out. The relative data of adult sepsis patients with positive bacterial blood culture (including central venous catheter tip culture) within 48 hours after admission were collected from the electronic medical database of the First Affiliated Hospital of Dalian Medical University from January 1, 2018 to December 31, 2019, including demographic characters, vital signs, laboratory data, etc. The patients were divided into a survival group and a death group according to in-hospital outcome. The risk factors were analyzed and the prediction model was established by means of multi-factor logistics regression. The discriminatory ability of the model was shown by area under the receiver operating characteristic curve (AUC). The visualization of the predictive model was drawn by nomogram and the model was also verified by internal validation methods with R language. Results A total of 1189 patients were retrieved, and 563 qualified patients were included in the study, including 398 in the survival group and 165 in the death group. Except gender and pathogen type, other indicators yielded statistical differences in single factor comparison between the survival group and the death group. Independent risk factors included in the logistic regression prediction model were: age [P=0.000, 95% confidence interval (CI) 0.949 - 0.982], heart rate (P=0.000, 95%CI 0.966 - 0.987), platelet count (P=0.009, 95%CI 1.001 - 1.006), fibrinogen (P=0.036, 95%CI 1.010 - 1.325), serum potassium ion (P=0.005, 95%CI 0.426 - 0.861), serum chloride ion (P=0.054, 95%CI 0.939 - 1.001), aspartate aminotransferase (P=0.03, 95%CI 0.996 - 1.000), serum globulin (P=0.025, 95%CI 1.006 - 1.086), and mean arterial pressure (P=0.250, 95%CI 0.995 - 1.021). The AUC of the prediction model was 0.779 (95%CI 0.737 - 0.821). The prediction efficiency of the total score of the model's nomogram was good in the 210 - 320 interval, and mean absolute error was 0.011, mean squared error was 0.00018. Conclusions The basic vital signs within 48 h admitting into hospital, as well those homeostasis disordering index indicated by coagulation, liver and renal dysfunction are highly correlated with the prognosis of septic patients with bacterial bloodstream infection. Early warning should be set in order to achieve early detection and rescue patients’ lives.