Epidemiological Characteristics and Drug Resistance Analysis of Cerebrospinal Fluid Microbial Infections in Wenzhou Area

Epidemiology and Drug Resistance of Pathogens Isolated from Cerebrospinal Fluids at a Children's Medical Center in Eastern China During 2006-2020

Objective

To investigate the epidemiology and drug resistance of pathogens isolated from cerebrospinal fluid samples at a children's medical center in eastern China and provide the basis for anti-infection treatments.

Methods

In all, 307 non-duplicated strains of pathogens were isolated from cerebrospinal fluid samples in the Children's Hospital of Soochow University from January 2006 to December 2020. Mass spectrometry was used for pathogen identification. The VITEK 2 Compact system and Kirby-Bauer method were applied to determine antimicrobial susceptibility.

Results

Among the 307 isolates, gram-positive bacteria, gram-negative bacteria and fungi accounted for 60.26%, 34.53%, and 5.21%, respectively. The most prevalent pathogens were Streptococcus pneumoniae (26.06%), Escherichia coli (20.20%) and Streptococcus agalactiae (17.26%). The number of isolates was highest in winter. The most prevalent gram-positive bacterium in children <6 months old was Streptococcus agalactiae, while Streptococcus pneumoniae was the most in children were >6 months old. The drug resistance of gram-positive bacteria, fungi and Haemophilus influenza were not high. In addition, 35 strains of gram-negative bacteria produced extended-spectrum β-lactamases (ESBLs) and 6 strains were identified as multidrug-resistant (MDR) bacteria. These strains showed much higher resistance to the antibiotics than other strains.

Conclusion

Cases of meningitis among children have increased in the past 15 years and MDR bacteria were also identified. The emergence of MDR bacteria is a cause for great concern and requires further investigation.

Accuracy of Meningitis Bacterial Score (MBS) as an indicator in establishing the diagnosis of acute bacterial meningitis in adults

Bacterial meningitis persists as a worldwide threat contributing to high mortality and morbidity rate, where differentiating bacterial meningitis from aseptic meningitis is key for better management and outcomes. Hence, this study aimed to assess the Bacterial Meningeal Score (BMS) as a tool for early diagnosis of acute bacterial meningitis. This study employed a retrospective cross-sectional method using medical records of patients with meningitis and meningoencephalitis who were hospitalized at Dr. Soetomo Hospital, from January 2018 to September 2021. Data of demographics, clinical, laboratory and cerebrospinal fluid (CSF) profile and culture were collected. The diagnostic performance of the BMS in diagnosing acute bacterial meningitis was evaluated by its sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), positive likelihood ratio (LR +) and negative likelihood ratio (LR -). A total of 128 patients who had been diagnosed with meningitis and meningoencephalitis were included. Out of total patients, 53 samples were diagnosed with acute bacterial meningitis as confirmed by CSF culture. The sensitivity and specificity of BMS with cutoff >2.5 in diagnosing acute bacterial meningitis were 92.4% and 92.0%, respectively with PPV 89.1% and NPV 94.5%. The area under the curve (AUC) of BMS in diagnosing of acute bacterial meningitis was 95.6% (95%CI: 92.3%, 99%). A BMS score of greater than 2.5 indicates a high likelihood of acute bacterial meningitis, whereas a score less than 2.5 indicates a low likelihood.