New evidence for managing Gram-negative bloodstream infections

Prediction of carbapenem-resistant gram-negative bacterial bloodstream infection in intensive care unit based on machine learning

BACKGROUND

Predicting whether Carbapenem-Resistant Gram-Negative Bacterial (CRGNB) cause bloodstream infection when giving advice may guide the use of antibiotics because it takes 2-5 days conventionally to return the results from doctor's order.

METHODS

It is a regional multi-center retrospective study in which patients with suspected bloodstream infections were divided into a positive and negative culture group. According to the positive results, patients were divided into the CRGNB group and other groups. We used the machine learning algorithm to predict whether the blood culture was positive and whether the pathogen was CRGNB once giving the order of blood culture.

RESULTS

There were 952 patients with positive blood cultures, 418 patients in the CRGNB group, 534 in the non-CRGNB group, and 1422 with negative blood cultures. Mechanical ventilation, invasive catheterization, and carbapenem use history were the main high-risk factors for CRGNB bloodstream infection. The random forest model has the best prediction ability, with AUROC being 0.86, followed by the XGBoost prediction model in bloodstream infection prediction. In the CRGNB prediction model analysis, the SVM and random forest model have higher area under the receiver operating characteristic curves, which are 0.88 and 0.87, respectively.

CONCLUSIONS

The machine learning algorithm can accurately predict the occurrence of ICU-acquired bloodstream infection and identify whether CRGNB causes it once giving the order of blood culture.

Evolution and development of potent monobactam sulfonate candidate IMBZ18g as a dual inhibitor against MDR Gram-negative bacteria producing ESBLs

A series of new monobactam sulfonates is continuously synthesized and evaluated for their antimicrobial efficacies against Gram-negative bacteria. Compound 33a (IMBZ18G) is highly effective in vitro and in vivo against clinically intractable multi-drug-resistant (MDR) Gram-negative strains, with a highly druglike nature. The checkerboard assay reveals its significant synergistic effect with β-lactamase inhibitor avibactam, and the MIC values against MDR enterobacteria were reduced up to 4-512 folds. X-ray co-crystal and chemoproteomic assays indicate that the anti-MDR bacteria effect of 33a results from the dual inhibition of the common PBP3 and some class A and C β-lactamases. Accordingly, preclinical studies of 33a alone and 33a‒avibactam combination as potential innovative candidates are actively going on, in the treatment of β-lactamase-producing MDR Gram-negative bacterial infections.

Antimicrobial susceptibility to polymyxin B and other comparators against Gram-negative bacteria isolated from bloodstream infections in China: Results from CARVIS-NET program

Objective

To investigate the bacterial distribution and antimicrobial resistance profile of clinical isolates from Gram-negative bacteria bloodstream infections (GNBSI) in China.

Methods

The clinical bacterial strains isolated from blood culture were collected during April 2019 to December 2021 in 21 member hospitals of China Bloodstream Gram-negative Pathogens Antimicrobial Resistance and Virulence Surveillance Network (CARVIS-NET). Antibiotic susceptibility test was conducted by broth microdilution method recommended by Clinical and Laboratory Standards Institute (CLSI, United States). WHONET 2021 and SPSS 22.0 were used to analyze data.

Results

During the study period, 1939 Gram-negative bacteria were collected from 21 hospitals, among which 1,724 (88.9%) were Enterobacteriaceae, 207 (10.7%) were non-fermenting Gram-negative bacteria and 8 (0.4%) were others. The top five bacterial species were Escherichia coli (46.2%), Klebsiella pneumoniae (31.6%), Pseudomonas aeruginosa (4.9%), Acinetobacter baumannii (4.2%) and Enterobacter cloacae (3.0%). For K. pneumoniae, antibiotic resistance was mainly prevalent in hospital-associated bloodstream infections, while for A. baumannii, antibiotic resistance was mainly prevalent in community-associated bloodstream infections. It is worth mentioning that 94.1% of the 1939 Gram-negative isolates were susceptible to polymyxin B. The sensitivity of the strains involved in our investigation to polymyxin B is highly correlated with their sensitivity to colistin.

Conclusion

The surveillance results in CARVIS-NET-2021 showed that the main pathogens of GNBSI in China were Enterobacteriaceae, while E. coli was the most common pathogen. The resistance rates of K. pneumonia, P. aeruginosa, A. baumannii, and E. cloacae to multiple antibiotics kept on a high level. In many cases, polymyxin B and colistin has become the last-resort agents to combat bloodstream infections caused by multidrug-resistant (MDR) Gram-negative bacteria.