Impact of an Antibiotic Stewardship Program on the Incidence of Resistant Escherichia coli: A Quasi-Experimental Study

Insights into the Two Most Common Cancers of Primitive Gut-Derived Structures and Their Microbial Connections

The gastrointestinal and respiratory systems are closely linked in different ways, including from the embryological, anatomical, cellular, and physiological angles. The highest number (and various types) of microorganisms live in the large intestine/colon, and constitute the normal microbiota in healthy people. Adverse alterations of the microbiota or dysbiosis can lead to chronic inflammation. If this detrimental condition persists, a sequence of pathological events can occur, such as inflammatory bowel disease, dysplasia or premalignant changes, and finally, cancer. One of the most commonly identified bacteria in both inflammatory bowel disease and colon cancer is Escherichia coli. On the other hand, patients with inflammatory bowel disease are at risk of several other diseases-both intestinal (such as malnutrition and intestinal obstruction, besides cancer) and extraintestinal (such as arthritis, bronchiectasis, and cancer risk). Cancers of the lung and colon are the two most common malignancies occurring worldwide (except for female breast cancer). Like the bacterial role in colon cancer, many studies have shown a link between chronic Chlamydia pneumoniae infection and lung cancer. However, in colon cancer, genotoxic colibactin-producing E. coli belonging to the B2 phylogroup may promote tumorigenesis. Furthermore, E. coli is believed to play an important role in the dissemination of cancer cells from the primary colonic site. Currently, seven enteric pathogenic E. coli subtypes have been described. Conversely, three Chlamydiae can cause infections in humans (C. trachomatis may increase the risk of cervical and ovarian cancers). Nonetheless, striking genomic plasticity and genetic modifications allow E. coli to constantly adjust to the surrounding environment. Consequently, E. coli becomes resistant to antibiotics and difficult to manage. To solve this problem, scientists are thinking of utilizing suitable lytic bacteriophages (viruses that infect and kill bacteria). Several bacteriophages of E. coli and Chlamydia species are being evaluated for this purpose.

Machine-learning-based risk assessment tool to rule out empirical use of ESBL-targeted therapy in endemic areas

BACKGROUND

Antimicrobial stewardship focuses on identifying patients who require extended-spectrum beta-lactamase (ESBL)-targeted therapy. 'Rule-in' tools have been researched extensively in areas of low endemicity; however, such tools are inadequate for areas with high prevalence of ESBL-producing pathogens, as almost all patients will be selected.

AIM

To develop a machine-learning-based 'rule-out' tool suitable for areas with high levels of resistance.

METHODS

Gradient-boosted decision trees were used to train and validate a risk prediction model on data from 17,913 (45% ESBL) patients with Escherichia coli and Klebsiella pneumoniae in urine cultures. The predictive power of different sets of variables was evaluated using Shapley values to evaluate the contributions of variables.

FINDINGS

The model successfully identified patients with low risk of ESBL resistance in ESBL-endemic areas (area under receiver operating characteristic curve 0.72). When used to select the 30% of patients with the lowest predicted risk, the model yielded a negative predictive value ≥0.74. A simplified model with seven input features was found to perform nearly as well as the full model. This simplified model is freely accessible as a web application.

CONCLUSIONS

This study found that a risk calculator for antibiotic resistance can be a viable 'rule-out' strategy to reduce the use of ESBL-targeted therapy in ESBL-endemic areas. The robust performance of a version of the model with limited features makes the clinical use of such a tool feasible. This tool provides an important alternative in an era with growing rates of ESBL-producing pathogens, where some experts have called for empirical use of carbapenems as first-line therapy for all patients in areas with high prevalence of ESBL-producing pathogens.

Impact of a Primary Care Antimicrobial Stewardship Program on Bacterial Resistance Control and Ecological Imprint in Urinary Tract Infections

Antimicrobial stewardship programs (ASPs) are a central component in reducing the overprescription of unnecessary antibiotics, with multiple studies showing benefits in the reduction of bacterial resistance. Less commonly, ASPs have been performed in outpatient settings, but there is a lack of available data in these settings. We implemented an ASP in a large regional outpatient setting to assess its feasibility and effectiveness. Over a 5-year post-implementation period, compared to the pre-intervention period, a significant reduction in antibiotic prescription occurred, with a reduction in resistance in E. coli urinary isolates. ASP activities also were found to be cost-effective, with a reduction in medication prescription.

The current landscape of microRNAs (miRNAs) in bacterial pneumonia: opportunities and challenges

MicroRNAs (miRNAs), which were initially discovered in Caenorhabditis elegans, can regulate gene expression by recognizing cognate sequences and interfering with the transcriptional or translational machinery. The application of bioinformatics tools for structural analysis and target prediction has largely driven the investigation of certain miRNAs. Notably, it has been found that certain miRNAs which are widely involved in the inflammatory response and immune regulation are closely associated with the occurrence, development, and outcome of bacterial pneumonia. It has been shown that certain miRNA techniques can be used to identify related targets and explore associated signal transduction pathways. This enhances the understanding of bacterial pneumonia, notably for "refractory" or drug-resistant bacterial pneumonia. Although these miRNA-based methods may provide a basis for the clinical diagnosis and treatment of this disease, they still face various challenges, such as low sensitivity, poor specificity, low silencing efficiency, off-target effects, and toxic reactions. The opportunities and challenges of these methods have been completely reviewed, notably in bacterial pneumonia. With the continuous improvement of the current technology, the miRNA-based methods may surmount the aforementioned limitations, providing promising support for the clinical diagnosis and treatment of "refractory" or drug-resistant bacterial pneumonia.