Socioeconomic Disparities and the Prevalence of Antimicrobial Resistance.

BACKGROUND: The increased prevalence of antimicrobial resistant (AMR) infections is a significant global health threat, resulting in increased morbidity, mortality, and costs. The drivers of AMR are complex and potentially impacted by socioeconomic factors. We investigated the relationships between geographic and socioeconomic factors and AMR. METHODS: We collected select patient bacterial culture results from 2015 to 2020 from electronic health records (EHR) of two expansive healthcare systems within the Dallas-Fort Worth, TX (DFW) metropolitan area. Among individuals with EHR records who resided in the four most populus counties in DFW, culture data were aggregated. Case counts for each organism studied were standardized per 1,000 persons per area population. Using residential addresses, the cultures were geocoded and linked to socioeconomic index values. Spatial autocorrelation tests identified geographic clusters of high and low AMR organism prevalence and correlations with established socioeconomic indices. RESULTS: We found significant clusters of AMR organisms in areas with high levels of deprivation, as measured by the Area Deprivation Index (ADI). We found a significant spatial autocorrelation between ADI and the prevalence of AMR organisms, particularly for AmpC and MRSA with 14% and 13%, respectively, of the variability in prevalence rates being attributable to their relationship with the ADI values of the neighboring locations. CONCLUSIONS: We found that areas with a high ADI are more likely to have higher rates of AMR organisms. Interventions that improve socioeconomic factors such as poverty, unemployment, decreased access to healthcare, crowding, and sanitation in these areas of high prevalence may reduce the spread of AMR.

The role of microbiome-based therapeutics for the reduction and prevention of antimicrobial-resistant organism colonization.

The gut is host to a diverse array of microbiota that constitute a complex ecological system crucial to human physiology. Disruptors to the normal host microbiota, such as antimicrobials, can cause a loss of species diversity in the gut, reducing its ability to resist colonization by invading pathogens and potentially leading to colonization with antimicrobial resistant organisms (AROs). ARO negatively impact gut health by disrupting the usual heterogeneity of gut microbiota and have the potential to cause systemic disease. In recent years, fecal microbiota transplantation (FMT) has been increasingly explored in the management of specific disease states such as Clostridioides difficile infection (CDI). Promising data from management of CDI has led to considerable interest in understanding the role of therapeutics to restore the gut microbiota to a healthy state. This review aims to discuss key studies that highlight the current landscape, and explore existing clinical evidence, for the use of FMT and microbiome-based therapeutics in combating intestinal colonization with ARO. We also explore potential future directions of such therapeutics and discuss unaddressed needs in this field that merit further investigation.

Healthcare costs doubled when children had urinary tract infections caused by extended-spectrum ß-lactamase-producing bacteria.

AIM: The impact of the emergence of antimicrobial resistant organisms has rarely been studied in children, including the healthcare costs of urinary tract infections (UTIs) caused by extended-spectrum beta-lactamase (ESBL)-producing bacteria. We evaluated the effect of ESBL on UTI healthcare costs and risk factors for paediatric UTIs. METHODS: This retrospective case-control study covered 2005-2014 and focused on children below 16 years of age treated in a University hospital: 22 children with UTIs caused by ESBL-producing bacteria and 56 ESBL-negative UTI controls. RESULTS: The median healthcare costs were 3929 Euros for the 22 ESBL patients and 1705 Euros for the 56 controls (p = 0.015). The mean and standard deviation length of hospital stay was 7.4 (5.9) days for the ESBL group and 3.6 (2.3) days for the controls (p = 0.007), and the figures for antibiotic treatment were 12.3 (5.5) days versus 5.8 (3.0) days (p < 0.001), respectively. The odd ratios for ESBL were underlying disease (6.63, p = 0.013), previous hospitalisation (6.07, p = 0.009) and antibiotic prophylaxis (5.20, p = 0.035). CONCLUSION: Healthcare costs more than doubled when children had ESBL-related UTIs, mainly due to their increased length of stay. Effective oral antibiotics are urgently needed to treat paediatric infections caused by ESBL-producing bacteria.

Clinical prediction tools for identifying antimicrobial-resistant organism (ARO) carriage on hospital admissions: a systematic review.

BACKGROUND: Increasing prevalence of antimicrobial-resistant organisms (AROs) is a growing economic and healthcare challenge. Increasing utilization of electronic medical record (EMR) systems and improvements in computation and analytical techniques afford an opportunity to reduce the spread of AROs through the development of clinical prediction tools to identify ARO carriers on admission to hospital. AIM: To identify existing clinical prediction tools for meticillin-resistant Staphylococcus aureus (MRSA) and carbapenemase-producing organisms (CPOs), their predictive performance, and risk factors utilized in these tools. METHODS: The CHARMS checklist was followed. Medline, EMBASE, Cochrane SR, CRD databases (DARE, NHS EED), CINAHL and Web of Science were searched from database inception to 26th July 2021. Full-text articles were assessed independently, and quality assessment was conducted using the Prediction Model Risk of Bias Assessment Tool. FINDINGS: In total, 3809 abstracts were identified and 22 studies were included. Among these studies, risk score models were the most common prediction tool (N=16). Previous admission, recent antibiotic exposure, age and sex were the most common risk factors for ARO carriage. Prediction tools were commonly evaluated on sensitivity and specificity with ranges of 15-100% and 46-98.6%, respectively, for MRSA, and 30-81.3% and 79.8-99.9%, respectively, for CPOs. CONCLUSION: There is no gold standard ARO prediction tool. However, high-performance clinical prediction tools and identification of key risk factors for the early detection of AROs exist. Risk score models are easier to use and interpret; however, with recent improvements in machine learning techniques, highly robust models can be developed with data stored in an EMR.

Clinical manifestations, characteristics, and outcome of infections caused by vancomycin-resistant enterococci at a tertiary care center in Lebanon: A case-case-control study.

BACKGROUND: Vancomycin-resistant enterococci (VRE) are prevalent infectious agents that particularly affect critically-ill patients, and they are on the rise in Lebanon. We aim at determining the potential risk factors and complications for VRE and vancomycin-susceptible enterococci (VSE) infections in a hospital setting and identify risk factors for in-hospital mortality. METHODS: A case-case-control study design was used where patients with VRE and VSE were included as two separate groups and each group was compared to uninfected controls. We also constructed binary regression models to detect risk factors that were associated with the acquisition of a VRE or a VSE infection. We also identified independent mortality predictors for all patients with enterococcal infection as well as patients with only a VRE infection. RESULTS: A total of 142 patients with enterococcal infections (VRE and VSE) were compared to 142 in-patients not infected with Enterococcus spp. independent risk factors for a VRE infection were steroid therapy within 30 days and the presence of another infection preceding the VRE infection (aOR 15.4, 95 % CI 2.4-99.3 and 23.9, 95 % CI 3.9-1482, respectively). An independent risk factor for VSE was diabetes mellitus (aOR 5.4, 95 % CI 1.1-26.6). Based on these risk factors, we developed a risk score to be used in quantifying the risk of VRE in a patient with an enterococcal infection. Male sex and low albumin were significant risk factors for mortality in our patient cohort. CONCLUSIONS: VRE and VSE infections have distinct risk factors that can be used to guide empiric antimicrobial therapy.

Dimensions of poverty as risk factors for antimicrobial resistant organisms in Canada: a structured narrative review.

BACKGROUND: Few studies have assessed the relationship between poverty and the risk of infection with antimicrobial resistant organisms (AROs). We sought to identify, appraise, and synthesize the available published Canadian literature that analyzes living in poverty and risk of AROs. METHODS: A structured narrative review methodology was used, including a systematic search of three databases: MedLINE, EMBASE and Web of Science for articles pertaining to poverty, and infection with AROs in Canada between 1990 and 2020. Poverty was broadly defined to include economic measures and associated social determinants of health. Based on inclusion and exclusion criteria, there were 889 initial articles, and 43 included in the final review. The final articles were extracted using a standard format and appraised using the Joanna Briggs Institute Levels of Evidence framework. RESULTS: Of 43 studies, 15 (35%) related to methicillin-resistant Staphylococcus aureus (MRSA). One study found a 73% risk reduction (RR 0.27, 95%CI 0.19-0.39, p = < 0.0001) in community-acquired MRSA (CA-MRSA) infection for each $100,000 income increase. Results pertaining to homelessness and MRSA suggested transmission was related to patterns of frequent drug use, skin-to-skin contact and sexual contact more than shelter contact. Indigenous persons have high rates of CA-MRSA, with more rooms in the house being a significant protective factor (OR 0.86, p = 0.023). One study found household income over $60,000 (OR 0.83, p = 0.039) in univariate analysis and higher maternal education (OR 0.76, 95%CI 0.63-0.92, p = 0.005) in multivariate analysis were protective for otitis media due to an ARO among children. Twenty of 43 (46.5%) articles pertained to tuberculosis (TB). Foreign-born persons were four times more likely to have resistant TB compared to Canadian-born persons. None of the 20 studies used income in their analyses. CONCLUSIONS: There is an association between higher income and protection from CA-MRSA. Mixed results exist regarding the impact of homelessness and MRSA, demonstrating a nuanced relationship with behavioural risk factors. Higher income and maternal education were associated with reduced ARO-associated acute otitis media in children in one study. We do not have a robust understanding of the social measures of marginalization related to being foreign-born that contribute to higher rates of resistant TB infection.

The Canadian Nosocomial Infection Surveillance Program: Keeping an eye on antimicrobial resistance in Canadian hospitals since 1995.

Surveillance is essential to inform evidence-based policy and control measures that combat antimicrobial resistance (AMR). The Canadian Nosocomial Infection Surveillance Program (CNISP) collaborates with 88 sentinel hospitals across Canada to conduct prospective surveillance of infections and antimicrobial resistant organisms important to hospital infection prevention and control. This article aims to increase awareness of CNISP hospital-based surveillance activities. Since its inception in 1995, the scope of CNISP has expanded to include community-associated infections, outpatient Clostridioides difficile infections, viral respiratory infections such as coronavirus disease 2019, and emerging pathogens such as Candida auris. This change in scope, along with expansion to include rural, northern and community hospitals, has improved the generalizability of CNISP surveillance data. To generate actionable surveillance data, CNISP integrates demographic and clinical data abstracted from patient charts with molecular and microbiological data abstracted from laboratory testing. These data serve as a benchmark for participating hospitals and stakeholders to assess the burden of AMR in hospital and intervene as needed. Further, CNISP surveillance data are now available on a public-facing data blog that provides interactive visualizations and data syntheses sooner than peer-reviewed publications. Future directions of CNISP include the Simplified Dataset, which will capture aggregate AMR data from hospitals outside of the CNISP network, surveillance in long-term care facilities and a fourth point prevalence survey. Given its strengths and future directions, CNISP is well positioned to serve as the reference point for hospital-based AMR data in Canada.

Prevalence of antimicrobial-resistant organisms in smaller Canadian hospitals: Community, Rural, and Northern Acute Care Point Prevalence (CNAPP-19) Survey, 2019.

Background: The availability of national data on the prevalence of antimicrobial resistant infections in smaller, community, northern and rural acute care hospitals is limited. The objective of this article is to determine the prevalence of infections caused by selected antimicrobial-resistant organisms (AROs) in these smaller hospitals. Methods: A point prevalence survey was conducted by 55 hospitals between February and May 2019 and included representation from all 10 Canadian provinces. Eligible hospitals were those with 350 or fewer beds. Data were collected on hospital characteristics. De-identified patient data were collected on selected infections (pneumonia, urinary tract infections, bloodstream infections, skin/soft tissue infections, surgical site infections, and Clostridioides difficile infections) for selected AROs (methicillin-resistant Staphylococcus aureus, vancomycin-resistant Enterococci, extended-spectrum ß-lactamase-producing organisms and carbapenemase-producing organisms). Data on antimicrobial prescribing and infection prevention and control precautions were also collected. Results: A total of 3,640 patients were included in the survey. Median patient age was 73 years, and 52.8% (n=1,925) were female. Selected infections were reported in 14.4% (n=524) of patients, of which 6.9% (n=36) were associated with an ARO infection. Infection prevention and control additional precautions were in place for 13.7% (n=500) of patients, of which half (51.0%, n=255) were due to an ARO. Approximately one third (35.2%, n=1,281) of patients had at least one antimicrobial prescribed. Conclusion: Antimicrobial-resistant organisms remain a serious threat to public health in Canada. The results of this survey warrant further investigation into AROs in smaller Canadian hospitals as a potential reservoir of antimicrobial resistance.

Direct detection of OXA-48-like carbapenemase variants with and without co-expression of an extended-spectrum ß-lactamase from bacterial cell lysates using mass spectrometry.

INTRODUCTION: Antibiotic-resistant Gram-negative bacteria are of a growing concern globally, especially those producing enzymes conferring resistance. OXA-48-like carbapenemases hydrolyze most ß-lactam antibiotics, with typically low-level hydrolysis of carbapenems, but have limited effect on broad-spectrum cephalosporins. These are frequently co-expressed with extended spectrum ß-lactamases, especially CTX-M-15, which typically shows high level resistance to broad-spectrum cephalosporins, yet is carbapenem susceptible. The combined resistance profile makes the need for successful detection of these specific resistance determinants imperative for effective antibiotic therapy. OBJECTIVES: The objective of this study is to detect and identify OXA-48-like and CTX-M-15 enzymes using mass spectrometry, and to subsequently develop a method for detection of both enzyme types in combination with liquid chromatography. METHODS: Cells grown in either broth or on agar were harvested, lysed, and, in some cases buffer-exchanged. Lysates produced from bacterial cells were separated and analyzed via liquid chromatography with mass spectrometry (LC-MS) and tandem mass spectrometry (LC-MS/MS). RESULTS: The intact proteins of OXA-48, OXA-181, and OXA-232 (collectively OXA-48-like herein) and CTX-M-15 were characterized and detected. Acceptance criteria based on sequence-informative fragments from each protein group were established as confirmatory markers for the presence of the protein(s). A total of 25 isolates were successfully tested for OXA-48 like (2), CTX-M-15 (3), or expression of both (7) enzymes. Thirteen isolates served as negative controls. CONCLUSIONS: Here we present a method for the direct and independent detection of both OXA-48-like carbapenemases and CTX-M-15 ß-lactamases using LC-MS/MS. The added sensitivity of MS/MS allows for simultaneous detection of at least two co-eluting, co-isolated and co-fragmented proteins from a single mass spectrum.

The evolutionary puzzle of Escherichia coli ST131.

The abrupt expansion of Escherichia coli sequence type (ST) 131 is unmatched among Gram negative bacteria. In many ways, ST131 can be considered a real-world model for the complexities involved in the evolution of a multidrug resistant pathogen. While much progress has been made on our insights into the organism's population structure, pathogenicity and drug resistance profile, significant gaps in our knowledge remain. Whole genome studies have shed light on key mutations and genes that have been selected against the background of antibiotics, but in most cases such events are inferred and not supported by experimental data. Notable examples include the unknown fitness contribution made by specific plasmids, genomic islands and compensatory mutations. Furthermore, questions remain like why this organism in particular achieved such considerable success in such a short time span, compared to other more pathogenic and resistant clones. Herein, we document what is known regarding the genetics of this organism since its first description in 2008, but also highlight where work remains to be done for a truly comprehensive understanding of the biology of ST131, in order to account for its dramatic rise to prominence.

Utilizing Organoid and Air-Liquid Interface Models as a Screening Method in the Development of New Host Defense Peptides.

Host defense peptides (HDPs), also known as antimicrobial peptides, are naturally occurring polypeptides (~12-50 residues) composed of cationic and hydrophobic amino acids that adopt an amphipathic conformation upon folding usually after contact with membranes. HDPs have a variety of biological activities including immunomodulatory, anti-inflammatory, anti-bacterial, and anti-biofilm functions. Although HDPs have the potential to address the global threat of antibiotic resistance and to treat immune and inflammatory disorders, they have yet to achieve this promise. Indeed, there are several challenges associated with bringing peptide-based drug candidates from the lab bench to clinical practice, including identifying appropriate indications, stability, toxicity, and cost. These challenges can be addressed in part by the development of innate defense regulator (IDR) peptides and peptidomimetics, which are synthetic derivatives of HDPs with similar or better efficacy, increased stability, and reduced toxicity and cost of the original HDP. However, one of the largest gaps between basic research and clinical application is the validity and translatability of conventional model systems, such as cell lines and animal models, for screening HDPs and their derivatives as potential drug therapies. Indeed, such translation has often relied on animal models, which have only limited validity. Here we discuss the recent development of human organoids for disease modeling and drug screening, assisted by the use of omics analyses. Organoids, developed from primary cells, cell lines, or human pluripotent stem cells, are three-dimensional, self-organizing structures that closely resemble their corresponding in vivo organs with regards to immune responses, tissue organization, and physiological properties; thus, organoids represent a reliable method for studying efficacy, formulation, toxicity and to some extent drug stability and pharmacodynamics. The use of patient-derived organoids enables the study of patient-specific efficacy, toxicogenomics and drug response predictions. We outline how organoids and omics data analysis can be leveraged to aid in the clinical translation of IDR peptides.

Mapping and Analysing Potential Sources and Transmission Routes of Antimicrobial Resistant Organisms in the Environment using Geographic Information Systems-An Exploratory Study.

Antimicrobial resistance (AMR) is one of the leading threats to human health worldwide. The identification of potential sources of antimicrobial resistant organisms (AROs) and their transmission routes in the environment is important for improving our understanding of AMR and to inform and improve policy and monitoring systems, as well as the identification of suitable sampling locations and potential intervention points. This exploratory study uses geographic information systems (GIS) to analyse the spatial distribution of likely ARO sources and transmission routes in four local authority areas (LAAs) in Ireland. A review of relevant spatial data in each LAA, grouped into themes, and categorised into sources and transmission routes, was undertaken. A range of GIS techniques was used to extract, organise, and collate the spatial data into final products in the form of thematic maps for visual and spatial analysis. The results highlight the location of 'clusters' at increased risk of harbouring AMR in each LAA. They also demonstrate the relevance of aquatic transmission routes for ARO mobility and risk of human exposure. The integration of a GIS approach with expert knowledge of AMR is shown to be a useful tool to gain insights into the spatial dimension of AMR and to guide sampling campaigns and intervention points.

Decision-support models for empiric antibiotic selection in Gram-negative bloodstream infections.

OBJECTIVES: Early empiric antibiotic therapy in patients can improve clinical outcomes in Gram-negative bacteraemia. However, the widespread prevalence of antibiotic-resistant pathogens compromises our ability to provide adequate therapy while minimizing use of broad antibiotics. We sought to determine whether readily available electronic medical record data could be used to develop predictive models for decision support in Gram-negative bacteraemia. METHODS: We performed a multi-centre cohort study, in Canada and the USA, of hospitalized patients with Gram-negative bloodstream infection from April 2010 to March 2015. We analysed multivariable models for prediction of antibiotic susceptibility at two empiric windows: Gram-stain-guided and pathogen-guided treatment. Decision-support models for empiric antibiotic selection were developed based on three clinical decision thresholds of acceptable adequate coverage (80%, 90% and 95%). RESULTS: A total of 1832 patients with Gram-negative bacteraemia were evaluated. Multivariable models showed good discrimination across countries and at both Gram-stain-guided (12 models, areas under the curve (AUCs) 0.68-0.89, optimism-corrected AUCs 0.63-0.85) and pathogen-guided (12 models, AUCs 0.75-0.98, optimism-corrected AUCs 0.64-0.95) windows. Compared to antibiogram-guided therapy, decision-support models of antibiotic selection incorporating individual patient characteristics and prior culture results have the potential to increase use of narrower-spectrum antibiotics (in up to 78% of patients) while reducing inadequate therapy. CONCLUSIONS: Multivariable models using readily available epidemiologic factors can be used to predict antimicrobial susceptibility in infecting pathogens with reasonable discriminatory ability. Implementation of sequential predictive models for real-time individualized empiric antibiotic decision-making has the potential to both optimize adequate coverage for patients while minimizing overuse of broad-spectrum antibiotics, and therefore requires further prospective evaluation. SUMMARY: Readily available epidemiologic risk factors can be used to predict susceptibility of Gram-negative organisms among patients with bacteraemia, using automated decision-making models.

COMMON INFECTIONS IN THE ELDERLY IN THE HOME OR NURSING HOME SETTING

Infections in the elderly are associated with high morbidity and mortality. Diagnosing infections in the elderly is challenging due to their atypical and subtle presentation. A high index of suspicion is often needed. Commonly encountered infections in the elderly include bacterial pneumonia, urinary tract infection, cellulitis and Herpes zoster. In addition, institutionalised elderly and those with multiple hospital admissions are at risk of infection with Multidrug-resistant Organisms (MROs); this can be difficult to manage. The purpose of this article is to look at some common infections in the elderly encountered in the home or nursing home, and review their management.