Geographic mapping of Enterobacteriaceae with extended-spectrum β-lactamase (ESBL) phenotype in Pereira, Colombia

Application of Spatial Analysis for Electronic Health Records: Characterizing Patient Phenotypes and Emerging Trends

Background

Electronic health records (EHR) commonly contain patient addresses that provide valuable data for geocoding and spatial analysis, enabling more comprehensive descriptions of individual patients for clinical purposes. Despite the widespread use of EHR in clinical decision support and interventions, no systematic review has examined the extent to which spatial analysis is used to characterize patient phenotypes.

Objective

This study reviews advanced spatial analyses that employed individual-level health data from EHR within the US to characterize patient phenotypes.

Methods

We systematically evaluated English-language peer-reviewed articles from PubMed/MEDLINE, Scopus, Web of Science, and Google Scholar databases from inception to August 20, 2023, without imposing constraints on time, study design, or specific health domains.

Results

Only 49 articles met the eligibility criteria. These articles utilized diverse spatial methods, with a predominant focus on clustering techniques, while spatiotemporal analysis (frequentist and Bayesian) and modeling were relatively underexplored. A noteworthy surge (n = 42, 85.7%) in publications was observed post-2017. The publications investigated a variety of adult and pediatric clinical areas, including infectious disease, endocrinology, and cardiology, using phenotypes defined over a range of data domains, such as demographics, diagnoses, and visits. The primary health outcomes investigated were asthma, hypertension, and diabetes. Notably, patient phenotypes involving genomics, imaging, and notes were rarely utilized.

Conclusions

This review underscores the growing interest in spatial analysis of EHR-derived data and highlights knowledge gaps in clinical health, phenotype domains, and spatial methodologies. Additionally, this review proposes guidelines for harnessing the potential of spatial analysis to enhance the context of individual patients for future clinical decision support.

Predictive Mapping of Antimicrobial Resistance for Escherichia coli, Salmonella, and Campylobacter in Food-Producing Animals, Europe, 2000-2021

In Europe, systematic national surveillance of antimicrobial resistance (AMR) in food-producing animals has been conducted for decades; however, geographic distribution within countries remains unknown. To determine distribution within Europe, we combined 33,802 country-level AMR prevalence estimates with 2,849 local AMR prevalence estimates from 209 point prevalence surveys across 31 countries. We produced geospatial models of AMR prevalence in Escherichia coli, nontyphoidal Salmonella, and Campylobacter for cattle, pigs, and poultry. We summarized AMR trends by using the proportion of tested antimicrobial compounds with resistance >50% and generated predictive maps at 10 × 10 km resolution that disaggregated AMR prevalence. For E. coli, predicted prevalence rates were highest in southern Romania and southern/eastern Italy; for Salmonella, southern Hungary and central Poland; and for Campylobacter, throughout Spain. Our findings suggest that AMR distribution is heterogeneous within countries and that surveillance data from below the country level could help with prioritizing resources to reduce AMR.

Spatial clusters of extended-spectrum beta-lactamase-producing Escherichia coli causing community-onset bacteriuria due to repeat infections: cluster analysis from a large urban medical center, San Francisco, 2014-2020

BACKGROUND

Urinary tract infections caused by extended-spectrum beta-lactamase (ESBL)-producing Escherichia coli (ESBL-E. coli) may occur as outbreaks due to common-source exposures. Yet, it is currently unknown if they cluster geographically as would be expected as part of an outbreak.

METHODS

We collected electronic health record data on all patients living in San Francisco with culture-documented community-onset E. coli bacteriuria in a safety-net public healthcare system from January 2014 to March 2020 (diagnosed < 48 h after hospital admission or in outpatient clinical settings without a hospitalization in the past 90 days). We assessed the presence of spatial clusters of (1) ESBL-E. coli bacteriuria episodes, and (2) individuals with any ESBL-E. coli bacteriuria episode, with Global and Local Moran's I. We evaluated differences in prevalence of bacteriuria recurrence by ESBL-production by Poisson regression.

RESULTS

Out of 4,304 unique individuals, we identified spatial clusters of ESBL-E. coli bacteriuria episodes (n = 461) compared to non-ESBL-E. coli bacteriuria episodes (n = 5477; Global Moran's p < 0.001). Spatial clusters of individuals with any bacteriuria caused by ESBL-E. coli were not identified (p = 0.43). Bacteriuria recurrence was more likely to occur with ESBL-E. coli (odds ratio [OR] 2.78, 95% confidence interval [95% CI] 2.10, 3.66, p < 0.001), particularly after an initial ESBL-E. coli bacteriuria episode (OR 2.27, 95% CI 1.82, 2.83, p < 0.001).

CONCLUSION

We found spatial clusters of ESBL-E. coli bacteriuria episodes. However, this was partly explained by clustering within individuals more than between individuals, as having an ESBL-E. coli bacteriuria was associated with recurrence with ESBL-E. coli. These findings may help better tailor clinical treatment of patients with recurrent urinary tract infections after an initial episode caused by ESBL-E. coli.

National action plans for antimicrobial resistance and variations in surveillance data platforms

Objective

To assess how national antimicrobial susceptibility data used to inform national action plans vary across surveillance platforms.

Methods

We identified available open-access, supranational, interactive surveillance platforms and cross-checked their data in accordance with the World Health Organization's (WHO's) Data Quality Assurance: module 1. We compared platform usability and completeness of time-matched data on the antimicrobial susceptibilities of four blood isolate species: Escherichia coli, Klebsiella pneumoniae, Staphylococcus aureus and Streptococcus pneumoniae from WHO's Global Antimicrobial Resistance and Use Surveillance System, European Centre for Disease Control's (ECDC's) network and Pfizer's Antimicrobial Testing Leadership and Surveillance database. Using Bland-Altman analysis, paired t-tests, and Wilcoxon signed-rank tests, we assessed susceptibility data and number of isolate concordances between platforms.

Findings

Of 71 countries actively submitting data to WHO, 28 also submit to Pfizer's database; 19 to ECDC; and 16 to all three platforms. Limits of agreement between WHO's and Pfizer's platforms for organism-country susceptibility data ranged from -26% to 35%. While mean susceptibilities of WHO's and ECDC's platforms did not differ (bias: 0%, 95% confidence interval: -2 to 2), concordance between organism-country susceptibility was low (limits of agreement -18% to 18%). Significant differences exist in isolate numbers reported between WHO-Pfizer (mean of difference: 674, P-value: < 0.001, and WHO-ECDC (mean of difference: 192, P-value: 0.04) platforms.

Conclusion

The considerable heterogeneity of nationally submitted data to commonly used antimicrobial resistance surveillance platforms compromises their validity, thus undermining local and global antimicrobial resistance strategies. Hence, we need to understand and address surveillance platform variability and its underlying mechanisms.

Spatial clusters of extended-spectrum beta-lactamase-producing Escherichia coli causing community-onset bacteriuria due to repeat infections: cluster analysis from a large urban medical center, San Francisco, 2014-2020

Background

Urinary tract infections caused by extended-spectrum beta-lactamase (ESBL)-producing Escherichia coli (ESBL-E. coli) may occur as outbreaks due to common-source exposures. Yet, it is currently unknown if they cluster geographically as would be expected as part of an outbreak.

Methods

We collected electronic health record data on all patients living in San Francisco with culture-documented community-onset E. coli bacteriuria in a safety-net public healthcare system from January 2014 to March 2020 (diagnosed < 48 hours after hospital admission or in outpatient clinical settings without a hospitalization in the past 90 days). We assessed the presence of spatial clusters of (1) ESBL-E. coli bacteriuria episodes, and (2) individuals with any ESBL-E. coli bacteriuria episode, with Global and Local Moran's I. We evaluated differences in prevalence of bacteriuria recurrence by ESBL-production by Poisson regression.

Results

Out of 4,304 unique individuals, we identified spatial clusters of ESBL-E. coli bacteriuria episodes (n = 461) compared to non-ESBL-E. coli bacteriuria episodes (n = 5477; Global Moran's p < 0.001). Spatial clusters of individuals with any bacteriuria caused by ESBL-E. coli were not identified (p = 0.43). Bacteriuria recurrence was more likely to occur with ESBL-E. coli (odds ratio [OR] 2.78, 95% confidence interval [95% CI] 2.10, 3.66, p < 0.001), particularly after an initial ESBL-E. coli bacteriuria episode (OR 2.27, 95% CI 1.82, 2.83, p < 0.001).

Conclusion

We found spatial clusters of ESBL-E. coli bacteriuria episodes. However, this was partly explained by clustering within individuals more than between individuals, as having an ESBL-E. coli bacteriuria was associated with recurrence with ESBL-E. coli.

Risk-factor analysis for extended-spectrum beta-lactamase-producing Enterobacterales colonization or infection: Evaluation of a novel approach to assess local prevalence as a risk factor

OBJECTIVE

To explore an approach to identify the risk of local prevalence of extended-spectrum β-lactamase-producing Enterobacterales (ESBL-E) on ESBL-E colonization or infection and to reassess known risk factors.

DESIGN

Case-control study.

SETTING

Johns Hopkins Health System emergency departments (EDs) in the Baltimore-Washington, DC, region.

PATIENTS

Patients aged ≥18 years with a culture growing Enterobacterales between April 2019 and December 2021. Cases had a culture growing an ESBL-E.

METHODS

Addresses were linked to Census Block Groups and placed into communities using a clustering algorithm. Prevalence in each community was estimated using the proportion of ESBL-E among Enterobacterales isolates. Logistic regression was used to determine risk factors for ESBL-E colonization or infection.

RESULTS

ESBL-E were detected in 1,167 of 11,224 patients (10.4%). Risk factors included a history of ESBL-E in the prior 6 months (aOR, 20.67; 95% CI, 13.71-31.18), exposure to a skilled nursing or long-term care facility (aOR, 1.64; 95% CI, 1.37-1.96), exposure to a third-generation cephalosporin (aOR, 1.79; 95% CI, 1.46-2.19), exposure to a carbapenem (aOR, 2.31; 95% CI, 1.68-3.18), or exposure to a trimethoprim-sulfamethoxazole (aOR, 1.54; 95% CI, 1.06-2.25) within the prior 6 months. Patients were at lower risk if their community had a prevalence <25th percentile in the prior 3 months (aOR, 0.83; 95% CI, 0.71-0.98), 6 months (aOR, 0.83; 95% CI, 0.71-0.98), or 12 months (aOR, 0.81; 95% CI, 0.68-0.95). There was no association between being in a community in the >75th percentile and the outcome.

CONCLUSIONS

This method of defining the local prevalence of ESBL-E may partially capture differences in the likelihood of a patient having an ESBL-E.

Geographic distribution of the major clone of extended-spectrum beta-lactamase-producing Escherichia coli infection in a pediatric community in southern Taiwan

BACKGROUND

The geographic distribution of the major clone of sequence type 131 (ST131) in extended-spectrum beta-lactamase (ESBL)-producing Escherichia coli (E. coli) infections is not known. We analyzed the clinical features, resistance mechanisms, and geographic distribution of ESBL-producing E. coli clones in 120 children.

METHODS

We studied the 120 ESBL-producing E. coli strains from children younger than 18 years. A VITEK 2 automated system was used to determine bacterial identification and ESBL production. Sequence type was determined by multi-locus sequence typing (MLST). The genetic relationship of the ESBL-producing strains was studied using pulsed-field gel electrophoresis (PFGE). Phylogenetic group and blaCTX-M group was performed using polymerase chain reaction (PCR). Multiplex PCR for detecting the common group 9 variant, CTX-M-14, and group 1 variant, CTX-M-15, was also performed. The addresses of the 120 children were collected, and plotted on the Taiwan map.

RESULTS

The groups in the center of Kaohsiung City lived mainly in urban areas with a population density of over 10,000 people per square kilometer, and the majority of the Kaohsiung groups on the outskirts of the city center lived in suburban areas with a population density of under 6000 people per square kilometer. There was no statistically significant difference between the city center and outskirt groups in terms of clinical presentation, laboratory, and imaging data. However, more ST131 clones, major pulsotype groups, and phylogenetic group B2 strains were found in the center of Kaohsiung than on the outskirts.

CONCLUSION

ESBL-producing E. coli clones may be more challenging to treat clinically. Most infections were community-acquired, and there appeared to be major pulsotype clones, mainly in urban areas. This reinforces the necessity of environmental surveillance and sanitary procedures for ESBL-producing E. coli.

Estimation of the Difference in Colistin Plasma Levels in Critically Ill Patients with Favorable or Unfavorable Clinical Outcomes

In recent decades, antimicrobial resistance (AMR) has led to an increased use of therapeutic alternatives. Among these options, colistin continues to be an option for the treatment of multi-resistant (MDR) Gram-negative bacterial infections. However, due to its high toxicity (nephrotoxicity and neurotoxicity) and narrow therapeutic window, colistin treatment must be utilized carefully. Colistin-treated patients have been observed to have higher mortality due to inadequate therapeutic levels. The objective of this study was to estimate the difference in colistin plasma levels in critically ill patients, and its relationship to favorable or unfavorable clinical outcomes. This prospective observational study was conducted between September 2017 and June 2020 at the Universidad de La Sabana Clinic, in patients who had been treated with colistimethate sodium (CMS) for at least 72 h until day 7 of drug treatment in the critical care unit of a university hospital. There were no statistically significant differences in colistin levels between groups with favorable or unfavorable clinical outcomes (0.16 SD vs. 0.54 SD p-value = 0.167). There was higher mortality in patients with subtherapeutic levels (18% vs. 0%), and additionally, there was a greater rate of renal failure in the group with higher therapeutic levels (50% vs. 20.7%). Due to the loss of power of the study, we were unable to demonstrate a possible difference between colistin levels related to favorable or unfavorable clinical outcomes at day 7. However, we recommend further studies to evaluate the impact of measuring levels in terms of mortality and security.

Early prediction models for extended-spectrum β-lactamase-producing Escherichia coli infection in emergency department: A protocol for systematic review and meta analysis

BACKGROUND

Resistance in gram-negative bacteria has gained great importance in recent decades and one reason is the rapid increase of extended spectrum β-lactamase (ESBL)-producing bacteria as a growing problem worldwide. The increasing proportion of ESBL-producing Enterobacteriaceae (ESBL-E) infections acquired in the emergency community is a new feature of ESBLs epidemiology. Early recognition of patients with extended-spectrum β-lactamase-producing Escherichia coli infection is important in the emergency department. To mitigate the burden on the healthcare system, while also providing the best possible care for patients, early recognition of the infection is needed.

METHODS

For the acquisition of required data of eligible prospective/retrospective cohort study or randomized controlled trials (RCTs), we will search for publications from PubMed, Web of science, EMBASE, Cochrane Library, Google scholar. Two independent reviewers will read the full English text of the articles, screened and selected carefully, removing duplication. Then we evaluate the quality and analyses data by Review Manager (V.5.4). Results data will be pooled and meta-analysis will be conducted if there's 2 eligible studies considered.

RESULTS

This systematic review and meta-analysis will evaluate the value of the early prediction models for Extended-spectrum β-lactamase-producing E coli infection in emergency department.

CONCLUSIONS

This systematic review and meta-analysis will provide clinical evidence for predicting Extended-spectrum β-lactamase-producing E coli infection in emergency department, inform our understanding of the value of the predictive model in predicting Extended-spectrum β-lactamase-producing E coli infection in emergency department in the early stage. The conclusions drawn from this study may be beneficial to patients, clinicians, and health-related policy makers.

STUDY REGISTRATION NUMBER

INPLASY202130049.