Outbreak of Pseudomonas aeruginosa Infections from a Contaminated Gastroscope Detected by Whole Genome Sequencing Surveillance

Epidemiology of healthcare-associated Pseudomonas aeruginosa in intensive care units: are sink drains to blame?

BACKGROUND

Pseudomonas aeruginosa (PA) is a common cause of healthcare-associated infection (PA-HAI) in the intensive care unit (ICU).

AIM

To describe the epidemiology of PA-HAI in ICUs in Ontario, Canada, and to identify episodes of sink-to-patient PA transmission.

METHODS

This was a prospective cohort study of patients in six ICUs from 2018 to 2019, with retrieval of PA clinical isolates, and PA-screening of antimicrobial-resistant organism surveillance rectal swabs, and of sink drain, air, and faucet samples. All PA isolates underwent whole-genome sequencing. PA-HAI was defined using US National Healthcare Safety Network criteria. ICU-acquired PA was defined as PA isolated from specimens obtained ≥48 h after ICU admission in those with prior negative rectal swabs. Sink-to-patient PA transmission was defined as ICU-acquired PA with close genomic relationship to isolate(s) previously recovered from sinks in a room/bedspace occupied 3-14 days prior to collection date of the relevant patient specimen.

FINDINGS

Over ten months, 72 PA-HAIs occurred among 60/4263 admissions. The rate of PA-HAI was 2.40 per 1000 patient-ICU-days; higher in patients who were PA-colonized on admission. PA-HAI was associated with longer stay (median: 26 vs 3 days uninfected; P < 0.001) and contributed to death in 22/60 cases (36.7%). Fifty-eight admissions with ICU-acquired PA were identified, contributing 35/72 (48.6%) PA-HAIs. Four patients with five PA-HAIs (6.9%) had closely related isolates previously recovered from their room/bedspace sinks.

CONCLUSION

Nearly half of PA causing HAI appeared to be acquired in ICUs, and 7% of PA-HAIs were associated with sink-to-patient transmission. Sinks may be an under-recognized reservoir for HAIs.

Residual risk of Pseudomonas aeruginosa waterborne contamination in an intensive care unit despite the presence of filters at all water points-of-use

OBJECTIVE

To assess the residual risk of waterborne contamination by Pseudomonas aeruginosa from a water network colonized by a single genotype [sequence type (ST) 299] despite the presence of antimicrobial filters in a medical intensive care unit (ICU).

METHODS

During the first 19-month period since the ICU opened, contamination of the water network was assessed monthly by collecting water upstream of the filters. Downstream water was also sampled to assess the efficiency of the filters. P. aeruginosa isolates from patients were collected and compared with the waterborne ST299 P. aeruginosa by multiplex-rep polymerase chain reaction (PCR), pulsed-field gel electrophoresis (PFGE) and whole-genome sequencing. Cross-transmission events by other genotypes of P. aeruginosa were also assessed.

RESULTS

Overall, 1.3% of 449 samples of filtered water were positive for P. aeruginosa in inoculum, varying between 1 and 104 colony-forming units/100 mL according to the tap. All P. aeruginosa hydric isolates belonged to ST299 and displayed fewer than two single nucleotide polymorphisms (SNPs). Among 278 clinical isolates from 122 patients, 10 isolates in five patients showed identical profiles to the hydric ST299 clone on both multiplex-rep PCR and PFGE, and differed by an average of fewer than five SNPs, confirming the water network reservoir as the source of contamination by P. aeruginosa for 4.09% of patients. Cross-transmission events by other genotypes of P. aeruginosa were responsible for the contamination of 1.75% of patients.

DISCUSSION/CONCLUSION

Antimicrobial filters are not sufficient to protect patients from waterborne pathogens when the water network is highly contaminated. A microbiological survey of filtered water may be needed in units hosting patients at risk of P. aeruginosa infections, even when all water points-of-use are fitted with filters.

Real-time genomic epidemiologic investigation of a multispecies plasmid-associated hospital outbreak of NDM-5-producing Enterobacterales infections

OBJECTIVES

New Delhi metallo-β-lactamase (NDM) is an emergent mechanism of carbapenem resistance associated with high mortality and limited treatment options. Because the blaNDM resistance gene is often carried on plasmids, traditional infection prevention and control (IP&C) surveillance methods and reactive whole genome sequencing (WGS) may not detect plasmid transfer in multispecies outbreaks.

METHODS

Initial outbreak detection of NDM-producing Enterobacterales identified at an acute care hospital occurred via traditional IP&C methods and was supplemented by real-time WGS surveillance performed weekly. To resolve NDM-encoding plasmids, we performed long-read sequencing and constructed hybrid assemblies. WGS data for suspected outbreaks was shared with the IP&C team for assessment and intervention.

RESULTS

We observed a multispecies outbreak of NDM-5-producing Enterobacterales isolated from 15 patients between February 2021 and February 2023. The 19 clinical and surveillance isolates sequenced included 7 bacterial species encoding the same NDM-5 plasmid. WGS surveillance and epidemiologic investigation characterized 10 horizontal plasmid transfer events and 6 bacterial transmission events between patients in varying hospital units.

CONCLUSIONS

Our investigation revealed a complex, multispecies outbreak of NDM involving multiple plasmid transfer and bacterial transmission events. We highlight the utility of combining traditional IP&C and prospective genomic methods in identifying and containing plasmid-associated outbreaks.

Use of whole genomic sequencing to detect New Delhi metallo-B-lactamase (NDM)-producing Escherichia coli outbreak associated with endoscopic procedures

BACKGROUND

Whole-genome sequencing (WGS) has emerged as an alternative genotyping tool for outbreak investigations in the healthcare setting. We describe the investigation and control of a New Delhi metallo-B-lactamase (NDM)-producing Escherichia coli cluster in Southeast Michigan.

METHODS

Michigan Bureau of Laboratories identified several closely related NDM-producing E. coli isolates with WGS. An epidemiologic investigation, including case-control study, assessment of infection control practices, and endoscope culturing, was performed to identify source of transmission. Targeted screening of potentially exposed patients was performed following identification of probable source.

RESULTS

Between July 2021 and February 2023, nine patients were identified. Phylogenetic analysis confirmed the isolates were closely related with less than 26 single nucleotide polymorphism (SNP) differences between isolates, suggesting an epidemiological link. Eight (89%) patients had a duodenoscope and/or gastroscope exposure. Cases were compared with 23 controls. Cases had significantly higher odds of exposure to duodenoscopes (odds ratio 15.0; 95% CI, 1.8-142.2; P = .015). The mean incubation period, estimated as date of procedure to positive index culture, was 86 days (range, 1-320 days). No lapses in endoscope reprocessing were identified; NDM-producing E. coli was not recovered from reprocessed endoscopes or during targeted screening. No additional cases were identified after removal of implicated gastroscopes and replacement of duodenoscope with disposable end caps.

CONCLUSIONS

In this investigation, WGS was utilized to identify transmission of an NDM-producing E. coli outbreak associated with endoscope exposure. Coupled with epidemiologic data, WGS can facilitate outbreak investigations by rapidly identifying linked cases and potential sources to prevent further transmission.

WITHDRAWN: Evaluation of Fourier Transform Infrared spectroscopy (IR Biotyper) as a complement to Whole genome sequencing (WGS) to characterise Enterobacter cloacae , Citrobacter freundii and Klebsiella pneumoniae isolates recovered from hospital sinks

The authors have withdrawn their manuscript due to becoming aware of methodology issues related to the curation of the training set used to determine cut-off values for Biotyper cluster assignation and lack of replicate measurements on different days for the isolates analysed. It is therefore unclear whether the conclusions of the manuscript are founded and no further work is possible to correct these issues as the instrument is no longer available to the authors. If you have any questions, please contact the corresponding author.

The clinical and epidemiological impacts of whole genomic sequencing on bacterial and virological agents

Whole Genome Sequencing (WGS) is a molecular biology tool consisting in the sequencing of the entire genome of a given organism. Due to its ability to provide the finest available resolution of bacterial and virological genetics, it is used at several levels in the field of infectiology. On an individual scale and through application of a single technique, it enables the typological identification and characterization of strains, the characterization of plasmids, and enhanced search for resistance genes and virulence factors. On a collective scale, it enables the characterization of strains and the determination of phylogenetic links between different microorganisms during community outbreaks and healthcare-associated epidemics. The information provided by WGS enables real-time monitoring of strain-level epidemiology on a worldwide scale, and facilitates surveillance of the resistance dissemination and the introduction or emergence of pathogenic variants in humans or their environment. There are several possible approaches to completion of an entire genome. The choice of one method rather than another is essentially dictated by the matrix, either a clinical sample or a culture isolate, and the clinical objective. WGS is an advanced technology that remains costly despite a gradual decrease in its expenses, potentially hindering its implementation in certain laboratories and thus its use in routine microbiology. Even though WGS is making steady inroads as a reference method, efforts remain needed in view of so harmonizing its interpretations and decreasing the time to generation of conclusive results.

Performance of a single-use gastroscope for esophagogastroduodenoscopy: Prospective evaluation

Background and study aims Reprocessing reusable endoscopes is challenging due to their non-sterilizable nature. Disinfection has been shown to have a significant risk of failure with serious consequences. Single-use endoscopes can eliminate contamination risk and reduce workflow delays caused by reprocessing. This study evaluated the clinical performance of single-use gastroscopes in patients undergoing esophagogastroduodenoscopy (EGD). Patients and methods In this case series, 60 patients underwent EGD using single-use gastroscopes, with 34 procedures in the endoscopy department and 26 in the intensive care unit. The primary outcome was successful completion of the intended EGD objective. Furthermore, certified endoscopists assessed device performance on a five-point Likert scale (ranging from 1-"much worse" to 5-"much better"), considering their experience with a reusable gastroscope. Results Successful completion of EGDs using only the single-use gastroscope was achieved in 58 of 60 cases (96.7%). In two cases, crossover to an ultra-slim endoscope was necessary to either reach the esophageal stenosis or to transverse the stenosis. Overall satisfaction was rated as comparable to reusable scopes in 51 of 56 cases (91.1%) and inferior in five cases (8.9%). The lower weight of the single-use gastroscope was rated as superior in 42 of 60 cases (70.0%). Drawbacks included reduced image quality (23 of 45 cases; 51.1%). Feedback included the absence of a freeze button, lens cleaning issues, and small image size. Conclusions Single-use gastroscopes exhibited a high EGD completion rate and effectiveness for various indications. Further research should focus on evaluating the implementation of single-use gastroscopes in a comprehensive context, considering clinical effectiveness, costs, and environmental impact.

Two Artificial Tears Outbreak-Associated Cases of Extensively Drug-Resistant Pseudomonas aeruginosa Detected Through Whole Genome Sequencing-Based Surveillance

We describe 2 cases of extensively drug-resistant Pseudomonas aeruginosa infection caused by a strain of public health concern, as it was recently associated with a nationwide outbreak of contaminated artificial tears. Both cases were detected through database review of genomes in the Enhanced Detection System for Hospital-Associated Transmission (EDS-HAT), a routine genome sequencing-based surveillance program. We generated a high-quality reference genome for the outbreak strain from an isolate from our center and examined the mobile elements encoding blaVIM-80 and bla-GES-9 carbapenemases. We used publicly available Pseudomonas aeruginosa genomes to explore the genetic relatedness and antimicrobial resistance genes of the outbreak strain.

Staphylococcus epidermidis joint isolates: Whole-genome sequencing demonstrates evidence of hospital transmission and common antimicrobial resistance

OBJECTIVE

We investigated genetic, epidemiologic, and environmental factors contributing to positive Staphylococcus epidermidis joint cultures.

DESIGN

Retrospective cohort study with whole-genome sequencing (WGS).

PATIENTS

We identified S. epidermidis isolates from hip or knee cultures in patients with 1 or more prior corresponding intra-articular procedure at our hospital.

METHODS

WGS and single-nucleotide polymorphism-based clonality analyses were performed, including species identification, in silico multilocus sequence typing (MLST), phylogenomic analysis, and genotypic assessment of the prevalence of specific antibiotic resistance and virulence genes. Epidemiologic review was performed to compare cluster and noncluster cases.

RESULTS

In total, 60 phenotypically distinct S. epidermidis isolates were identified. After removal of duplicates and impure samples, 48 isolates were used for the phylogenomic analysis, and 45 (93.7%) isolates were included in the clonality analysis. Notably, 5 S. epidermidis strains (10.4%) showed phenotypic susceptibility to oxacillin yet harbored mecA, and 3 (6.2%) strains showed phenotypic resistance despite not having mecA. Smr was found in all isolates, and mupA positivity was not observed. We also identified 6 clonal clusters from the clonality analysis, which accounted for 14 (31.1%) of the 45 S. epidermidis isolates. Our epidemiologic investigation revealed ties to common aspirations or operative procedures, although no specific common source was identified.

CONCLUSIONS

Most S. epidermidis isolates from clinical joint samples are diverse in origin, but we identified an important subset of 31.1% that belonged to subclinical healthcare-associated clusters. Clusters appeared to resolve spontaneously over time, suggesting the benefit of routine hospital infection control and disinfection practices.

Innovative Techniques for Infection Control and Surveillance in Hospital Settings and Long-Term Care Facilities: A Scoping Review

Healthcare-associated infections (HAIs) pose significant challenges in healthcare systems, with preventable surveillance playing a crucial role. Traditional surveillance, although effective, is resource-intensive. The development of new technologies, such as artificial intelligence (AI), can support traditional surveillance in analysing an increasing amount of health data or meeting patient needs. We conducted a scoping review, following the PRISMA-ScR guideline, searching for studies of new digital technologies applied to the surveillance, control, and prevention of HAIs in hospitals and LTCFs published from 2018 to 4 November 2023. The literature search yielded 1292 articles. After title/abstract screening and full-text screening, 43 articles were included. The mean study duration was 43.7 months. Surgical site infections (SSIs) were the most-investigated HAI and machine learning was the most-applied technology. Three main themes emerged from the thematic analysis: patient empowerment, workload reduction and cost reduction, and improved sensitivity and personalization. Comparative analysis between new technologies and traditional methods showed different population types, with machine learning methods examining larger populations for AI algorithm training. While digital tools show promise in HAI surveillance, especially for SSIs, challenges persist in resource distribution and interdisciplinary integration in healthcare settings, highlighting the need for ongoing development and implementation strategies.

A prospective bacterial whole-genome-sequencing-based surveillance programme for comprehensive early detection of healthcare-associated infection transmission in paediatric oncology patients

BACKGROUND

Bacterial whole-genome sequencing (WGS) and determination of genetic relatedness is an important tool for investigation of epidemiologically suspected outbreaks.

AIM

This prospective cohort study evaluated a comprehensive, prospective bacterial WGS-based surveillance programme for early detection of transmission of most bacterial pathogens among patients at a paediatric oncology hospital.

METHODS

Cultured bacterial isolates from clinical diagnostic specimens collected prospectively from both inpatient and outpatient encounters between January 2019 and December 2021 underwent routine WGS and core genome multi-locus sequence typing to determine isolates' relatedness. Previously collected isolates from January to December 2018 were retrospectively analysed for identification of prior or ongoing transmission. Multi-patient clusters were investigated to identify potential transmission events based on temporal and spatial epidemiological links and interventions were introduced.

FINDINGS

A total of 1497 bacterial isolates from 1025 patients underwent WGS. A total of 259 genetically related clusters were detected, of which 18 (6.9%) multi-patient clusters involving 38 (3.7%) patients were identified. Sixteen clusters involved two patients each, and two clusters involved three patients. Following investigation, epidemiologically plausible transmission links were identified in five (27.8%) multi-patient clusters. None of the multi-patient clusters were suspected by conventional epidemiological surveillance.

CONCLUSION

Bacterial WGS-based surveillance for early detection of hospital transmission detected several limited multi-patient clusters that were unrecognized by conventional epidemiological methods. Genomic surveillance helped efficiently focus interventions while reducing unnecessary investigations.

Sensitivity of National Healthcare Safety Network definitions to capture healthcare-associated transmission identified by whole-genome sequencing surveillance

The National Healthcare Safety Network (NHSN) definitions are critical for standardizing healthcare-associated infection surveillance in US healthcare facilities. However, their use in accurately detecting healthcare-associated transmission (HAT) has not been measured. Using whole-genome sequencing surveillance data, we show that the NHSN has a sensitivity of 44.4% in detecting HAT.

Genomic Epidemiologic Investigation of a Multispecies Hospital Outbreak of NDM-5-Producing Enterobacterales Infections

Background

New Delhi metallo-β-lactamase (NDM) represents an emergent mechanism of carbapenem resistance associated with high mortality and limited antimicrobial treatment options. Because the blaNDM resistance gene is often carried on plasmids, traditional infection prevention and control (IP&C) surveillance methods like speciation, antimicrobial resistance testing, and reactive whole genome sequencing (WGS) may not detect plasmid transfer in multispecies outbreaks.

Methods

Initial outbreak detection of NDM-producing Enterobacterales identified at an acute care hospital occurred via traditional IP&C methods and was supplemented by real-time WGS surveillance, which was performed weekly using the Illumina platform. To resolve NDM-encoding plasmids, we performed long-read Oxford Nanopore sequencing and constructed hybrid assemblies using Illumina and Nanopore sequencing data. Reports of relatedness between NDM-producing organisms and reactive WGS for suspected outbreaks were shared with the IP&C team for assessment and intervention.

Findings

We observed a multispecies outbreak of NDM-5-producing Enterobacterales isolated from 15 patients between February 2021 and February 2023. The 19 clinical and surveillance isolates sequenced included seven bacterial species and each encoded the same NDM-5 plasmid, which showed high homology to NDM plasmids previously observed in Asia. WGS surveillance and epidemiologic investigation characterized ten horizontal plasmid transfer events and six bacterial transmission events between patients housed in varying hospital units. Transmission prevention focused on enhanced observation and adherence to basic infection prevention measures.

Interpretation

Our investigation revealed a complex, multispecies outbreak of NDM that involved multiple plasmid transfer and bacterial transmission events, increasing the complexity of outbreak identification and transmission prevention. Our investigation highlights the utility of combining traditional IP&C and prospective genomic methods in identifying and containing plasmid-associated outbreaks.

Funding

This work was funded in part by the National Institute of Allergy and Infectious Diseases, National Institutes of Health (NIH) (R01AI127472) (R21AI1783691).

In host evolution of beta lactam resistance during active treatment for Pseudomonas aeruginosa bacteremia

Multidrug-resistant (MDR) Pseudomonas aeruginosa has been declared a serious threat by the United States Centers for Disease Control and Prevention. Here, we used whole genome sequencing (WGS) to investigate recurrent P. aeruginosa bloodstream infections in a severely immunocompromised patient. The infections demonstrated unusual, progressive increases in resistance to beta lactam antibiotics in the setting of active treatment with appropriate, guideline-directed agents. WGS followed by comparative genomic analysis of isolates collected over 44 days demonstrated in host evolution of a single P. aeruginosa isolate characterized by stepwise acquisition of two de-novo genetic resistance mechanisms over the course of treatment. We found a novel deletion affecting the ampC repressor ampD and neighboring gene ampE, which associated with initial cefepime treatment failure. This was followed by acquisition of a porin nonsense mutation, OprD, associated with resistance to carbapenems. This study highlights the potential for in-host evolution of P. aeruginosa during bloodstream infections in severely immunocompromised patients despite appropriate antimicrobial therapy. In addition, it demonstrates the utility of WGS for understanding unusual resistance patterns in the clinical context.

Two artificial tears outbreak-associated cases of XDR Pseudomonas aeruginosa detected through whole genome sequencing-based surveillance

We describe two cases of XDR Pseudomonas aeruginosa infection caused by a strain of public health concern recently associated with a nationwide outbreak of contaminated artificial tears. Both cases were detected through database review of genomes in the Enhanced Detection System for Hospital-Associated Transmission (EDS-HAT), a routine genome sequencing-based surveillance program. We generated a high-quality reference genome for the outbreak strain from one of the case isolates from our center and examined the mobile elements encoding bla VIM-80 and bla GES-9 carbapenemases. We then used publicly available P. aeruginosa genomes to explore the genetic relatedness and antimicrobial resistance genes of the outbreak strain.

Prevalence, antibiotic resistance patterns, and biofilm formation ability of Enterobacterales recovered from food of animal origin in Egypt

Background and Aim: The majority of animal-derived food safety studies have focused on foodborne zoonotic agents; however, members of the opportunistic Enterobacteriaceae (Ops) family are increasingly implicated in foodborne and public health crises due to their robust evolution of acquiring antimicrobial resistance and biofilms, consequently require thorough characterization, particularly in the Egyptian food sector. Therefore, this study aimed to determine the distribution and prevalence of Enterobacteriaceae family members in animal-derived foods, as well as their resistance to important antimicrobials and biofilm-forming potential. Materials and Methods: A total of 274 beef, rabbit meat, chicken meat, egg, butter, and milk samples were investigated for the presence of Enterobacteriaceae. All isolated strains were first recognized using traditional microbiological techniques. Following that, matrix-assisted laser desorption ionization-time of flight mass spectrometry was used to validate the Enterobacteriaceae's identity. The isolated enterobacteria strains were tested on disk diffusion and crystal violet quantitative microtiter plates to determine their antibiotic resistance and capacity to form biofilms. Results: There have been thirty isolates of Enterobacteriaceae from seven different species and four genera. Out of the three food types, Pseudomonas aeruginosa had the highest prevalence rate (4.1%). With three species, Enterobacter genera had the second-highest prevalence (3.28%) across five different food categories. In four different food types, the Klebsiella genera had the second-highest distribution and third-highest incidence (2.55%). Almost all isolates, except three Proteus mirabilis, showed prominent levels of resistance, particularly to beta-lactam antibiotics. Except for two Enterobacter cloacae and three P. mirabilis isolates, all isolates were classified as multidrug-resistant (MDR) or extensively multidrug-resistant (XDR). The multiple antibiotic resistance index (MARI) of the majority of isolates dropped between 0.273 and 0.727. The highest MARI was conferred by Klebsiella pneumoniae, at 0.727. Overall, 83.33% of the isolates had strong biofilm capacity, while only 16.67% exhibited moderate capacity. Conclusion: The MDR, XDR, and strong biofilm indicators confirmed in 83.33% of the currently tested Enterobacteriaceae from animal-derived foods suggest that, if not addressed, there may be rising risks to Egypt's economy and public health.

The future of automated infection detection: Innovation to transform practice (Part III/III)

Current methods of emergency-room-based syndromic surveillance were insufficient to detect early community spread of severe acute respiratory coronavirus virus 2 (SARS-CoV-2) in the United States, which slowed the infection prevention and control response to the novel pathogen. Emerging technologies and automated infection surveillance have the potential to improve upon current practice standards and to revolutionize the practice of infection detection, prevention and control both inside and outside of healthcare settings. Genomics, natural language processing, and machine learning can be leveraged to improve identification of transmission events and aid and evaluate outbreak response. In the near future, automated infection detection strategies can be used to advance a true "Learning Healthcare System" that will support near-real-time quality improvement efforts and advance the scientific basis for the practice of infection control.

New Variants of Pseudomonas aeruginosa High-Risk Clone ST233 Associated with an Outbreak in a Mexican Paediatric Hospital

Recent multidrug resistance in Pseudomonas aeruginosa has favoured the adaptation and dissemination of worldwide high-risk strains. In June 2018, 15 P. aeruginosa strains isolated from patients and a contaminated multi-dose meropenem vial were characterized to assess their association to an outbreak in a Mexican paediatric hospital. The strains were characterized by antibiotic susceptibility profiling, virulence factors’ production, and biofilm formation. The clonal relationship among isolates was determined with pulse-field gel electrophoresis (PFGE) and multi-locus sequence typing (MLST) sequencing. Repressor genes for the MexAB-OprM efflux pump were sequenced for haplotype identification. Of the strains, 60% were profiled as extensively drug-resistant (XDR), 33% as multidrug-resistant (MDR), and 6.6% were classified as sensitive (S). All strains presented intermediate resistance to colistin, and 80% were sensitive to aztreonam. Pyoverdine was the most produced virulence factor. The PFGE technique was performed for the identification of the outbreak, revealing eight strains with the same electrophoretic pattern. ST235 and ten new sequence types (STs) were identified, all closely related to ST233. ST3241 predominated in 26.66% of the strains. Twenty-five synonymous and seventeen nonsynonymous substitutions were identified in the regulatory genes of the MexAB-OprM efflux pump, and nalC was the most variable gene. Six different haplotypes were identified. Strains from the outbreak were metallo-β-lactamases and phylogenetically related to the high-risk clone ST233.

Genomic Diversity of Hospital-Acquired Infections Revealed through Prospective Whole-Genome Sequencing-Based Surveillance

Healthcare-associated infections (HAIs) cause mortality, morbidity, and waste of health care resources. HAIs are also an important driver of antimicrobial resistance, which is increasing around the world. Beginning in November 2016, we instituted an initiative to detect outbreaks of HAIs using prospective whole-genome sequencing-based surveillance of bacterial pathogens collected from hospitalized patients. Here, we describe the diversity of bacteria sampled from hospitalized patients at a single center, as revealed through systematic analysis of bacterial isolate genomes. We sequenced the genomes of 3,004 bacterial isolates from hospitalized patients collected over a 25-month period. We identified bacteria belonging to 97 distinct species, which were distributed among 14 groups of related species. Within these groups, isolates could be distinguished from one another by both average nucleotide identity (ANI) and principal-component analysis of accessory genes (PCA-A). Core genome genetic distances and rates of evolution varied among species, which has practical implications for defining shared ancestry during outbreaks and for our broader understanding of the origins of bacterial strains and species. Finally, antimicrobial resistance genes and putative mobile genetic elements were frequently observed, and our systematic analysis revealed patterns of occurrence across the different species sampled from our hospital. Overall, this study shows how understanding the population structure of diverse pathogens circulating in a single health care setting can improve the discriminatory power of genomic epidemiology studies and can help define the processes leading to strain and species differentiation. IMPORTANCE Hospitalized patients are at increased risk of becoming infected with antibiotic-resistant organisms. We used whole-genome sequencing to survey and compare over 3,000 clinical bacterial isolates collected from hospitalized patients at a large medical center over a 2-year period. We identified nearly 100 different bacterial species, which we divided into 14 different groups of related species. When we examined how genetic relatedness differed between species, we found that different species were likely evolving at different rates within our hospital. This is significant because the identification of bacterial outbreaks in the hospital currently relies on genetic similarity cutoffs, which are often applied uniformly across organisms. Finally, we found that antibiotic resistance genes and mobile genetic elements were abundant and were shared among the bacterial isolates we sampled. Overall, this study provides an in-depth view of the genomic diversity and evolutionary processes of bacteria sampled from hospitalized patients, as well as genetic similarity estimates that can inform hospital outbreak detection and prevention efforts.

Whole-genome sequencing surveillance and machine learning for healthcare outbreak detection and investigation: A systematic review and summary

BACKGROUND

Whole-genome sequencing (WGS) has traditionally been used in infection prevention to confirm or refute the presence of an outbreak after it has occurred. Due to decreasing costs of WGS, an increasing number of institutions have been utilizing WGS-based surveillance. Additionally, machine learning or statistical modeling to supplement infection prevention practice have also been used. We systematically reviewed the use of WGS surveillance and machine learning to detect and investigate outbreaks in healthcare settings.

METHODS

We performed a PubMed search using separate terms for WGS surveillance and/or machine-learning technologies for infection prevention through March 15, 2021.

RESULTS

Of 767 studies returned using the WGS search terms, 42 articles were included for review. Only 2 studies (4.8%) were performed in real time, and 39 (92.9%) studied only 1 pathogen. Nearly all studies (n = 41, 97.6%) found genetic relatedness between some isolates collected. Across all studies, 525 outbreaks were detected among 2,837 related isolates (average, 5.4 isolates per outbreak). Also, 35 studies (83.3%) only utilized geotemporal clustering to identify outbreak transmission routes. Of 21 studies identified using the machine-learning search terms, 4 were included for review. In each study, machine learning aided outbreak investigations by complementing methods to gather epidemiologic data and automating identification of transmission pathways.

CONCLUSIONS

WGS surveillance is an emerging method that can enhance outbreak detection. Machine learning has the potential to identify novel routes of pathogen transmission. Broader incorporation of WGS surveillance into infection prevention practice has the potential to transform the detection and control of healthcare outbreaks.

Gastrointestinal endoscope contamination rates - elevators are not only to blame: a systematic review and meta-analysis

Background and study aims  Duodenoscopes that are contaminated due to inadequate reprocessing are well-documented. However, studies have demonstrated poor reprocessing of other kinds of endoscopes as well, including echoendoscopes, gastroscopes, and colonoscopes. We estimated the contamination rate beyond the elevator of gastrointestinal endoscopes based on available data. Methods  We searched PubMed and Embase from January 1, 2010 to October 10, 2020, for studies investigating contamination rates of reprocessed gastrointestinal endoscopes. A random-effects model was used to calculate the contamination rate of patient-ready gastrointestinal endoscopes. Subgroup analyses were conducted to investigate differences among endoscope types, countries, and colony-forming unit (CFU) thresholds. Results  Twenty studies fulfilled the inclusion criteria, including 1,059 positive cultures from 7,903 samples. The total contamination rate was 19.98 % ± 0.024 (95 % confidence interval [Cl]: 15.29 %-24.68 %; I ²  = 98.6 %). The contamination rates of colonoscope and gastroscope channels were 31.95 % ± 0.084 and 28.22 % ± 0.076, respectively. Duodenoscope channels showed a contamination rate of 14.41 % ± 0.029. The contamination rates among studies conducted in North America and Europe were 6.01 % ± 0.011 and 18.16% ± 0.053 %, respectively. The contamination rate among studies using a CFU threshold > 20 showed contamination of 30.36 % ± 0.094, whereas studies using a CFU threshold < 20 showed a contamination rate of 11 % ± 0.026. Conclusions  On average, 19.98 % of reprocessed gastrointestinal endoscopes may be contaminated when used in patients and varies between different geographies. These findings highlight that the elevator mechanism is not the only obstacle when reprocessing reusable endoscopes; therefore, guidelines should recommend more surveillance of the endoscope channels as well.

Artificial Intelligence and the Risk for Intuition Decline in Clinical Medicine

Artificial intelligence (AI) is revolutionizing big data analytics. In this issue of The American Journal of Gastroenterology, Ahn et al. introduce the AI-cirrhosis-electrocardiogram score that can grade the electrophysiologic cardiac changes present in patients with cirrhosis. Apart from showing excellent accuracy to identify cirrhosis, the AI-cirrhosis-electrocardiogram algorithm identified a biological gradient and signal reversibility after transplantation. Clinical applicability needs to be determined. Some concerns inherent to the use of AI are discussed, including the need to verify that the quality of data used for machine training is optimal. The black box nature of AI-identified associations is discussed, along with the lack of pathophysiologic coherence allowing intuitive medical reasoning.

Whole Genome Sequencing Surveillance and Machine Learning of the Electronic Health Record for Enhanced Healthcare Outbreak Detection

BACKGROUND

Most hospitals use traditional infection prevention (IP) methods for outbreak detection. We developed the Enhanced Detection System for Healthcare-Associated Transmission (EDS-HAT), which combines whole genome sequencing (WGS) surveillance and machine learning (ML) of the electronic health record (EHR) to identify undetected outbreaks and the responsible transmission routes, respectively.

METHODS

We performed WGS surveillance of healthcare-associated bacterial pathogens from November 2016 to November 2018. EHR ML was used to identify the transmission routes for WGS-detected outbreaks, which were investigated by an IP expert. Potential infections prevented were estimated and compared to traditional IP practice during the same period.

RESULTS

Of 3,165 isolates, there were 2,752 unique patient isolates in 99 clusters involving 297 (10.8%) patient isolates were identified by WGS; clusters ranged from 2-14 patients. At least one transmission route was detected for 65.7% of clusters. During the same time, traditional IP investigation prompted WGS for 15 suspected outbreaks involving 133 patients, for which transmission events were identified for 5 (3.8%). If EDS-HAT had been running in real-time, 25-63 transmissions could have been prevented. EDS-HAT was found to be cost-saving and more effective than traditional IP practice, with overall savings of $192,408 - $692,532.

CONCLUSION

EDS-HAT detected multiple outbreaks not identified using traditional IP methods, correctly identified the transmission routes for most outbreaks, and would save the hospital substantial costs. Traditional IP practice misidentified outbreaks for which transmission did not occur. WGS surveillance combined with EHR ML has the potential to save costs and enhance patient safety.

mSphere of Influence: Whole-Genome Sequencing, a Vital Tool for the Interruption of Nosocomial Transmission

Ahmed Babiker’s work focuses on the clinical and genomic epidemiology of multidrug-resistant health care-associated pathogens and other high-consequence pathogens. In this mSphere of Influence article, he reflects on how the paper “Tracking a Hospital Outbreak of Carbapenem-Resistant Klebsiella pneumoniae with Whole-Genome Sequencing” by author Evan S.

Ahmed Babiker’s work focuses on the clinical and genomic epidemiology of multidrug-resistant health care-associated pathogens and other high-consequence pathogens. In this mSphere of Influence article, he reflects on how the paper “Tracking a Hospital Outbreak of Carbapenem-Resistant Klebsiella pneumoniae with Whole-Genome Sequencing” by Evan S. Snitkin et al. (Sci Transl Med 4:148ra116, 2012, https://doi.org/10.1126/scitranslmed.3004129) impacted his thinking on the use of whole-genome sequencing for nosocomial transmission investigation.