Background: Infection prevention and control (IPC) workflows are often retrospective and manual. New tools, however, have entered the field to facilitate rapid prospective monitoring of infections in hospitals. Although artificial intelligence (AI)–enabled platforms facilitate timely, on-demand integration of clinical data feeds with pathogen whole-genome sequencing (WGS), a standardized workflow to fully harness the power of such tools is lacking. We report a novel, evidence-based workflow that promotes quicker infection surveillance via AI-assisted clinical and WGS data analysis. The algorithm suggests clusters based on a combination of similar minimum inhibitory concentration (MIC) data, timing of sample collection, and shared location stays between patients. It helps to proactively guide IPC professionals during investigation of infectious outbreaks and surveillance of multidrug-resistant organisms and healthcare-acquired infections. Methods: Our team established a 1-year workgroup comprised of IPC practitioners, clinical experts, and scientists in the field. We held weekly roundtables to study lessons learned in an ongoing surveillance effort at a tertiary care hospital—utilizing Philips IntelliSpace Epidemiology (ISEpi), an AI-powered system—to understand how such a tool can enhance practice. Based on real-time case discussions and evidence from the literature, a workflow guidance tool and checklist were codified. Results: In our workflow, data-informed clusters posed by ISEpi underwent triage and expert follow-up analysis to assess: (1) likelihood of transmission(s); (2) potential vector(s) identity; (3) need to request WGS; and (4) intervention(s) to be pursued, if warranted. In a representative sample (spanning October 17, 2019, to November 7, 2019) of 67 total isolates suggested for inclusion in 19 unique cluster investigations, we determined that 9 investigations merited follow-up. Collectively, these 9 investigations involved 21 patients and required 115 minutes to review in ISEpi and an additional 70 minutes of review outside of ISEpi. After review, 6 investigations were deemed unlikely to represent a transmission; the other 3 had potential to represent transmission for which interventions would be performed. Conclusions: This study offers an important framework for adaptation of existing infection control workflow strategies to leverage the utility of rapidly integrated clinical and WGS data. This workflow can also facilitate time-sensitive decisions regarding sequencing of specific pathogens given the preponderance of available clinical data supporting investigations. In this regard, our work sets a new standard of practice: precision infection prevention (PIP). Ongoing effort is aimed at development of AI-powered capabilities for enterprise-level quality and safety improvement initiatives.

Funding: Philips Healthcare provided support for this study.

Disclosures: Alan Doty and Juan Jose Carmona report salary from Philips Healthcare.

Background: Automated testing instruments (ATIs) are commonly used by clinical microbiology laboratories to perform antimicrobial susceptibility testing (AST), whereas public health laboratories may use established reference methods such as broth microdilution (BMD). We investigated discrepancies in carbapenem minimum inhibitory concentrations (MICs) among Enterobacteriaceae tested by clinical laboratory ATIs and by reference BMD at the CDC. Methods: During 2016–2018, we conducted laboratory- and population-based surveillance for carbapenem-resistant Enterobacteriaceae (CRE) through the CDC Emerging Infections Program (EIP) sites (10 sites by 2018). We defined an incident case as the first isolation of Enterobacter spp (E. cloacae complex or E. aerogenes), Escherichia coli, Klebsiella pneumoniae, K. oxytoca, or K. variicola resistant to doripenem, ertapenem, imipenem, or meropenem from normally sterile sites or urine identified from a resident of the EIP catchment area in a 30-day period. Cases had isolates that were determined to be carbapenem-resistant by clinical laboratory ATI MICs (MicroScan, BD Phoenix, or VITEK 2) or by other methods, using current Clinical and Laboratory Standards Institute (CLSI) criteria. A convenience sample of these isolates was tested by reference BMD at the CDC according to CLSI guidelines. Results: Overall, 1,787 isolates from 112 clinical laboratories were tested by BMD at the CDC. Of these, clinical laboratory ATI MIC results were available for 1,638 (91.7%); 855 (52.2%) from 71 clinical laboratories did not confirm as CRE at the CDC. Nonconfirming isolates were tested on either a MicroScan (235 of 462; 50.9%), BD Phoenix (249 of 411; 60.6%), or VITEK 2 (371 of 765; 48.5%). Lack of confirmation was most common among E. coli (62.2% of E. coli isolates tested) and Enterobacter spp (61.4% of Enterobacter isolates tested) (Fig. 1A), and among isolates testing resistant to ertapenem by the clinical laboratory ATI (52.1%, Fig. 1B). Of the 1,388 isolates resistant to ertapenem in the clinical laboratory, 1,006 (72.5%) were resistant only to ertapenem. Of the 855 nonconfirming isolates, 638 (74.6%) were resistant only to ertapenem based on clinical laboratory ATI MICs. Conclusions: Nonconfirming isolates were widespread across laboratories and ATIs. Lack of confirmation was most common among E. coli and Enterobacter spp. Among nonconfirming isolates, most were resistant only to ertapenem. These findings may suggest that ATIs overcall resistance to ertapenem or that isolate transport and storage conditions affect ertapenem resistance. Further investigation into this lack of confirmation is needed, and CRE case identification in public health surveillance may need to account for this phenomenon.

Funding: None

Disclosures: None

Background: Infection prevention surveillance for cross transmission is often performed by manual review of microbiologic culture results to identify geotemporally related clusters. However, the sensitivity and specificity of this approach remains uncertain. Whole-genome sequencing (WGS) analysis can help provide a gold-standard for identifying cross-transmission events. Objective: We employed a published WGS program, the Philips IntelliSpace Epidemiology platform, to compare accuracy of two surveillance methods: (i.) a virtual infection practitioner (VIP) with perfect recall and automated analysis of antibiotic susceptibility testing (AST), sample collection timing, and patient location data and (ii) a novel clinical matching (CM) algorithm that provides cluster suggestions based on a nuanced weighted analysis of AST data, timing of sample collection, and shared location stays between patients. Methods: WGS was performed routinely on inpatient and emergency department isolates of Enterobacter cloacae, Enterococcus faecium, Klebsiella pneumoniae, and Pseudomonas aeruginosa at an academic medical center. Single-nucleotide variants (SNVs) were compared within core genome regions on a per-species basis to determine cross-transmission clusters. Moreover, one unique strain per patient was included within each analysis, and duplicates were excluded from the final results. Results: Between May 2018 and April 2019, clinical data from 121 patients were paired with WGS data from 28 E. cloacae, 21 E. faecium, 61 K. pneumoniae, and 46 P. aeruginosa isolates. Previously published SNV relatedness thresholds were applied to define genomically related isolates. Mapping of genomic relatedness defined clusters as follows: 4 patients in 2 E. faecium clusters and 2 patients in 1 P. aeruginosa cluster. The VIP method identified 12 potential clusters involving 28 patients, all of which were “pseudoclusters.” Importantly, the CM method identified 7 clusters consisting of 27 patients, which included 1 true E. faecium cluster of 2 patients with genomically related isolates. Conclusions: In light of the WGS data, all of the potential clusters identified by the VIP were pseudoclusters, lacking sufficient genomic relatedness. In contrast, the CM method showed increased sensitivity and specificity: it decreased the percentage of pseudoclusters by 14% and it identified a related genomic cluster of E. faecium. These findings suggest that integrating clinical data analytics and WGS is likely to benefit institutions in limiting expenditure of resources on pseudoclusters. Therefore, WGS combined with more sophisticated surveillance approaches, over standard methods as modeled by the VIP, are needed to better identify and address true cross-transmission events.

Funding: This study was supported by Philips Healthcare.

Disclosures: None

This article provides an overview of selected ongoing international efforts that have been inspired by Edward Zigler's vision to improve programs and policies for young children and families in the United States. The efforts presented are in close alignment with three strategies articulated by Edward Zigler: (a) conduct research that will inform policy advocacy; (b) design, implement, and revise quality early childhood development (ECD) programs; and (c) invest in building the next generation of scholars and advocates in child development. The intergenerational legacy left by Edward Zigler has had an impact on young children not only in the United States, but also across the globe. More needs to be done. We need to work together with a full commitment to ensure the optimal development of each child.

Trifludimoxazin, a new protoporphyrinogen oxidase–inhibiting herbicide, is being evaluated for possible use as a soil-residual active herbicide treatment in cotton for control of small-seeded annual broadleaf weeds. Laboratory and greenhouse studies were conducted to compare vertical mobility and cotton tolerance of trifludimoxazin to flumioxazin and saflufenacil, which are two currently registered protoporphyrinogen oxidase–inhibiting herbicides for use in cotton, in three West Texas soils. Vertical soil mobility of trifludimoxazin was similar to flumioxazin in Acuff loam and Olton loam soils, but was more mobile than flumioxazin in the Amarillo loamy sand soil. The depth of trifludimoxazin movement after a 2.5-cm irrigation event ranged from 2.5 to 5.0 cm in all soils, which would not allow for crop selectivity based on herbicide placement, because ideal cotton seeding depth is from 0.6 to 2.54 cm deep. Greenhouse studies indicated that PRE treatments were more injurious than the 14 d preplant treatment when summarized across soils for the three herbicides (43% and 14% injury, respectively). No differences in visual cotton response or dry weight was observed after trifludimoxazin preplant as compared with the nontreated control within each of the three West Texas soils and was similar to the flumioxazin preplant across soils. On the basis of these results, a use pattern for trifludimoxazin in cotton may be established with the use of a more than 14-d preplant restriction before cotton planting.

The sustainability concept seeks to balance how present and future generations of humans meet their needs. But because nature is viewed only as a resource, sustainability fails to recognize that humans and other living beings depend on each other for their well-being. We therefore argue that true sustainability can only be achieved if the interdependent needs of all species of current and future generations are met, and propose calling this ‘multispecies sustainability’. We explore the concept through visualizations and scenarios, then consider how it might be applied through case studies involving bees and healthy green spaces.

We hypothesized that a computerized clinical decision support tool for Clostridium difficile testing would reduce unnecessary inpatient tests, resulting in fewer laboratory-identified events. Census-adjusted interrupted time-series analyses demonstrated significant reductions of 41% fewer tests and 31% fewer hospital-onset C. difficile infection laboratory-identified events following this intervention.

Infect Control Hosp Epidemiol 2018;39:737–740

We describe an outbreak of tuberculosis (TB) in the food preparation area of a hospital, which demonstrates that employees in healthcare settings may serve as potential risks for spread of TB even if they have no direct patient contact.

Infect Control Hosp Epidemiol 2016;37:1111–1113

An accepted practice for patients colonized with multidrug-resistant organisms is to discontinue contact precautions following 3 consecutive negative surveillance cultures. Our experience with surveillance cultures to detect persistent carbapenemase-producing Enterobacteriaceae (CPE) colonization suggests that extrapolation of this practice to CPE-colonized patients may not be appropriate.

Infect Control Hosp Epidemiol 2015;36(7):835–837

Carbapenemase-producing Enterobacteriaceae (CPE) are of increasing prevalence worldwide, and long-term acute care hospitals (LTACHs) have been implicated in several outbreaks in the United States. This prospective study of routine screening for CPE on admission to a LTACH demonstrates a high prevalence of CPE colonization in central Virginia.