bluuebunny/crossref_metadata_2025_split huggingface dataset:
P-1787. Tailor Swiftly: Lessons Learned from a Nationwide Implementation of an Antimicrobial Stewardship Program for Asymptomatic Bacteriuria
Authors: Amenta Eva , Haltom Trenton M , Donnelly John P , Braund Sophia , Hernandez Rogelio , Chou Andrew , Brehm Tyler , Stevens Vanessa W , Trautner Barbara 
Published: January 2025

Abstract

Background
Overtreatment of asymptomatic bacteriuria (ASB) is a major cause of antibiotic overuse. We are facilitating an implementation of ASB Antimicrobial Stewardship (AS) intervention in 40 Veterans Affairs facilities, with 20 of these sites participating in a Virtual Learning Collaborative (VLC). The VLC meets twice monthly for webinars to hear from content experts and share stewardship strategies.
Figure 1.
Thematic Categories of Stewardship Strategies for Implementation of Antimicrobial Stewardship Program

Methods
Data come from descriptive field notes taken during each webinar. Notes focused on stewardship strategies shared by guest presenters or participating local site participants. Webinar sessions were recorded and transcribed using MS Teams. Transcripts were iteratively reviewed first by individual webinar, then across all webinars. Stewardship strategies were then organized thematically. We use exemplar quotes to illustrate and support thematic categories.

Results
Across 19 webinars conducted between May 2023-February 2024, it became clear that each implementation site had different resources, team membership, and organizational structures. Thus, sites had to “tailor [the AS intervention] swiftly” for effective reach and implementation. Tailoring meant adapting the delivery of AS educational materials for timing, length, audience, and location of outreach. Sites used five strategies to implement the AS program: Organization and Structural Strategies, Interpersonal and Recruitment Strategies, Data- and Information-Based Strategies, Interpersonal Strategies, and Resources (Figure 1).

Conclusion
VLC webinars encouraged sites to share tips and strategies about implementation of a nationwide AS program wherein rapid tailoring and focused strategies were effective. "Tailoring swiftly” acknowledges differing resources and organizational contexts to allow implementation sites to adapt AS materials to their needs.

Disclosures
Andrew Chou, MD, MSc, Prolacta Bioscience: Advisor/Consultant Barbara Trautner, MD, PhD, Abbott Laboratories: Stocks/Bonds (Public Company)|AbbVie: Stocks/Bonds (Public Company)|Bristol Myers Squibb: Stocks/Bonds (Public Company)|Pfizer: Stocks/Bonds (Public Company)|Phiogen Pharma: Advisor/Consultant
P-1805. Identifying Hospital Antimicrobial Usage Trends Using Wastewater Based Surveillance
Authors: Penney Matthew , Kuzma Darina , Kormendi Aleshia , Moffett Kayla , O’Grady Christine , Clark Rhonda , Nobrega Diego , Kimura-Hara Susana , McCalder Janine , Vivas Laura , Papparis Chloe , Acosta Nicole , Waddell Barbara Jean M , Hubert Casey R J , Dalton Bruce , Conly John , Parkins Michael , Weyant Benson , Rennert-May Elissa 
Published: January 2025

Abstract

Background
Hospitals represent ideal locations for developing wastewater (WW) surveillance for antibiotics (Abx), owing to the high frequency of Abx use and robust record-keeping. To investigate this technology as a potentially useful stewardship tool, we compared the concentration of several Abx in WW from tertiary care hospitals to their corresponding levels in the surrounding municipality.
Concentration of 4 common antimicrobials found in hospital wastewater effluent over a 4-month period
Concentrations of 4 antimicrobials measured in WW from 3 tertiary care hospitals and the corresponding wastewater treatment plant (WWTP) in the same city. Displayed statistics represent the results of a Wilcoxon test, antimicrobials labelled “*” are commonly administered intravenously.

Methods
WW was collected bi-weekly from three tertiary care hospitals (two adult and one pediatric, with 600, 650 and 135 inpatient beds, respectively) and the associated municipal WW treatment plant (serving a population of ∼1,000,000) between February and May of 2024. Aliquots of WW were filtered and run directly on a liquid-chromatography paired triple quadrupole mass spectrometer (LC-QQQ) to quantify specific Abx (azithromycin, doxycycline, ciprofloxacin, levofloxacin, metronidazole, cefazolin, ceftriaxone, piperacillin, tazobactam, meropenem, vancomycin, and sulfamethoxazole). Spiked and replicate samples were randomly included to validate analyte recovery and reproducibility. Agilent MassHunter software (Version 10.1, 2019) was utilized to process and export raw data to R. Box plots and Wilcoxon tests were utilized to compare the concentration of each Abx.

Results
Validation experiments confirmed that filtering WW samples and directly running them on LC-QQQ yields reproducible and reliable results. Serial monitoring revealed that WW from hospitals generally exhibited a broader range of Abx concentrations than was observed city-wide (Figure 1). This variability was particularly evident among the most used Abx, consistent with the changing treatment needs of highly dynamic hospital populations. In addition to this, ceftriaxone, an IV-administered antimicrobial was found at significantly higher concentrations in all hospital sites when compared to the municipal WW treatment plant.

Conclusion
Validating Abx monitoring in WW from a range of scales will enable this approach to be applied across diverse environments as a tool to mitigate Abx resistance. This approach will be strengthened as it is integrated with clinical metadata and metagenomic assessment of antimicrobial resistance genes from the same samples.

Disclosures
All Authors: No reported disclosures
P-1840. Differential Memory CD4 T Cell Responses to SARS-CoV-2 in Children and Adults Pre- and Post-Pandemic
Authors: Rowe Regina K , Huertas Nelson , Matthews Bailey , Nayak Jennifer L 
Published: January 2025

Abstract

Background
Coronaviruses are endemic in the human population and include both seasonal viruses as well as the SARS-CoV-2 virus responsible for the COVID-19 pandemic. As a betacoronavirus, SARS-CoV-2 is closely related to two endemic coronaviruses (OC43 and HKU1), with exposure history differing between children and adults. We sought to identify age-specific differences in memory CD4 T cells specific for the SARS-CoV-2 Spike protein (S), as quantitative and qualitative differences in immune function may be responsible for age-related variation in disease presentation.

Methods
Peripheral blood mononuclear cells were obtained from cohorts of children and adults enrolled pre-2019 and following the SARS-CoV-2 pandemic. Subjects enrolled post-pandemic had a history of COVID-19 vaccination. Cells were stimulated with peptide pools representing the unique and more cross-reactive portions of the S protein for 24 hours, with cytokine release blocked for the last 4 hours of coculture. Subsets of S-specific CD4 T cells were identified using a 31-plex spectral flow cytometry panel.

Results
Pre-pandemic, adults had a higher frequency of activated IFNγ+ CD4 T cells specific for the S protein compared to children, with boosting of responses in both adults and children following SARS-CoV-2 exposure. Overall, the CD4 T cell response to the S protein was Th1 biased, with adults having a greater proportion of cells expressing IFNγ, IL2 and TNFα. When cytokine-expressing, antigen-specific CD4 T cells were subsetted by CD45RA and CCR7 expression, there was a more naïve phenotype pre-pandemic, with transition to an effector memory phenotype post-2019.

Conclusion
A greater magnitude of CD4 T cells specific for the S protein was detected in adults pre-pandemic, with this reactivity boosted in both children and adults following SARS-CoV-2 exposure. Boosting of reactivity to both unique and conserved S protein epitopes in children and adults suggested that exposure to SARS-CoV-2 via vaccination did not preferentially boost memory CD4 T cells specific for conserved epitopes. Post-pandemic, there was a shift to a more Th1 phenotype together with a gain in cytokine-producing CD4 T cells with a phenotype consistent with effector memory.

Disclosures
Jennifer L. Nayak, MD, Merck, Inc.: Grant/Research Support|Moderna, Inc.: Grant/Research Support|Pfizer, Inc.: Grant/Research Support
P-1843. Genomic surveillance of invasive Streptococcus pyogenes in Metropolitan Detroit
Authors: Kaur Jagjeet , Jagannathan Megha , Jordan Tamara , Kinsey Daniel , Truppiano Maryssa , Shallal Anita , Suleyman Geehan 
Published: January 2025

Abstract

Background
Group A streptococcal (GAS) disease is a major problem worldwide and can cause both noninvasive and invasive disease, including necrotizing fasciitis, with significant morbidity and mortality. Overall, the number of invasive GAS infections has been increasing in the United States over the past decade, primarily in adults. We aim to characterize the genomic features of circulating GAS strains causing invasive disease.Table.Patient demographics and genomic characteristics

Methods
We performed whole-genome sequencing (WGS) on clinically obtained GAS blood isolates at Henry Ford Health, a comprehensive, integrated, health care organization in Southeast Michigan from Jan 2017-Dec 2023. Sequencing libraries were created using the QIAseq FX DNA Library Kit (Qiagen,USA) according to manufacturer’s instructions and sequenced on NextSeq 2000 (Illumina Sandiego, USA). Fastq files were used to determine the distribution of traits, virulence factors, and resistance genes using the 1928 Platform.

Results
We sequenced unique isolates from 64 patients, of whom 38 (59%) were males with median age 57 years [Table]. Most isolates were from 2022 (25%) and 2023 (53%). Fifteen M protein (emm) serotypes and 19 sequence type (ST) were obtained from 64 characterized isolates. The most frequent emm lineages were emm1 (n=16) and emm12 (n=12), where most patients had skin and soft tissue infection. The predominant emm1 lineage belonged to ST28. None of the emm1 and emm12 isolates carried aminoglycoside, macrolides/lincosamides/streptogramines (MLS), or tetracycline resistance genes. All the emm11 and emm49 isolates exhibited erm(A) and tetracycline resistance genes. Streptococcal superantigen (SAgs) genes were frequently detected; streptococcal pyrogenic exotoxin (SPE)-G was the most detected SAgs (97%), followed by streptococcal mitogenic exotoxin (SME)-Z (75%). SPE-H and SPE-I were each found in 48% of the isolates.

Conclusion
In our cohort of patients with invasive GAS, several SAgs were detected. SPE-A, SPE-G, SME-Z and SPE-J were most frequently found in emm1 lineages. However, there was no correlation between various clinical syndromes and the virulence genes identified. Continued genomic surveillance can help characterize features associated with emerging invasive strains to inform management and infection prevention strategies.

Disclosures
All Authors: No reported disclosures
P-1869. Utilizing Large Language Models for Enhanced Decision Support in Travel Medicine Clinic: our experience at Mayo Clinic
Authors: O’Horo John C , Akhtar Haris , Anantraman Vish , Ammar Muhammad , Gottweis Juro , Challener Douglas 
Published: January 2025

Abstract

Background
The integration of Generative AI (GAI) into healthcare systems is increasingly recognized for its potential to transform patient management. The primary aim of this research was to evaluate and quantify the performance of large language models (LLMs) in generating actionable travel medicine advice.
Architectural design of the Travel Clinic LLM project.
Four phases of Discovery, Design, Evaluation, and Implementation/Deployment.

Methods
This study utilized two iterative phases of evaluation. In the initial phase, LLMs were prompted with detailed clinical scenarios including demographic data, medical and immunization histories, and specific travel plans. These prompts were designed to mimic typical inquiries encountered in travel consultations. The LLMs' initial responses were generated using the CDC’s Yellow Book as a foundational knowledge base. In the subsequent phase, the prompts were refined for greater specificity and clarity, and the knowledge base was enhanced by transitioning to Travax’s Travelers’ Health database. Additional structured data inputs included an exhaustive list of vaccines from our pharmacy formulary and a detailed table of vaccine contraindications. The responses were evaluated and scored by ID clinicians from the Mayo Clinic.

Results
Initial findings after first iteration revealed limited efficacy with recall at 23.9%, an F1 score of 38.6%, accuracy also at 23.9%, and precision maintained at 100%, utilizing the CDC's Yellow Book. With the implementation of Travax and refined prompting techniques, preliminary results suggest a notable improvement in the quality of responses, though detailed scoring is presently underway.
Improvements in the LLM’s performance can be attributed to several key adjustments: the adoption of a more comprehensive knowledge base, refined prompt engineering, and the incorporation of structured data to support more accurate and detailed recommendations. The collaborative engagement of Mayo Clinic with Google and Travax facilitated a synergistic approach to optimizing the AI model's utility and integration. Future plans include embedding the LLM into our EMR system.

Conclusion
The findings from this study highlight the significance of strategic collaborations between large healthcare centers, IT industry, and specialized knowledge database firms in effectively harnessing GAI for clinical use.

Disclosures
All Authors: No reported disclosures
P-1870. Clinical Outcomes of Self-Administered Outpatient Parenteral Antimicrobial Therapy over 12 Years in a Safety Net Hospital
Authors: Jacobs Anna , Smartt Jillian , Harms Michael , Castellino Laila M , Alvarez Kristin , Bhavan Kavita 
Published: January 2025

Abstract

Background
Outpatient Parenteral Antimicrobial Therapy (OPAT) is safe and effective for medically stable patients requiring intravenous (IV) antibiotics.1 OPAT is most commonly administered in a healthcare setting (H-OPAT), utilizing home health services, infusion centers, nursing homes, or hemodialysis centers. However, patients without health insurance are often unable to afford H-OPAT services, leading to lengthy hospital stays and potentially avoidable healthcare costs. Self-administered OPAT (S-OPAT) is relatively uncommon. At our safety net hospital, we established a S-OPAT clinic for uninsured patients in 2009. Data published from the first four years of our S-OPAT program in 2015 demonstrated a decreased risk of 30-day readmission among S-OPAT compared to H-OPAT with no significant difference in 1-year mortality.1. A registry of all patients discharged on OPAT has since been developed.Table 1:Patient Demographics

Methods
Data from 7335 OPAT discharges between October 2012 and December 2023 were analyzed. We assessed both H-OPAT and S-OPAT groups for blood stream infections secondary to vascular access sites in the ambulatory setting, 30-day readmission rates, and total number of S-OPAT days as an estimate for prevented inpatient days.Table 2.Clinical Outcomes for S-OPAT versus H-OPAT

Results
Of the 7,335 OPAT discharges from 2012 to 2023, 49.9% were discharged to H-OPAT and 50.1% to S-OPAT (Table 1). There was no difference between 30-day readmissions (OR 1.01 [CI 1.000 - 1.029) for S-OPAT as compared to H-OPAT (Table 2). There were a total of 47 blood stream infections over this 12-year period. 35 occurred in H-OPAT patients and 12 in S-OPAT patients (p &lt; .01). A total of 54,733 days of S-OPAT were prescribed, preventing an estimated same number of inpatient days.

Conclusion
S-OPAT was designed to provide an alternative to prolonged hospital stays for uninsured patients requiring prolonged IV antibiotics. There is always a concern about the safety of discharging patients with vascular access, especially in patients with limited access to healthcare. Our data demonstrates that the safety of S-OPAT is as good, if not better, than the standard of care, H-OPAT, while allowing for more effective utilization of and improving health equity for our uninsured patients in our safety net hospital.

Disclosures
All Authors: No reported disclosures
P-1903. Beyond the Hospital Walls: Unveiling the Post-COVID-19 Path to Institutionalization
Authors: Bandera Alessandra , Colaneri Marta , Canuti Marta , Galbussera Alessia , Dall’Olio Lucia , Bobbio Chiara , Baldi Sante Leandro , Nobili Alessandro , Puoti Massimo , Marchetti Giulia , Latronico Nicola , Plebani Pierluigi , Raviglione Mario , Gori Andrea , Ojeda Fernandez Maria Luisa , Baviera Marta , Leoni Olivia , Fortino Ida , Tettamanti Mauro 
Published: January 2025

Abstract

Background
Functional decline (decrement in physical/cognitive functioning that causes inability to engage in daily activities) is common following acute hospitalization in elderly patients and is associated with hospital readmission, institutionalization, and mortality. We sought to determine rate of institutionalization after COVID-19 hospitalization and to characterize functional decline of patients institutionalized after COVID-19.

Characteristics of COVID-19 and pre-COVID-19 hospitalized patients

Methods
We conducted a retrospective cohort study using health administrative database from Lombardy Welfare Directorate. We included patients 44 years-old and older who were discharged from a Lombardy hospital with a diagnosis of COVID-19 between Feb 1st, 2020 and Jun, 30th, 2022 (COVID cohort) compared with patients discharged from the same sites with any diagnosis from Jan, 1st 2018 until Dec 31st, 2018 (pre-COVID cohort). Our primary outcome was institutionalization during the 6-month period following hospital discharge. We also compared functional decline parameters at institutionalization in the two cohorts.

Trend of institutionalization during the COVID-19 pandemic waves

Results
Our study included 141651 patients hospitalized for COVID-19 and 251459 individuals acutely hospitalized before COVID-19 pandemic (pre-COVID-cohort) for any diagnosis (Table 1). Among them, 3835 (2.7%) and 7976 (3.2%) were institutionalized during the following 6-months, respectively. Rates of institutionalization in the COVID-cohort increased over time during the observation period (Table 2). At institutionalization, patients hospitalized for COVID-19 were younger (median 83.6 years vs 84.9 years, p &gt;0.0001), and more frequently female (37.8% vs 32.3%, p&lt; 0.0001). Moreover, they had more frequently pressure sores (20.5% vs 16.3%, p&lt; 0.0001) and urinary catheter (27% vs 19.8%, p&lt; 0.0001) and fewer assistive devices (p&lt; 0.0001) as compared to the pre-COVID cohort (Table 3).

Characteristics of institutionalized patients following acute COVID-19-realated hospitalizations vs non-COVID-19 acute hospitalization

Conclusion
Hospitalization for COVID-19 was followed by institutionalization at the same rate as acute hospitalization for all-cause in the pre-COVID period. However, functional decline, pressure sores, urinary catheter, incontinence, and use of assistive devices following COVID-19 hospitalization in the elderly population should be closely monitored.

Disclosures
All Authors: No reported disclosures
642. The Role of Electronic Medical Record Automation in Latent Tuberculosis Screening and Treatment in a Large Health System
Authors: Li Hannah T , Sahni Harleen , Cervenka Andrea 
Published: January 2025

Abstract

Background
Valley Medical Center is a tertiary county hospital in San Jose, California that also staffs 12 clinics. Our institution’s Mycobacterial and Refugee Health Clinic is the main referral center for latent tuberculosis (LTBI) and active TB cases in the county.
The USPFTF recommends screening for LTBI in asymptomatic adults who are at higher risk. This is challenging in primary care settings where physicians often see a high number of patients within limited time frames. There are many points on the LTBI care cascade (Figure 1) where patients can fall off. In the age of automation, technological tools can be designed to help reduce clinician burden.Figure 1:Latent Tuberculosis Care CascadeSource: California Department of Public Health Tuberculosis Control Branch

Methods
An EMR tool was engineered to prompt physicians to order a QuantiFERON (QFN) if a patient meets certain criteria: 18 years or older, no prior QFN or TB skin test, and any of the following risk factors: HIV positive, in custody, drug use, homelessness, or non-English primary language (proxy for foreign birth). This EMR tool went live on 8/9/22.
Using EMR data-collection tools, a retrospective analysis was done among patients who had a clinical encounter (office visit or telemedicine) between 8/9/21-8/9/22 and 8/9/22-8/9/23 (one year before and after implementation of the tool). We determined the number of patients who were eligible for screening, obtained a QFN, had a positive QFN, initiated, and completed treatment. A 2-sample Z-test was used to assess temporal trends.Table 1:LTBI Care Cascade for Patients Seen by a Primary Care Physician in 8/9/21-8/9/22 and 8/9/22-8/9/23

Results
From 8/9/22-8/9/23, 34251 patients were marked eligible for LTBI screening based on the EMR tool (Table 1, Figure 2). The proportion of patients tested for LTBI increased from 45.3% to 81.2% (p-value &lt; 2.2e-16). The proportion of positive LTBI results increased from 8.6% to 12.4% (p-value &lt; 2.2e-16). The number of patients who initiated treatment increased from 545 (40.8%) to 1038 (30%). The number of patients who completed treatment increased from 417 (76.5%) to 770 (74.2%).Figure 2:LTBI Care Cascade for Patients Seen by a Primary Care Physician in 8/9/21-8/9/22 and 8/9/22-8/9/23

Conclusion
This study highlights that a low-cost EMR intervention can lead to substantial increases in LTBI screening, and as a result higher treatment completion. EMR automation can also improve accuracy in screening, reflected by the increased proportion of positive QFN results. Future tools involving digital technology can be designed to reduce drop-offs at other points along the LTBI cascade as well.

Disclosures
All Authors: No reported disclosures