Akhtar, Haris

Abstract Objective: Patients with Opioid Use Disorder (OUD) are prone to Multidrug-Resistant Organism (MDRO) colonization and infections, thus at risk for worse outcomes during critical illness. Understanding the prevalence and predictors of MDRO infections is essential to optimize interventions and treatments. Design: Retrospective cohort study. Methods: The study evaluated the prevalence of MDRO isolation among adults with OUD admitted to an intensive care unit (ICU) between January 1, 2018, and July 31, 2023. It included adults admitted to an ICU with bacterial infections and positive cultures obtained within 48 hours of admission. Demographics, clinical traits, and MDRO isolation rates were analyzed using descriptive statistics, univariate methods, and Least Absolute Shrinkage and Selection Operator (LASSO) regression. Results: MDRO isolation occurred in 178 of 790 patients (22.5%), with methicillin-resistant Staphylococcus aureus as the most frequently isolated organism. LASSO regression identified housing insecurity (OR: 1.79, 95% CI 1.09–2.93, P = .022), no receipt of medications for OUD treatment (OR: 1.56, 95% CI 1.06–2.29, P = .023), positive hepatitis C virus (HCV) status (OR: 2.19, 95% CI 1.19–4.03, P = .012), and intravenous antibiotic use in the prior 90 days (OR: 1.04 per 24 h, 95% CI 1.01–1.07, P = .007) as significant predictors of MDRO isolation. Conclusions: The study highlights a high prevalence of MDRO isolation in critically ill OUD patients admitted for infection-related issues with positive cultures obtained within 48 hours of admission, influenced by factors like housing insecurity, no receipt of medications for OUD treatment, HCV status, and prior antibiotic use.

Abstract Background The opioid crisis and the increasing prevalence of multi-drug resistant organism (MDRO) infections pose a threat to public health. Opioid Use Disorder (OUD) patient are prone to MDRO colonization and infections, thus potentially leading to adverse outcomes during periods of critical illness. Understanding the prevalence and predictors of MDRO infections within this vulnerable population is critical to improving patient outcomes by optimizing interventions and treatment plans. Methods We conducted a retrospective, multicenter, cohort study to evaluate the prevalence of MDRO isolation among adults with OUD admitted to an intensive care unit (ICU) with an infection across four Mayo Clinic regions. Patients were classified to the MDRO cohort if an MDRO was isolated from standard cultures or rapid diagnostic testing within 48 hours of admission. We utilized descriptive statistics, univariate and multivariate least absolute shrinkage and selection operator (LASSO) regression analysis including random effect to account for site variability, to analyze demographic data, clinical characteristics, and outcomes. Results 790 critically ill adult OUD patients with infection-related admission were included in the study cohort. The prevalence of MDRO isolation was 22.5% (n=178), with MRSA being the predominant isolated MDRO. In LASSO regression analyses, we identified homelessness (OR: 1.79, p = 0.022), no Medications for OUD (MOUD) treatment (OR: 1.56, p=0.023), and positive Hepatitis C Virus (HCV) status (OR: 2.19, p = 0.012) as significant predictors for isolation of an MDRO. Intravenous (IV) antibiotic use in the preceding 90 days was also positively associated (OR: 1.04 per 24 hours, p = 0.007), alongside mental health disorders (OR: 2.03, p < 0.001) and diabetes (OR: 1.54, p = 0.023). Conclusion The high prevalence of MDRO isolation in critically ill OUD patients with infection is associated with complex social and clinical factors. Disclosures All Authors: No reported disclosures

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

ABSTRACT Campylobacter fetus is known to cause human disease, particularly in elderly and immunocompromised hosts. There are limited published data for antimicrobial susceptibility patterns with this organism, and no interpretive criteria are available. We reviewed antimicrobial susceptibilities of C. fetus isolates tested at a tertiary care center and reference laboratory over an 11-year period. C. fetus isolates from patients treated at Mayo Clinic and those sent as referrals for identification and susceptibility were included. Antimicrobial susceptibility testing was performed using agar dilution for ciprofloxacin, doxycycline, erythromycin, gentamicin, meropenem, and tetracycline. Geographic distribution, culture source, organism minimal inhibitory concentration (MIC) distributions, and MIC 50 and MIC 90 were examined. Excluding duplicates, 105 unique isolates were identified from 110 positive cultures. Blood cultures represented the most common source, followed by body fluids, skin and soft tissue, and central nervous system. Gentamicin and meropenem had favorable MIC 50 and MIC 90 of 1 µg/mL. Ciprofloxacin demonstrated an MIC 50 of 1 µg/mL; however, the MIC 90 was >2 µg/mL. Erythromycin demonstrated MIC 50 and MIC 90 of 2 µg/mL. Tetracycline and doxycycline were tested on a limited number of isolates and showed a wide range of MICs. Gentamicin and meropenem demonstrated favorable MICs in C. fetus isolates. These may represent therapeutic options for consideration in serious C. fetus infections, pending susceptibility results. Ciprofloxacin, which showed variable results, may be more appropriate for use only after susceptibility testing. C. fetus interpretive criteria are needed to aid clinicians in selection of both empiric and definitive therapies. IMPORTANCE Our findings contribute to the scant literature on Campylobacter fetus antimicrobial susceptibility test results. We used a reference test method of agar dilution and provide MICs for a large number of organisms and antimicrobial agents.

Abstract Background Clostridioides difficile infection (CDI) is a common and potentially life-threatening infection. Transplant recipients are vulnerable to CDI due to immune suppression and frequent antibiotic exposure. CDI can lead to serious complications in these patients, including allograft failure. In a population of pancreas transplant recipients, we aimed to identify epidemiologic characteristics and risk factors associated with CDI within 90 days of transplant. Methods We performed a retrospective cohort study of adults who underwent pancreas transplantation between January 1, 2010, and December 31, 2020, at three centers in Arizona, Florida, and Minnesota. Patients were excluded if they developed pancreas allograft failure within 48 hours of transplantation. The primary outcome was diagnosis of CDI within 90 days of transplantation and the secondary outcome was pancreas allograft failure. The main analyses were performed by Cox regression. Results A total of 482 patients were included, of which 35 (7.3%) developed CDI within 90 days (Table 1). Within the subset of 35 CDI patients, the median time to CDI was 17.0 (IQR 13.0–28.5) days (Figure 1) with most (83%) diagnosed with non-severe CDI. Most patients with CDI were on current systemic antibiotics (94%), primarily for prophylaxis (73%). CDI treatment was vancomycin for the majority of patients (71%) and metronidazole for the rest (29%). One patient had a fecal transplant for recurrence, and none required surgery. In multivariable cox regression of associations with 90-day CDI, significant associations were anastomotic leak (HR 3.04, 95% CI 1.2-7.4; p=0.015) and simultaneous pancreas-kidney transplantation (HR 8.70, 95% CI 1.15-66.7; p=0.036); age (HR 0.97, 95% CI 0.94-1.01; p=0.110) was not significant. In a secondary analysis, CDI was not associated with pancreas allograft failure (p=0.719).Table 1.Characteristics of 482 patients who underwent pancreas transplantation. Conclusion This study identified preceding anastomotic leak as a risk factor for 90-day CDI after pancreas transplantation, likely due to subsequent intra-abdominal infection and antibiotic use. simultaneous pancreas-kidney transplantation is another risk factor due to additional comorbidity. Transplant providers should be cognizant of the risks of CDI and mitigate these risks as possible. Disclosures All Authors: No reported disclosures