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Background: Clinical antibiotic susceptibility testing (AST) interpretations based on minimum inhibitory concentrations (MIC) breakpoints are important for both clinical decision making and some reportable condition criteria. Standardization of MIC breakpoints across clinical laboratories is lacking; AST instruments are often validated for outdated Clinical and Laboratory Standards Institute (CLSI) MIC breakpoint guidelines. In this study, we analyzed the agreement between the reported clinical laboratory AST interpretations and the guideline CLSI interpretation. Methods: Clinical laboratory AST data collected from the Multisite Gram-Negative Surveillance Initiative (MuGSI) carbapenem-resistant Enterobacterales (CRE) surveillance program in Tennessee between 2019 and 2021 were utilized. MIC values from the clinical instrument were used to calculate CLSI standard interpretations following the 2019–2021 CLSI M100 guidelines. Agreement between the clinical laboratory and CLSI interpretations of the reported MIC values were measured using a weighted Cohen κ calculated in SAS version 9.4 software. Total matches were isolates with identical CLSI and clinical laboratory interpretations. Results: In total, 14 antibiotics were assessed. Of those, 9 antibiotics had at least moderate agreement (κ > 0.41) between interpretations. Agreement between the clinical laboratory and the CLSI interpretations were near perfect (κ > 0.81) for 3 antibiotics. Agreement between the clinical laboratory and the CLSI interpretations were poor for cefazolin (0.06) and ertapenem (0.14). Cefotaxime (−0.07) was the only antibiotic that suggested no agreement. Conclusions: Of the antibiotics included in the analysis, 36% had less than moderate agreement between clinical laboratory and CLSI AST interpretations. Given the increases in antimicrobial resistance globally and the emphasis placed on antibiotic stewardship, standardization across clinical AST panels should be prioritized. Inconsistencies have the potential to contribute to inappropriate antibiotic use in addition to under- or overidentification of reportable conditions, including CRE. Disclosures: None

Background: In September 2021, the CMS mandated that long-term care facility (LTCF) healthcare workers be vaccinated for COVID-19 unless medically or religiously exempt. Vaccinating healthcare workers reduces transmission of COVID-19 among patients and workers, reducing the risk of illness among residents and patients. We examined the relationship between COVID-19 clusters and staff vaccination rates in Tennessee LTCFs. Methods: COVID-19 cluster data were collected using REDCap from January 3, 2021, to September 25, 2022, and LTCF vaccination rates were collected from the NHSN. Clusters were identified in facilities with 2 or more cases. The staff vaccination rate 2 weeks prior to the cluster was used, accounting for the lag time between vaccination dose and reaching full immunity. We selected 75% as the critical immunization threshold. The facility case rate was calculated per 100 beds. A test was performed to determine whether reaching the critical vaccination threshold was associated with cluster occurrence. The relationship between vaccination rate and case number was tested using Pearson correlation. Statistical analyses were conducted using SAS version 9.4 software. Results: The average staff vaccination rate when NHSN first required long-term care facilities to report rates rose from 47% in June 2021 to 83% in September 2022. In total, 806 clusters were identified with 20,868 combined weeks from all facilities being reported after merging facilities’ weekly vaccine percentage rates with cluster data. Most weeks from all facilities did not identify a cluster (n = 20,064, 96.15%) and did not meet the critical immunization threshold (n = 11,050, 52.95%). The association between a cluster occurring and a facility meeting the threshold was significant (χ 2 = 5.41; df = 1; P 95% CI, .7327–.9740). The Pearson correlation coefficient between vaccination rate and case number was 0.05560 ( P = .2894). Conclusions: There was a significant association between facilities not reaching the immunization threshold and presence of a COVID-19 cluster. The facility case rate was not correlated with staff vaccination rate; however, a limitation of this analysis was that resident vaccination was not tested. Another limitation was that medical and religious exemptions could not be differentiated. Healthcare staff should consider getting vaccinated, if able, to reduce the risk of COVID-19 and to keep staff and residents safe from COVID-19. Disclosures: None

Background: According to the Centers for Disease Control and Prevention (CDC), carbapenem-resistant Enterobacterales (CRE) are an urgent public health threat. The CDC states the most common or ‘Big Three’ CRE are Escherichia coli, Enterobacter species, and Klebsiella species. States look at the ‘Big Three’ for guidance when setting reportable condition criteria for CRE. Evaluating trends of the non-‘Big Three’ genera is critical to ensure surveillance efforts are focused on priority targets. Thus, CRE genera trends were evaluated to verify the fitness of CRE surveillance reporting recommendations. Method: The Antimicrobial Resistance Laboratory Network (ARLN) Southeast region (SER) includes Alabama, Florida, Georgia, Louisiana, Mississippi, Tennessee, and Puerto Rico. All CRE is reportable in Tennessee (TN) and isolate submission is required to ARLN. Other jurisdictions submit CRE to the TN regional lab. Submitted CRE cases to ARLN from 2018 – 2023 were analyzed. CRE cases were defined as an Enterobacterales organism resistant to one or more carbapenem, excluding imipenem for Proteus sp., Providencia sp., or Morganella sp. due to intrinsic resistance. Data was cleaned in SAS v9.4 to provide descriptive CRE statistics. Result: The top three genera for TN fluctuate between Enterobacter sp., Klebsiella sp., Proteus sp., and Escherichia sp. In 2022, Proteus sp. (n=132) had twice the incidence of Escherichia sp. (n=65) in TN. There was an overall increasing trend of Proteus sp. from 2018 – 2023. The largest increase of Proteus sp. in TN was seen between 2018 (n=23) and 2021 (n=183). However, the prevalence sharply decreased between 2021 (n=183) and 2023 (n=12). Proteus sp. was 17% (n=627) of all CRE cases (n=3625) in TN from 2018 – 2023, while the “Big Three” was 72% (n=2628). In contrast, Proteus sp. was only 3% (n=35) of all CRE cases (n=1400) in the SER excluding TN from 2018 – 2023, compared to 89% (n=1250) for the “Big Three”. Conclusion: CRE surveillance identified an increased overall prevalence of Proteus sp. in TN between 2018 and 2022 despite not being included in the ‘Big Three’. While there was a large increase of Proteus sp. observed in 2021, the increase was limited to TN, and the subsequent decline suggests this is an outlier. Jurisdictions outside of TN often only submit Carbapenemase-producing CRE to ARLN as not all jurisdictions have CRE as a reportable condition. Results of this analysis suggest the SER should continue to monitor CRE and Proteus sp. to note if there is an increasing overall trend to better inform isolate submission strategies.

Background: Identification and timely reporting of multi-drug resistant organisms (MDROs) drives efficacy of infection prevention efforts. Data on MDRO reporting timeliness and inter-facility variability are limited. Facility-dependent variability in MDRO reporting across Tennessee was examined to identify opportunities for MDRO surveillance improvement. Methods: Data for reported Tennessee MDROs including carbapenem-resistant Enterobacterales (CRE), carbapenem-resistant Acinetobacter baumannii (CRAB), Carbapenem-resistant Pseudomonas aeruginosa (CRPA) and Candida auris, were obtained from the southeast regional Antibiotic Resistance Laboratory Network (ARLN) from 2018-2022, excluding screening and colonization specimens. Variance in days accrued from specimen collection to ARLN receipt was analyzed using one-way analysis of variance (ANOVA) with Tukey’s test (SAS 9.4). Facilities were categorized as fast (1-10 days), slow (11-20 days), or delayed (21-100 days) reporters. Results: There were 9,569 MDRO isolates reported. CRPA was reported faster than other MDROs (p < 0.001), while specimens from West Tennessee compared to other regions (p < 0.001) (Figure) and blood cultures compared to other specimens were reported more slowly (p < 0.001) (Table). There was no difference in reporting times for facilities using on-site microbiology laboratories versus reference laboratories (P = 0.062). Conclusion: MDRO reporting times varied across Tennessee by region, specimen, and organism. Future work to elucidate drivers of variability will consist of surveys and focused interviews with laboratory personnel to identify shared and unique barriers and opportunities for improvement.

Background: Antimicrobial resistance is a growing problem in Candida spp., leading to treatment challenges and increased morbidity and mortality. The World Health Organization (WHO) fungal priority pathogens list classifies C. glabrata, C. tropicalis, and C. parapsilosis as high priority and leading causes of candidemia with high fluconazole resistance. In the US, these organisms are the most frequently isolated non-albicans Candida species. In 2016, the Antibiotic Resistance Laboratory Network (ARLN) was created to monitor resistance threats, including in Candida spp. This study describes the proportion of resistance in C. glabrata, C. parapsilosis, and C. tropicalis isolates sent to the Southeast ARLN from 2017 to 2023. Methods: This study evaluated C. glabrata, C. parapsilosis, and C. tropicalis submitted to the Southeast ARLN from Alabama, Florida, Georgia, Louisiana, Mississippi, and Tennessee from February 2017- September 2023. Species identification was confirmed by Bruker Biotyper matrix assisted laser desorption-ionization time of flight (MALDI-TOF). Antifungal susceptibility testing (AFST) was performed using TREK frozen broth microdilution panels. Minimum inhibitory concentration values from the clinical instrument were used to determine susceptibility based on Clinical and Laboratory Standards Institute (CLSI) standard interpretations from the 2020 CLSI M60 guidelines. Data were extracted from the laboratory information management system. Analyses were conducted using SAS v9.4. Results: AFST testing was performed on 660 C. glabrata, 500 C. parapsilosis, and 233 C. tropicalis isolates from within the Southeast region. The predominant specimen sources by species were blood 25.30% C. glabrata; other/not specified 27.80% C. parapsilosis; and lower respiratory 36.91% C. tropicalis. Resistance to fluconazole is as follows: C. glabrata, 12.88%; C. parapsilosis, 3.41%; C. tropicalis, 36.64%. Resistance to voriconazole is as follows: C. parapsilosis, 1.00%; C. tropicalis 30.04%. Resistance to at least one echinocandin (Anidulafungin, Capsofungin, Micafungin) is as follows: C. glabrata, 1.67%; C. parapsilosis, 0.60%; C. tropicalis, 0.43%. Overall, there was a decreasing trend in resistance to fluconazole, and voriconazole in all three species between 2017 and 2023. Conclusions: Antifungal resistance in non-albicans Candida species represents an emerging public health threat, however, within the Southeast region, ARLN data has shown a decreasing trend of azole resistance. This may be due in part to changes in reporting requirements and submission criteria from within the region. Nevertheless, C. tropicalis showed high resistance to azoles within the Southeast region. These Candida species should be monitored to inform clinical decision making and identify resistance patterns in other US regions due to their increase in resistance worldwide.

Background: Multidrug-resistant organisms (MDROs) are a global threat. To track and contain the spread, the Tennessee Department of Health (TDH) performs targeted surveillance of carbapenemase-producing and pan-nonsusceptible organisms. When these MDROs are identified, TDH conducts a containment response and collects epidemiological data, which includes risk factors such as indwelling devices and previous hospitalizations. The impact of the COVID-19 pandemic on these MDROs is not well understood. Therefore, we have described the characteristics of cases positive for both COVID-19 and select MDROs. Methods: MDRO investigation data from January 1, 2020–September 30, 2021 were matched with all COVID-19 case data from the TDH statewide surveillance system, National Electronic Disease Surveillance System Base System. MDRO-positive date was defined as the specimen collection date; COVID-19 case date was first defined as the date of symptom onset and if missing, then diagnosis date, and investigation creation date, respectively. Descriptive statistics and Fisher exact tests were calculated using SAS version 9.4 software. Results: Among 336 MDRO cases, 50 had a reported SARS-CoV-2–positive result. MDRO types were Enterobacterales (CRE) (n = 31), Acinetobacter spp (CRA) (n = 18), and Pseudomonas aeruginosa (n = 1). Of these 50 cases, 20 were MDRO-positive before and 30 days after the COVID-19 case date, respectively. Of the 18 CRA cases, 16 (89%), were positive after the COVID-19 case date, compared to 13 (42%) among 31 CRE cases ( P < .01). Also, 35 patients (70%) had a record of hospitalization, and 22 (63%) had their MDRO specimen collected after the COVID-19 case date ( P = .37). Of these 22 patients, 4 had their MDRO specimen collected during their COVID-19 hospitalization, with an average duration from admission to MDRO collection date of 17 days (range, 4–36). Among the 50 coinfected cases, 8 died, 7 (88%) of whom were MDRO-positive after their COVID-19 case date. Data on indwelling devices at time of MDRO positivity were completed for 17 cases; 14 had an indwelling device and, among these, 13 (93%) were MDRO-positive after their COVID-19 case date. Conclusions: MDRO cases with specimen collections after COVID-19 comprised the majority of hospitalized patients, patients who died, and patients with indwelling devices compared to those with MDROs collected before their COVID-19 case date. These results show a stark difference with CRA as the most common MDRO among post–COVID-19 cases. Our data were limited by reporting gaps. We recognize that patients can remain colonized with MDROs for lengthy durations, which could have result in undetected MDRO cases prior to the COVID-19 case date. More data and analyses are needed to make targeted public health recommendations. However, these findings highlight the burden of MDROs among COVID-19 cases. including adverse health outcomes. Funding: None Disclosures: None