bluuebunny/crossref_metadata_2025_split huggingface dataset:
P-2053. Clinical Outcomes and Severity of Hospitalized COVID-19 Patients Among Partially and Fully Vaccinated Patients in Louisville, Kentucky
Authors: Shahnawaz Waqas , Ali T’shura , Shafique Nouman , Wakeel Jafir , Sheikh Daniya , Salunkhe Vidyulata , Gootee Steven , Arnold Forest W 
Published: January 2025

Abstract

Background
Despite COVID-19 vaccine availability, reducing disease severity and hospitalizations remains crucial. Persistent vaccine hesitancy necessitates studies comparing outcomes between partially and fully vaccinated individuals. Our study aims to evaluate clinical outcomes among hospitalized COVID-19 patients, distinguishing between partial and full vaccination.
Multivariable logistic regression analysis for ICU admission among fully and partially vaccinated patients with COVID-19 CAP

Methods
We conducted a retrospective cohort study among hospitalized COVID-19 patients with community-acquired pneumonia (CAP) in Louisville, Kentucky. Clinical outcomes, including in-hospital mortality, cardiac events, ICU admission, and use of mechanical intubation and ventilation, were assessed. Statistical analyses included univariate and multivariable logistic regression to compare outcomes between vaccination statuses.
Multivariable logistic regression analysis for Mechanical intubation and ventilation use among fully and partially vaccinated patients with COVID-19 CAP

Results
Of 142 eligible patients, 87% were fully vaccinated, with 13% partially vaccinated. The fully vaccinated group had less patients with a CURB-65 score &gt;3 compared to the partially vaccinated group (63% vs. 53%, P=0.55). In addition, partially vaccinated patients exhibited increased rates of ARDS (6% vs 1%, P=0.61), septic shock (11% vs 3%, P=0.37), intubation (16% vs 8%, P=0.20) and mortality (21% vs 7%, P=0.09). Fully vaccinated patients exhibited lower rates of ICU admission compared to partially vaccinated patients (40% vs 15%, P=0.04). After adjusting for confounders, fully vaccinated patients had significantly lower odds of ICU admission (OR: 0.28, 95%CI: 0.15, 0.56) and intubation (OR: 0.22, 95%CI: 0.06, 0.81). However, fully vaccinated individuals had more in-hospital cardiac events (12% vs. 1%, P=0.61) and a lower odds of in-hospital mortality (OR: 0.18, 95%CI: 0.02, 1.66), but these were not statistically significant.
Multivariable logistic regression analysis for in-hospital mortality among fully and partially vaccinated patients with COVID-19 CAP

Conclusion
This study highlights full vaccination's importance in reducing COVID-19 severity among hospitalized patients. Male gender and cancer were associated with higher mortality rates. Fully vaccinated patients had lower odds of ICU admission and intubation compared to partially vaccinated counterparts. Being fully vaccinated was not found to be associated with less cardiac events or mortality. These findings emphasize the need for comprehensive vaccination strategies and targeted public health initiatives.

Disclosures
All Authors: No reported disclosures
P-2078. Performance of Anyplex and Xpert for the Detection of Mycobacterium tuberculosis complex in Respiratory and Non-Respiratory Samples
Authors: Gaxiola-Castro Alina , Flores-Treviño Samantha , Ibarías Paola Bocanegra , Camacho-Ortiz Adrian 
Published: January 2025

Abstract

Background
Tuberculosis diagnosis requires rapid and sensitive diagnostic methods. The aim was to evaluate the performance of Anyplex MTB/NTM and Xpert MTB/RIF assays for the detection of Mycobacterium tuberculosis complex (MTC) in respiratory and non-respiratory samples from patients suspected of having tuberculosis in a third-level hospital in Mexico.

Methods
Samples (n=436) from January 2020 to December 2023 in a hospital from Monterrey, Mexico underwent paired microbiological (MGIT or Lowenstein-Jensen culture) and molecular assays (Anyplex™ MTB/NTM Real-time Detection or Xpert MTB/RIF™) for mycobacterial detection.

Results
Of the 279 (63.8%) respiratory samples (bronchoalveolar lavage 71.3%, sputum 20.7% and tracheal aspirate 7.8%), positive culture and detected PCR were found in 26/201 samples by Anyplex and in 20/78 samples by Xpert whereas negative culture and detected PCR were found in 32 and 7 samples, respectively. Anyplex showed 65% sensitivity, 80.1% specificity, 26.5% positive predictive value (PPV), and 90.2% negative predictive value (NPV) whereas Xpert showed 100% sensitivity, 87.9% specificity, 74% PPV and 100% NPV. Of the 157 (36.1%) non-respiratory samples (cerebrospinal fluid 37.3%, soft tissues 21.5%, pleural 22.1%, lymph nodes 11.3%, and synovial 7.5%), positive culture and detected PCR were found in 14/118 samples by Anyplex and in 4/39 by Xpert whereas negative culture and detected PCR were found in 17 and 4 samples, respectively. Anyplex showed 73.6% sensitivity, 82.8% specificity, 45.1% PPV, 94.2% NPV whereas Xpert showed 66.6% sensitivity, 87.8% specificity, 50% PPV and 93.5% NPV.

Conclusion
Xpert assays showed higher sensitivity than Anyplex for the detection of MTC in respiratory samples and showed higher specificity compared to Anyplex in both respiratory and non- respiratory samples. Xpert showed higher PPV for respiratory samples, indicating its superiority disregarding true positive cases.

Disclosures
All Authors: No reported disclosures
P-2080. Impact of the Implementation of Multiplex Gastrointestinal PCR Panel on Antimicrobial Use for Infectious Diarrhea
Authors: Mangum Blake R , Smith Richard D , Sandruck Matthew , Kristie Johnson J , Luethy Paul , Claeys Kimberly C 
Published: January 2025

Abstract

Background
Rapid molecular methods, such as BioFire FilmArray™ Gastrointestinal (GI) Panel, have become common in clinical practice. The GI Panel identifies 22 GI pathogens in approximately 1 hour. We evaluated antimicrobial prescribing before and after the implementation of the GI Panel to see the impact on appropriate prescribing for infectious diarrhea and to identify quality improvement areas for antimicrobial stewardship moving forward.Figure 2:Percent Type of Antibiotic Change After Result of Diagnostic Testing

Methods
This retrospective cohort analysis compared antimicrobial prescribing practices for infectious diarrhea one year before and after the implementation of the BioFire GI Panel at the University of Maryland Medical Center (UMMC) in August 2021. Prior to GI Panel implementation at UMMC, the major diagnostic tests for infectious diarrhea were stool culture, ova and parasite smear, and a parasite PCR. Cases were randomly selected with an even distribution from each month from August 2019 to August 2022. Appropriateness of empiric and definitive management was assessed based on diarrhea type (bloody, acute, or prolonged), the patient's immune status, travel history, clinical presentation, and antibiotic selection.

Results
353 patients were included: 179 pre-GI panel implementation and 174 post-implementation. Empiric antibiotic therapy for infectious diarrhea was started in 47/179 (26.3%) of the pre-panel group and 50/174 (28.7%) of the post-panel (P = 0.601). The diagnostic tests resulted in positive organism identification in 10% of patients in the pre-group, while positive identification increased to 19.4% post-group (P = 0.012). When an organism was identified, 12/33 (66.7%) of the post-panel group received antibiotic therapy, while only 6/18 (33.3%) of the pre-panel group received antibiotics (P = 0.83)

Conclusion
Our analysis showed that many patients did not have antimicrobial therapy for infectious diarrhea, which was impacted by the diagnostic test. The increased sensitivity to detect organisms in the GI Panel may account for the increased utilization of definitive antimicrobials in the post-implementation cohort.

Disclosures
J Kristie Johnson, PhD, D (ABMM), biomerieux: has given presentations/speeches for the company listed above Kimberly C. Claeys, PharmD, PhD, bioMérieux: Advisor/Consultant|bioMérieux: Honoraria
P-2090. Using MRSA Nares PCR to Predict MRSA Purulent Skin and Soft Tissue Infections
Authors: Greene William , Aslam Sadaf 
Published: January 2025

Abstract

Background
Skin and soft tissue infections (SSTI) are divided into purulent vs non-purulent with the former necessitating the need for methicillin resistant staph aureus MRSA antimicrobial coverage per IDSA guidelines for management of SSTI. MRSA nares PCR screening for MRSA pneumonia has demonstrated high negative predictive value (NPV) (98.1%) for MRSA associated community-acquired pneumonia (CAP) and hospital-acquired pneumonia (HAP). Studies evaluating MRSA nares PCR to predict MRSA infection involving other anatomical sites including skin/soft tissue have shown mixed results. This retrospective cohort study seeks to further evaluate the utility of MRSA nares PCR in predicting MRSA associated purulent SSTI including in relation to anatomical site of the skin infection (above the waist line vs below the waist line).

Methods
We performed a retrospective medical record review of patients admitted to the hospital or evaluated in the emergency department with SSTI between 1/1/2015-11/30/2022. Patients 18 years or older with a diagnosis of purulent cellulitis were included if they had a MRSA nares PCR result and a positive culture for staph aureus from either a purulent wound culture swab or an abscess incision/drainage culture. Medical records were reviewed to confirm a diagnosis of purulent cellulitis including physician documentation and pictures of associated skin infections when available. The anatomic site of the SSTI were recorded.

Results
85 patients were included in the final analysis. MRSA nares PCR for MRSA SSTI had a negative predictive value (NPV) of 66.7% and positive predictive value (PPV) of 96.8%. The sensitivity and specificity of MRSA nares PCR for MRSA SSTI was 62.5% and 97.3% respectively. The NPV of MRSA nares PCR for MRSA SSTI above the waist was 71% vs 63% below the waist.

Conclusion
Our results are consistent with other studies showing high specificity and low sensitivity for MRSA nares PCR in predicting MRSA SSTI. However, the NPV was much lower in this cohort compared to other studies. These results do not support the use of MRSA nares PCR to rule out MRSA SSTI. Clinicians should continue to use clinical exam (purulent vs non-purulent) and microbiologic data when available to guide antimicrobial coverage of MRSA when treating patients with SSTI.

Disclosures
All Authors: No reported disclosures
P-2098. Clinical culture rates among hospitalized patients in the United States, 2012-2021
Authors: Wolford Hannah , McCarthy Natalie , Baggs James , Reddy Sujan , Lutgring Joseph D 
Published: January 2025

Abstract

Background
Microbial cultures are used in clinical care and to track trends in infectious diseases. Changes in culturing practices may affect these trends but have not been thoroughly explored. This analysis examines temporal and facility variability of clinical cultures among a cohort of acute care hospitals in the U.S. from 2012-2021.

Methods
We used microbiology data from a dynamic cohort of hospitals reporting data to the PINC-AI Healthcare Database from 2012-2021. Surveillance cultures and hospitals with outlier hospital-months were excluded. We defined admission cultures as those collected on or before calendar day 3 of hospitalization and post-admission cultures as those collected after calendar day 3. Admission culture rates were calculated per 1,000 discharges. Post-admission culture rates were calculated per 1,000 patient days. We calculated overall rates as well as rates stratified by specimen source (blood, respiratory, urine, other sterile sites, and other non-sterile sites). To account for multiple blood culture sets, only the first blood culture per patient per day was counted in this analysis.

Results
From 2012-2021, 361 hospitals were included in our cohort. Admission culture rates remained stable from 2012 through 2019. Admission culturing rates and facility variability increased in 2020 and 2021 (Fig. 1). Post-admission culture rates decreased from 2012 to 2016 and then plateaued; increases in rates and facility variability were noted in 2020 and 2021 (Fig. 2). Admission blood cultures increased over time and admission urine cultures decreased; respiratory and other non-sterile site cultures increased in 2020 and 2021 (Fig. 3). Most types of post-admission cultures declined from 2012-2016; post-admission blood cultures increased between 2016-2021 (Fig. 4).

Conclusion
Both admission and post-admission cultures increased during the early years of the COVID-19 pandemic, and these increases were driven by respiratory, other non-sterile, and blood cultures (which increased since 2016). Prior to 2020, culturing trends differed by specimen type and timing of culture. Assessing factors that contribute to testing tends and facility variability can inform diagnostic stewardship efforts and increase understanding of how testing changes may impact infection rates.

Disclosures
All Authors: No reported disclosures
P-2118. False-positive Aspergillus Galactomannan Test in Multiple Myeloma
Authors: Nakamura Shingen , Maeda Yusaku , Sumitani Ryohei , Oura Masahiro , Sogabe Kimiko , Yagi Hikaru , Fujii Shiro , Harada Takeshi , Miki Hirokazu 
Published: January 2025

Abstract

Background
Invasive pulmonary aspergillosis (IA) is a common infectious disease in patients with hematological diseases. The prevention, early detection, and establishment of treatment strategies for IA are important clinical issues. One of the mycological tests for IA is the serum galactomannan antigen (GM), which is included in the European Organization for Research and Treatment of Cancer-Invasive Fungal Infections Cooperative Group/National Institute of Allergy and Infectious Diseases Mycosis Study Group (EORTC/MSG) mycological criteria and is widely used because of its high sensitivity and specificity. However, whether this method is useful for all diseases and situations is unclear.

Methods
We retrospectively analyzed the results of all GM tests performed in our department between April 2003 and January 2012.

Results
Of 330 cases and 2155 samples, 540 (25%) were positive (0.5≦). The positivity rates for underlying diseases were 10.1%, 6.6%, 4.8%, 20%, 21.2%, and 61.3% for acute myeloid leukemia, acute lymphoblastic leukemia, chronic myelogenous leukemia, myelodysplastic syndrome, lymphoma, and multiple myeloma, respectively, with the highest positivity rate for myeloma. By type, IgG, IgA, Bence Jones protein, and IgD were 71.7%, 33.3%, 57.1%, and 34.6%, respectively, and the positivity rate of IgG type was high. All 18 IgG-positive cases at the time of diagnosis of MM were false positives according to the 2019 EORTC/MSG criteria. There was no direct correlation between the IgG and GM values. Of the 18 false-positive cases, 12 patients received antifungal prophylaxis, two of whom developed IA during treatment with steroids, and five who did not receive prophylaxis did not develop IA. When the Aspergillus antigen was measured using the serum from which IgG-type monoclonal protein in some patients with IgG-type myeloma was purified and extracted using protein G, the Aspergillus antigen values decreased.

Conclusion
Although it is possible that the GM test for myeloma captures subclinical IA, the GM antigen test may be prone to false positives in IgG-type myeloma, and the results should be interpreted with caution.

Disclosures
All Authors: No reported disclosures
P-2119. Development of a Machine-Learning-Based Prediction Model for Candidemia Diagnosis
Authors: Lee Chaeryoung , Wang Da Woon , Hong Sung Kwan , Han Hyun Wook , Kim Jong Hun 
Published: January 2025

Abstract

Background
Early recognition and prompt initiation of antifungal therapy for candidemia substantially reduce morbidity and mortality. However, differentiating candidemia from bacteremia remains a clinical challenge and often results in delays in antifungal treatment. This study aimed to develop a machine-learning-based prediction model for candidemia.Figure 1.Receiver Operating Characteristic (ROC) Curves for Machine-Learning-Based Prediction Models for Candidemia

Methods
We conducted a single-center retrospective cohort study involving adult patients diagnosed with candidemia from 2014 to 2021, who were included as cases. Control patients, defined as adults with bacteremia, were randomly selected during the same timeframe. Patients with concurrent bacterial and candida infections were excluded. The event time was defined as the moment of blood culture collection for diagnosing each case of candidemia and bacteremia. Clinical data collected at the event time included vital signs (systolic blood pressure and heart rate), epidemiologic, and laboratory data. In total, 55 types of clinical variables were collected. Nine different machine learning algorithms—XGBoost, Random Forest, Logistic Regression, Support Vector Machine, Multinomial Naive Bayes, K-Nearest Neighbors, AdaBoost, CatBoost, and an ensemble incorporating CatBoost and AdaBoost—were utilized to develop a machine-learning-based prediction model for candidemia. The model demonstrating the highest area under the receiver operating characteristic curve (AUROC) was selected for further analysis. Model performance was assessed based on accuracy, precision, recall, and F1 score.

Results
The cohort included 261 patients with candidemia and 522 with bacteremia, with a median age of 68 years. The AUROC for the models varied from 0.439 to 0.895. The ensemble model achieved the highest AUROC of 0.895 (Figure 1). For this ensemble model, the F1 score was 0.853, recall was 0.849, precision was 0.862, and accuracy was 0.849.

Conclusion
A machine-learning-based prediction model could be a useful tool for identifying high-risk patients for the early diagnosis of candidemia.

Disclosures
All Authors: No reported disclosures
P-2180. Linkage to Care, Treatment Initiation, and Outcomes in Individuals with Hepatitis B Virus Infection With and Without Cirrhosis
Authors: Butt Adeel A , Yan Peng , Shaikh Obaid , Bedimo Roger 
Published: January 2025

Abstract

Background
Screening for hepatitis B virus (HBV) is far from ideal. Linkage to care is also poor. While traditional models suggest a progression of liver disease from fibrosis to cirrhosis to hepatic decompensation and hepatocellular carcinoma (HCC), emerging evidence suggest that terminal outcomes can occur without preceding cirrhosis. Our aim was to define the cascade of care for HBV and clinical outcomes in HBV infected individuals with and without cirrhosis in the US VA healthcare system.
Annual numbers of individuals with newly diagnosed hepatitis B virus infection and numbers initiated on treatment.

Methods
Within the Veterans Health Administration (VA) national databases, we identified all individuals with a positive HBsAg, HBeAg, or HBV DNA between 2002-2023. We tabulated the number of new infections per year and numbers initiated on treatment. We also calculated the incidence rates for development of cirrhosis, hepatic decompensation (HD), hepatocellular carcinoma (HCC), and death among HBV+ individuals.
Outcomes in individuals with hepatitis B virus infection who were free of cirrhosis at baseline.

Results
Of the 44,951 individuals with HBV, 62.9% were referred to gastroenterology, hepatology, or infectious disease specialist. Only 14.5% were initiated on an approved HBV treatment regimen. The mean time to treatment initiation was 34.1 months. Among 38,472 individuals without baseline cirrhosis, the incidence rates/100 person years (95% CI) for cirrhosis, HD, HCC, and death were 0.60 (0.58,0.63), 0.72 (0.69,0.75), 0.49 (0.47,0.52), and 4.29 (4.22,4.35) respectively.

Conclusion
While the incidence rates for liver related complications and death are high among those with HBV infection, large gaps remain in linkage to care and treatment initiation. Terminal events, e.g. hepatic decompensation and HCC, can occur without antecedent cirrhosis, highlighting the need for early screening, diagnosis and treatment. Focused interventions are required to bridge these gaps in care.

Disclosures
Adeel A. Butt, MD, MS, Gilead Sciences: Grant/Research Support
P-2216. The characteristics of human microbiome and fecal resistome in patients with recurrent urinary tract infection
Authors: Kim Bongyoung , Kim Yerin , Na Yeseul , Kim Jeoungyeon , Jang Wooyoung , Go Ji Won , Kim Jinnam , Park Se Yoon , Lee Yangsoon , Pai Hyunjoo , Rho Mina 
Published: January 2025

Abstract

Background
While uropathogenic E. coli (UPEC) is recognized as a primary causative agent of recurrent urinary tract infections (rUTIs), the factors contributing to its colonization remain poorly understood. The study aims to elucidate the characteristics of the human microbiome in patients with rUTI.
Bacterial proportion in genus level: PCoA (distance: Bray-Curtis dissimilarity)

Methods
A prospective study was conducted at a tertiary-care hospital (850 beds) in Korea from August 2021 to November 2023. All female adults (aged ≥19 years) hospitalized with upper UTI were screened daily for inclusion if they met the following criteria: i) E. coli was confirmed as causative pathogen, ii) no structural abnormalities in the urinary tract were present, and iii) patients agreed to participate in the study. Individuals diagnosed with UTI after 48 hours of admission or those transferred from other hospitals were excluded. Fresh stool samples were collected after 28 days of completion of antibiotic treatment, and whole metagenome sequences were obtained using Illumina HiSeq sequencing. Patients with a history of UTI within the past year were defined as having rUTI. We analyzed the characteristics of the microbiome in rUTI patients compared with those in non-rUTI patients as well as the healthy population (n=214), which had already been analyzed in other studies.
Bacterial proportion in genus level: Top 7 genera in each dataset

Results
A total of 51 cases were initially enrolled, but three samples failed to pass the quality check. Consequently, 48 cases (including 13 with rUTI) were included in the final analysis. Among UTI patients, the dominant genera observed were Blautia (7.7%), Bacteroides (7.6%), Faecalibacterium (4.3%), and Bifidobacterium (3.5%). Principal coordinates analysis (PCoA) revealed that the overall distribution of the microbiome in rUTI patients exhibited a distinct pattern compared to non-rUTI patients. Additionally, the proportion of Faecalibacterium and Prevotella was lower in rUTI patients compared to non-rUTI patients and the healthy population. Regarding antibiotic resistance genes (ARGs), rUTI patients showed a lower proportion of ACI and CatS compared to non-rUTI patients and the healthy population.
ARG abundance (RPKM) in gene family level: PCoA (distance: Bray-Curtis dissimilarity)

Conclusion
Some differences observed in the distribution of microbiome and resistome between patients with rUTI and non-rUTI or healthy population.
ARG abundance (RPKM) in gene family level

Disclosures
All Authors: No reported disclosures