OBJECTIVES/GOALS: Chronic or new symptoms after infection with severe-acute-respiratory-coronavirus-2 (SARS-CoV-2) has been termed post-acute sequelae of Covid-19 (PASC) or Long Covid. Our objective is to present results from COVID-OUT, a phase 3 double-blind, randomized controlled trial of early outpatient treatment of Covid-19 with repurposed medications. METHODS/STUDY POPULATION: COVID-OUT enrolled adults age 30 to 85 with overweight or obesity who had proof of SARS-CoV-2 infection and fewer than 7 days of symptoms. In this 2 by 3 factorial design trial of metformin, ivermectin, fluvoxamine, or exact-matching placebo of each medication, participants were randomized 1:1:1:1:1:1 to the 6 treatment allocations. This abstract focuses on whether early treatment with metformin prevented Long Covid. Immediate release metformin was titrated to 1500mg daily over the first 6 days. We assessed the incidence of clinician-diagnosed Long Covid with follow up through 10 months after enrollment. We also assessed where participants were diagnosed with Long Covid, and where they received Long Covid treatment. RESULTS/ANTICIPATED RESULTS: Of 1124 participants, 98 (8.7%) report having a healthcare provider make a diagnosis of long covid. By arm, 6.9% (39/564) of metformin participants report having a diagnosis for long covid as compared with 10.5% (59/560) of matched placebo controls. The absolute reduction attributable to metformin was 3.6% (95%CI, 0.3% to 7.0%; P=0.031) with a relative risk reduction of 34% (95%CI, 3% to 55%). The metformin cost per long covid case averted was $28 (95%CI, $15 to $306). 10-month follow-up data will be available at the time of presentation as well as an analysis of baseline factors associated with the development of Long-Covid, independent of treatment allocation in the trial. DISCUSSION/SIGNIFICANCE: Metformin reduced the incidence of clinician-diagnosed long covid by 34% in a double-blind randomized placebo-controlled trial, and previous research published in-vitro activity by metformin against SARS-CoV-2 and other RNA viruses. Further investigation of metformin as early treatment for SARS-CoV-2 is warranted.

ABSTRACT IMPACT: This study aims to provide insight into naturally acquired immunity against severe malaria, thereby laying the foundation for the design of novel vaccine candidates to prevent severe disease as well as monoclonal antibody therapies to treat severe malaria. OBJECTIVES/GOALS: Severe malaria is caused by parasite surface antigens that contain high sequence diversity. Nevertheless, P. falciparum-exposed individuals develop antibody responses against these antigens. Our goal is to isolate antibodies with broad reactivity to understand how disease protection is acquired. METHODS/STUDY POPULATION: Our study cohort consists of Ugandan adults living in a malaria-endemic region with high transmission intensity, who are protected against severe malaria. Using fluorescently labeled probes of parasite surface antigens, we have isolated antigen-specific B cells from these donors. We then expressed the corresponding monoclonal antibodies in vitro. These antibodies were screened against a library of variant surface antigens to determine antibody breadth and potential to inhibit interaction of the parasite surface antigen with host receptors, a critical step in pathogenesis. Additionally, using a panel of variant surface antigen mutants, we have predicted the epitopes targeted by the broadest monoclonal antibodies. RESULTS/ANTICIPATED RESULTS: We have identified three monoclonal antibodies with exceptionally broad reactivity and inhibitory activity against our panel of severe disease-inducing variant surface antigens. We have identified two major sites targeted by these broadly reactive antibodies. The first site was associated with the largest breadth, but limited inhibitory potential, while the second site showed high-affinity antibody binding and inhibition of receptor binding. Interestingly, two of these three antibodies were very similar in structure, even though they were isolated from different donors. Isolation of antigen-specific B cells from additional donors will enable us to identify how common such broadly reactive antibodies are and allow the identification of additional epitopes DISCUSSION/SIGNIFICANCE OF FINDINGS: This study is the first to isolate broadly reactive antibodies that are likely to protect against severe malaria in naturally immune individuals. Further characterization of antibody-antigen interactions will inform the development of this surface antigen as a vaccine candidate for malaria.

OBJECTIVES/GOALS: The Penn State CTSI has been working diligently to help communities in their fight against COVID-19. As the rapidly evolving COVID-19 situation has unfolded the Penn State CTSI has been able to provide support to our community stakeholders. As our communities have and are faced with unprecedented challenges, our CTSI has been there every step of the way. METHODS/STUDY POPULATION: The Penn State CTSI is unique as it sits in rural Pennsylvania that not only spans a wide catchment area but also many diverse communities. The Penn State CTSI connected with our communities throughout the pandemic to bring timely and culturally appropriate information about the novel COVID-19 pandemic through our own institution and in partnership with community leaders. Stakeholder boards were formed to hear from various communities about hardships and challenges that were and are being faced due to COVID-19. RESULTS/ANTICIPATED RESULTS: The Penn State CTSI provided our communities with information through various different platforms to ensure that needs were being met in dissemination of pertinent information related to COVID-19. No only was information tailored to the specific needs that were discussed during stakeholder boards, the information was provided in different languages and platforms in order to meet cultural and other needs to ensure health equity and literacy were met. DISCUSSION/SIGNIFICANCE: Not only did the Penn State CTSI provide these services to our current community partners new partnerships were formed to create stronger alliances amongst those being serve. Members of the Penn State CTSI were invited to serve on state and local advisory bords and became trusted messengers in our communities.

OBJECTIVES/GOALS: Recent studies indicate B cells are involved in dermal fibroblast activation and collagen deposition in the skin. However, B cell distribution in epidermal and dermal layers is unknown. Here, We aim to characterize the distribution of B cells residing in normal skin and keloidal scars. METHODS/STUDY POPULATION: One abdominal normal skin sample and two keloid samples (ear and shoulder) were obtained from the University of Colorado Biorepository Core Facility and from the Plastic Surgery Clinics. Five micron sections from formalin-fixed paraffin-embedded samples were prepared for multiplex fluorescence immunohistochemistry by the Human Immunology & Immunotherapy Initiative. We stained for CD20+, CD19+, and DAPI. Slides were imaged using Vectra®3 scanning system from PerkinElmer. Images were analyzed in InForm®Tissue Finder, phenotpr, phenoptrReports by Akoya biosciences. RESULTS/ANTICIPATED RESULTS: We found a significant increase in the percentage of CD20+ and CD19+ B cells in keloid skin compared to normal skin tissue (14.50% and 14.20% vs 6.47% and 7.56% of the total cells), respectively. Interestingly, we found that in the epidermis of keloid skin CD20+ cell were more abundant (14.46%) whereas in the epidermis normal skin CD20+ cells were less predominant (5.14%). In the dermis of keloid skin, CD20+ and CD19+ were in equal proportions (13%) whereas in normal skin CD19+ cells were more predominant (10.44%) compared to CD20+ cells (7.04%). Dual positive B cells, CD19+/CD20+ cells, were more abundant in keloid dermis (11.06%) compared to normal skin dermis (1.24%). DISCUSSION/SIGNIFICANCE OF IMPACT: B cells are involved in fibroblast activation in diseases such as scleroderma and rheumatoid arthritis. With the increase of CD19+/CD20+ B cells in keloids, the role of B cells in keloid pathogenesis warrants further study. CD27 staining may determine if these are activated or follicular B cells.

OBJECTIVES/SPECIFIC AIMS: Cardiovascular diseases (CVD) is the leading cause of death worldwide in both men and women due to lack of cardiac regeneration after disease or damaged is caused. There are many challenges to studying CVD since native cardiomyocytes cannot be cultured in vitro. With the advancements in biomaterial and pluripotent stem cells research, scientists are now able to produce engineered cardiac tissue models in vitro that mimic the native myocardium. This study shows our methods for producing engineered cardiac tissue with potential applications in cardiac regeneration, disease modeling, and scalable production. METHODS/STUDY POPULATION: In this study, human induced pluripotent stem cells (hiPSCs) were combined with two different photocrosslinkable hybrid biomaterials, poly (ethylene)- glycol fibrinogen (PF) and gelatin methacrylate (GelMa), in various tissue geometries to form 3D human engineered cardiac tissues (3D-hECTs). To study tissue growth and contraction, image and video analysis was performed at specific timepoints. To analyze differentiation efficiency and cell population, flow cytometry was performed using cardiac markers. To evaluate gene expression, qPCR was performed using pluripotency and cardiac specific primers. RESULTS/ANTICIPATED RESULTS: Direct cardiac differentiation of encapsulated hiPSCs resulted in synchronously contracting 3D-hECTs in both biomaterials and all tissue geometries. Spontaneous contractions started on Day 7 and increased in velocity, frequency, and synchronicity over time. 3D-hECTs had high cell viability with > 70% of cells positive for cardiac markers. Engineered tissues showed appropriate temporal changes in gene expression over time with pluripotency gene expression decreasing and cardiac gene expression increasing. DISCUSSION/SIGNIFICANCE OF IMPACT: This study shows the potential for direct differentiation of encapsulated hiPSCs to produce physiologically relevant engineered cardiac tissues. Resulting 3D-hECTS showed features of mature myocardium with appropriate cardiomyocyte populations, mechanical motion, and gene expression. Using this platform, we are able to produce engineered cardiac tissue in a variety of biomaterials and tissue geometries to study new therapeutics, mechanism of disease, and scalable tissue culture.

OBJECTIVES/SPECIFIC AIMS: Key factors causing irreproducibility of research include those related to inappropriate study design methodologies and statistical analysis. In modern statistical practice irreproducibility could arise due to statistical (false discoveries, p-hacking, overuse/misuse of p-values, low power, poor experimental design) and computational (data, code and software management) issues. These require understanding the processes and workflows practiced by an organization, and the development and use of metrics to quantify reproducibility. METHODS/STUDY POPULATION: Within the Foundation of Discovery – Population Health Research, Center for Clinical and Translational Science, University of Utah, we are undertaking a project to streamline the study design and statistical analysis workflows and processes. As a first step we met with key stakeholders to understand the current practices by eliciting example statistical projects, and then developed process information models for different types of statistical needs using Lucidchart. We then reviewed these with the Foundation’s leadership and the Standards Committee to come up with ideal workflows and model, and defined key measurement points (such as those around study design, analysis plan, final report, requirements for quality checks, and double coding) for assessing reproducibility. As next steps we are using our finding to embed analytical and infrastructural approaches within the statisticians’ workflows. This will include data and code dissemination platforms such as Box, Bitbucket, and GitHub, documentation platforms such as Confluence, and workflow tracking platforms such as Jira. These tools will simplify and automate the capture of communications as a statistician work through a project. Data-intensive process will use process-workflow management platforms such as Activiti, Pegasus, and Taverna. RESULTS/ANTICIPATED RESULTS: These strategies for sharing and publishing study protocols, data, code, and results across the spectrum, active collaboration with the research team, automation of key steps, along with decision support. DISCUSSION/SIGNIFICANCE OF IMPACT: This analysis of statistical methods and process and computational methods to automate them ensure quality of statistical methods and reproducibility of research.

OBJECTIVES/GOALS: Under enrollment of trials is a continued challenge in clinical research. In response, the Oregon Clinical and Translational Research Institute (OCTRI), the CTSA at Oregon Health & Science University (OHSU), launched a central resource, OCTRI Recruitment, to equip researchers with the knowledge and tools needed for recruitment success. METHODS/STUDY POPULATION: OCTRI Recruitment focused programmatic development in response to the voice of OHSU researchers. In 2018, a qualitative assessment project, “Clinical Research Recruitment Methods at OHSU”, was launched, which included a survey (N=100) and optional interview (N=24), to determine recruitment method utilization and experience, along with opinions on the needs and culture of recruitment at OHSU. In 2022, as part of the same protocol project, a second survey was deployed (N=31), to determine changes in recruitment method use and to identify further recruitment challenges. OCTRI Recruitment also obtains continual informal input on perceived recruitment challenges and opportunities through engagement within the OHSU research team community. RESULTS/ANTICIPATED RESULTS: 2018 survey and interviews showed: many researchers relied on their clinic’s patient population for recruitment (74%); were unaware of available tools to recruit OHSU patients, especially informatics tools (5-22%); and were not aware of and minimally use methods to recruit outside OHSU (<40%). In response, OCTRI Recruitment developed and began recruitment consultations, guidance materials, and educational seminars. In 2022, survey results showed an increase in the use of informatics-based recruitment tools (2-14%+) and increased use of methods focused on individuals outside of OHSU (1-7%+). Additionally, a review of studies post OCTRI Recruitment consultation over three years (N=51) showed that of those studies, 40% increased enrollment numbers and 61% increased team’s confidence level post consult. DISCUSSION/SIGNIFICANCE: This approach to program creation allowed for a uniquely targeted development of services in response to the voice of OHSU researchers and recruitment challenges. Based on additional data, efforts have begun to address the recruitment challenges of a study opportunity website, participant compensation methods, and community-based recruitment.

Community involvement in research is key to translating science into practice, and new approaches to engaging community members in research design and implementation are needed. The Community Scientist Program, established at the MD Anderson Cancer Center in Houston in 2018 and expanded to two other Texas institutions in 2021, provides researchers with rapid feedback from community members on study feasibility and design, cultural appropriateness, participant recruitment, and research implementation. This paper aims to describe the Community Scientist Program and assess Community Scientists' and researchers' satisfaction with the program. We present the analysis of the data collected from 116 Community Scientists and 64 researchers who attended 100 feedback sessions, across three regions of Texas including Northeast Texas, Houston, and Rio Grande Valley between June 2018 and December 2022. Community Scientists stated that the feedback sessions increased their knowledge and changed their perception of research. All researchers (100%) were satisfied with the feedback and reported that it influenced their current and future research methods. Our evaluation demonstrates that the key features of the Community Scientist Program such as follow-up evaluations, effective bi-directional communication, and fair compensation transform how research is conducted and contribute to reducing health disparities.

Structural racism in the USA has roots that extend deep into healthcare and medical research, and it remains a key driver of illness and early death for Black, Indigenous, People of Color (BIPOC). Furthermore, the persistence of racism within academic medicine compels an interrogation of education and research within this context. In the spirit of this interrogation, this article highlights a unique model of community-engaged education that integrates cultural humility. As an individual and institutional stance, cultural humility denotes lifelong learning and self-critique, the mitigation of power imbalances, and accountability. The integration of cultural humility emphasizes that when space is created for BIPOC communities to lead the way, education regarding healthcare and research can be effectively reimagined. Demonstrating this effectiveness, six community partners led the development and implementation of a five-module Structural Racism in Healthcare and Research course. Using a cohort model approach, the pilot course enrolled 12 community members and 12 researchers. The curriculum covered topics such as history of racism in healthcare and research, and introduced participants to a cultural resilience framework. Evaluation results demonstrated a significant increase in participants’ knowledge and ability to identify and take action to address inequities related to racism in healthcare and research.

OBJECTIVES/GOALS: The objective of this study is to define the molecular mechanisms that control survival of malignant stem cells in acute myeloid leukemia (AML). Leukemia stem cells (LSCs) are not effectively eradicated by standard treatment and lead to resistance and relapse, which contribute to poor survival rates. METHODS/STUDY POPULATION: The recently FDA approved venetoclax, a BCL2 inhibitor, with azacitidine, a hypomethylating agent leads to a 70% response rate in AML patients. Analysis of patients treated with this regimen showed direct targeting of LSCs. BCL2 has a non-canonical function in regulation of intracellular calcium. To determine how BCL2 mediated calcium signaling plays a role in LSC biology, we used LSCs isolated from venetoclax/azacitidine (ven/aza) sensitive and resistant patient samples to measure expression of calcium channels via RNA seq. BIO-ID, siRNA, flow cytometry, seahorse assays, calcium measurements and colony assays were used to determine the effects of calcium channel perturbation on LSC biology. RESULTS/ANTICIPATED RESULTS: BCL2 inhibition leads to decreased OXPHOS activity in primary AML specimens. BIO-ID studies revealed cation/metal ion transporters, ER membrane proteins and ER membrane organization as top enriched pathways interacting with BCL2. RNA-seq data showed increased expression of genes involved in calcium influx into the ER in ven/aza sensitive LSCs and increased expression of genes involved in calcium efflux from the ER in ven/aza resistant samples. Ven/Aza resistant LSCs have increased mitochondrial calcium content, consistent with their increased OXPHOS activity as calcium is required for OXPHOS. Perturbation of these channels leads to decreased OXPHOS activity and decreased viability in LSCs. DISCUSSION/SIGNIFICANCE OF IMPACT: We postulate that a deeper understanding of the mechanisms behind ven/aza targeting of LSCs will lead to the development of novel therapies for patients who do not respond to ven/aza. Our data show targeting intracellular calcium signaling could be a viable therapeutic strategy for AML patients.

OBJECTIVES/SPECIFIC AIMS: Historically, logistic regression algorithms (LRAs) have failed to differentiate strangulated small bowel obstructions (SBOs) from nonstrangulated SBOs. Our hypothesis is that a machine learning algorithm (MLA) can differentiate strangulated from simple SBOs better than an LRA can. METHODS/STUDY POPULATION: We used records of patients presenting with acute SBO and managed with exploratory laparotomy to test and train algorithms. We compared MLA to LRA via area under the receiver operating characteristic curve (AUROC) and cut-off points maximizing sensitivity and specificity. RESULTS/ANTICIPATED RESULTS: With 192 patient records, the AUROC of the MLA was 0.85. At the sensitivity cutoff, the MLA had 100% sensitivity and 55% specificity. At the specificity cutoff, the MLA had 45% sensitivity and 100% specificity. We anticipate improvements as more records are incorporated, and that LRA will underperform MLA across all measures. DISCUSSION/SIGNIFICANCE OF IMPACT: Our MLA represents a significant improvement over past LRAs, and may provide decision assistance to surgeons managing SBO. If this MLA maintains its high sensitivity, it may be used in the future to prevent unnecessary surgeries.

OBJECTIVES/GOALS: Identification of COVID-19 patients at risk for deterioration following discharge from the emergency department (ED) remains a clinical challenge. Our objective was to develop a prediction model that identifies COVID-19 patients at risk for return and hospital admission within 30 days of ED discharge. METHODS/STUDY POPULATION: We performed a retrospective cohort study of discharged adult ED patients (n = 7,529) with SARS-CoV-2 infection from 116 unique hospitals contributing to the national REgistry of suspected COVID-19 in EmeRgency care (RECOVER). The primary outcome was return hospital admission within 30 days. Models were developed using Classification and Regression Tree (CART), Gradient Boosted Machine (GBM), Random Forest (RF), and least absolute shrinkage and selection (LASSO) approaches. RESULTS/ANTICIPATED RESULTS: Among COVID-19 patients discharged from the ED on their index encounter, 571 (7.6%) returned for hospital admission within 30 days. The machine learning (ML) models (GBM, RF,: and LASSO) performed similarly. The RF model yielded a test AUC of 0.74 (95% confidence interval [CI] 0.71–0.78) with a sensitivity of 0.46 (0.39-0.54) and specificity of 0.84 (0.82-0.85). Predictive variables including: lowest oxygen saturation, temperature; or history of hypertension,: diabetes, hyperlipidemia, or obesity, were common to all ML models. DISCUSSION/SIGNIFICANCE: A predictive model identifying adult ED patients with COVID-19 at risk for return hospital admission within 30 days is feasible. Ensemble/boot-strapped classification methods outperform the single tree CART method. Future efforts may focus on the application of ML models in the hospital setting to optimize allocation of follow up resources.

ABSTRACT IMPACT: This work has the potential to identify targetable pathways conveying resistance to PARP inhibitors that may improve ovarian cancer patient outcomes. OBJECTIVES/GOALS: High grade serous ovarian cancer is the deadliest gynecologic malignancy. PARP inhibitors are an FDA approved targeted therapy that is being used more and more frequently in the clinic. It is vital to understand mechanisms driving resistance to this therapy in order to develop treatments to improve patient responses. METHODS/STUDY POPULATION: RNA-sequencing and transcription factor analysis was used to identify pathways of interest. An AP-1 transcriptional reporter assays was used to confirm results of the transcription factor analysis. An unbiased lentiviral shRNA screen was used to identify AP-1 subunits promoting PARP inhibitor resistance. Lentiviral transduction allowed for the knockdown ATF6. Comet assays and two-plasmid systems were used to determine levels of DNA damage and levels of DNA damage repair respectively. RESULTS/ANTICIPATED RESULTS: PARP inhibitor resistant cell lines have increased WNT signaling which promotes to increased DNA damage repair. PARP inhibitor resistant cell lines also have increased AP-1 transcriptional activity, ATF6 expression, and active p38. ATF6 knockdown and p38 inhibition is sufficient to resensitize cells to PARP inhibition. Upon treatment with PARP inhibitors, ATF6 knockdown as well as p38 inhibition lead to increased DNA damage in PARP inhibitor resistant cell lines. RNA-sequencing reveals a signifcant overlap in downregulated genes in cells treated with a β-catenin inhibitor and cells with an ATF6 knockdown. DISCUSSION/SIGNIFICANCE OF FINDINGS: Due to the increasing prevalence of PARP inhibitors in the clinic, it is vital to uncover mechanisms contributing to resistance. This work has the potential to identify targetable pathways conveying resistance to PARP inhibitors that may improve ovarian cancer patient outcomes.

OBJECTIVES/SPECIFIC AIMS: The objective of this partnership was to create a global network of clinical and public health researchers and communities conducting technology-assisted research in noncommunicable disease. METHODS/STUDY POPULATION: The University of Rochester’s Clinical and Translational Science Institute (CTSI) has successfully leveraged the informatics core’s capacity into an emerging network of organizations that focus on technology and health in settings outside of the mainland United States. The CTSI coordinated with another NIH-funded infrastructure program [the RCMI Translational Research Network (RTRN)] to identify partner institutions interested in technology and health. RTRN identified the University of Puerto Rico and the University of Hawaii, both of which serve as hubs for common research interests in technology and health throughout the Caribbean and the Pacific. This network was formalized as the CDC’s Coordinating Center for its Global and Territorial Health Research Network (the “Global Network”), with additional US partners (Yale, University of Illinois at Chicago, University of North Caroline Chapel Hill, and the University of South Florida) within a wider scope of the CDC’s Prevention Research Centers (PRC) program. RESULTS/ANTICIPATED RESULTS: Through combining 2 main NIH-funded research infrastructure networks (CTSA and RTRN), with a large CDC-funded PRC, the University of Rochester’s Informatics Core was successful in establishing a new productive global health network throughout Latin America and the Caribbean, and in the Pacific, garnering additional research support from NIH Fogarty and other programs. The resulting network not only supports locally-important research in technology and health on compelling health issues (eg, diabetes, ZIka, participation in research), but also facilitates community engagement through local partnerships and the cores of the involved networks. In addition, much of the information and communications technology (ICT)-related research and learnings from the Global Network activity is immediately applicable to populations in the United States, served by the various collaborative networks. In total, while new, the Global Network supports a wide range of projects and engagements throughout the world that expand local informatics capacity and use of technology in the research process and to address global health problems, further enhancing the CTSI’s informatics core to serve the needs of its own constituency and promote research engagement with technology within this population. Local research collaborative projects reinforce the utility of the network and its resources, evidenced by tools, publications, partnerships, and conference presentations that have arisen. Lessons to date from this Global Network collaboration include: specific global research projects provide opportunities for partnership building and meaningful collaboration, team science is of central importance in distributing the work of the network, synergy is multidirectional with expertise and need flowing in all directions, and project team members in all locales learned and contributed substantially in ways that carried into their other responsibilities. DISCUSSION/SIGNIFICANCE OF IMPACT: The overall partnership has created opportunity for South-South collaboration, for adaptation of projects among locales, and has helped boost reputational value for all partners involved. Implications for other CTSA awardees include: global collaboration can serve core research and technical needs for the CTSA itself and its local partners, CTSA status can be leveraged to access resources to support local research, and collaboration in other federally-funded research networks helps expand the insight, scope, and potential for new research.

OBJECTIVES/GOALS: Clinical trials of SGLT2 inhibitors in patients with heart failure (HF) have confirmed a reduction in hospitalization and death. Adoption of novel therapeutics has been slower in Black and female patients. We investigated utilization of SGLT2 inhibitor in patients with HF and type 2 diabetes and if there were utilization differences by race or gender. METHODS/STUDY POPULATION: We created a retrospective cohort of outpatients with HF at Emory Healthcare from 2015 to 2020. Additional inclusion criteria included presence of heart failure and a diagnosis of T2D. SGLT2 inhibitor use was identified by a presence of SGLT2 inhibitor prescription at the time of the clinic visit. We estimated differences in prescription of SGLT2 inhibitors by race and gender using Chi-square analysis. RESULTS/ANTICIPATED RESULTS: The cohort included 5829 patients, age 69.47 years ± 13.44, 47.67 % female, 54.62% Black. Overall prescription of SGLT2 inhibitors was low but increased over time (1.4% in 2015 to 5.6% in 2020; p<0.0001). On average, SGLT2 inhibitor use increased annually by 44.77%. From 2015 to 2020, fewer female than male patients were on an SGLT2 inhibitor (1.94% vs. 2.73%, p=0.0033). A similar percentage of Black and non-Black patients were on an SGLT2 inhibitor (2.13% vs. 2.64%, p=0.0591). DISCUSSION/SIGNIFICANCE: Prescription rates of SGLT2 inhibitors remain low in patients with T2D and HF, especially for female patients, despite evidence of their benefit on hospitalizations and mortality. Implementing use of SGLT2 inhibitors in this population represent an opportunity to improve cardiovascular outcomes.

OBJECTIVES/GOALS: Bronchiolitis is a major cause of PICU admission, yet identifying best practices is limited by the lack of existing databases containing the needed demographic and clinical variables. We used probabilistic linkage to join the Virtual Pediatric System (VPS) and Pediatric Health Information Systems (PHIS) databases to overcome this data barrier. METHODS/STUDY POPULATION: We performed a single site study joining VPS and PHIS data. These national databases contain clinical (VPS) and billing and resource use (PHIS) data. Limits on the use of patient identifiers (PI) for multi-center research, makes direct linkage techniques impossible. To demonstrate that probabilistic linkage can accurately link VPS and PHIS records, we obtained our single site VPS and PHIS records and linked them using probabilistic linkage without PI and compared this to a gold standard linkage created with PI. We also compared demographic features of linked and unlinked records to assess the ability of probabilistic linkage to create a representative sample. RESULTS/ANTICIPATED RESULTS: We obtained 920 VPS records of patients with bronchiolitis and linked 91% (839/920) to a PHIS record with 4 (0.5%) false-positive matches. Characteristics of linked and unlinked records are compared in Table 1. Comparison of probabilistically linked and unlinked records showed no difference in median age in years (0.7 [Interquartile range (IQR) 0.3-1.5] v 0.7 [IQR 0.2-1.5], p = 0.76), median number of complex chronic conditions (0 [IQR 0-1] v 0 [IQR 0-1], p = 0.16), median Pediatric Index of Mortality 3 severity of illness scores (-4.6 [IQR -4.7 – 4.4] v -4.6 [IQR -4.7 – 4.4], p = 0.44), median days of PICU stay (4 [IQR 3-6] v 4 [IQR 2-6], p = 0.36), proportion female ( 44% v 46%, p = 0.82), or proportion of patients intubated (28% v 24%, p = 0.41). DISCUSSION/SIGNIFICANCE: Probabilistic linkage creates an accurate combined VPS-PHIS database. Extending our methodology to join data from all 38 hospitals contributing to VPS and PHIS will allow creation of a large database containing the demographic, treatment, and outcome data needed to enable Comparative Effectiveness Research of bronchiolitis care.