OBJECTIVES/GOALS: High-grade gliomas (HGG) are among the rarest, most aggressive tumors in neurosurgical practice. We aimed to identify the clinical predictors for 30-day readmission and reoperation following HGGs surgery using the NSQIP database and seek to create web-based applications predicting each outcome. METHODS/STUDY POPULATION: We conducted a retrospective, multicenter cohort analysis of patients who underwent resection of supratentorial HGG between January 1, 2016, and December 31, 2020, using the NSQIP database. Demographics and comorbidities were extracted. The primary outcomes were 30-day unplanned readmission and reoperation. A stratified 80:20 split of the available data was carried out. Supervised machine learning algorithms were trained to predict 30-day outcomes. RESULTS/ANTICIPATED RESULTS: A total of 9,418 patients were included in our cohort. The rate of unplanned readmission within 30 days of surgery was 14.9%.Weight, chronic steroid use, pre-operative BUN, and WBC count were associated with a higher risk of readmission. The rate of early unplanned reoperation was 5.47%. Increased weight, higher operative time, and a longer period between hospital admission and the operation were linked to increased risk of early reoperation. Our Random Forest algorithm showed the highest predictive performance for early readmission (AUC = 0.967), while the XG Boost algorithm showed the highest predictive performance for early reoperation (AUC = 0.985).Web-based tools for both outcomes were deployed: https://glioma-readmission.herokuapp.com/, https://glioma-reoperation.herokuapp.com/. DISCUSSION/SIGNIFICANCE: A high fraction of documented early unplanned readmission and reoperation were considered preventable and related to surgery. Machine learning allows better prediction of resected HGG’s prognosis based on findings from baseline methods leading to more personalized patient care.

The Clinical and Translational Science Award (CTSA) Program recognizes that advancing diversity, equity, inclusion, and accessibility (DEIA) requires moving beyond statements of commitment to transformative actions. In 2021, the CTSA Program created a Task Force (TF) to initiate work in support of structural and transformational initiatives that advance DEIA for the consortium and its individual hubs. We describe the process of forming the expertise-driven (DEIA) TF and our activities to date. We 1) developed and adopted the DEIA Learning Systems Framework to guide our approach; 2) defined a set of recommendations across four focus areas (Institutional; Programmatic; Community-Centered; and Social, Cultural, Environmental); and 3) designed and disseminated a survey to capture the CTSA Program’s baseline demographic, community, infrastructural, and leadership diversity. The CTSA Consortium also elevated the TF to a standing Committee to extend our understanding, development, and implementation of DEIA approaches to translational and clinical science. These initial steps provide a foundation for collectively fostering environment that support DEIA across the research continuum.

Translational science is, by definition, groundbreaking; however, without an emphasis on quality and efficiency, some innovations in healthcare may translate into unnecessary risk, suboptimal solutions, and potentially loss of well-being and even lives. The COVID-19 pandemic and the Clinical and Translational Sciences Award Consortium’s response created an opportunity for quality and efficiency to be better defined, expediently and thoughtfully addressed, and further studied as central foundations in the translational science mission. This paper presents findings of an environmental scan of adaptive capacity and preparedness to illuminate the assets, institutional environment, knowledge, and forward-looking decision-making needed to optimize and sustain research quality and efficiency.

OBJECTIVES/GOALS: A disease-agnostic translational science framework for data mining is proposed for use across disciplines to: Answer clinical questions, justify future clinical research recruitment, and explore under-represented populations. As a case example, male puberty demonstrates utility of the framework. METHODS/STUDY POPULATION: As a case example using the generalizable framework, the following interdisciplinary question was asked: Does early pubertal timing increase the risk of developing type II diabetes (T2d) in boys? A digital phenotype of males < 18 years old was created in the TriNetX Diamond Network utilizing Boolean operator data queries. TriNetX contains patient electronic health record information (ICD-10 diagnoses, anthropometric measures). A case control analysis leveraging patient counts from various digital phenotypes allowed for outcome (T2d) comparison of boys diagnosed with precocious puberty (E30.1, ICD code for early pubertal timing) to those without, while controlling for body mass index (BMI). RESULTS/ANTICIPATED RESULTS: Subjects (N=12,996,132) displayed the following digital phenotype: Male, < 18 years old, without ever having a BMI documented >85th percentile. Boys diagnosed with precocious puberty (E30.1) were 6.89 times more likely to develop T2d when aged 14-18 years old than those without (OR 6.89, 95%CI: 5.17-9.19, p. DISCUSSION/SIGNIFICANCE: Boys are under-represented in the early pubertal timing literature, justifying future human subjects research on male puberty. This case example demonstrates a broader disease-agnostic framework which can be adapted across disciplines. Opportunities may include public health digital phenotyping.

OBJECTIVES/GOALS: To determine the signs, symptoms, and diagnoses that are significantly upregulated in cases of long COVID while identifying risk factors and demographics that increase one’s likelihood of developing long COVID. METHODS/STUDY POPULATION: This is a retrospective, big data science study. Data from Veterans Affairs (VA) medical centers across the United States between the start of 2020 and the end of 2022 were utilized. Our cohort consists of 316,782 individuals with positive COVID-19 tests recorded in the VA EHR with a history of ICD10-CM diagnosis codes in the record for case-control comparison. We looked at all new diagnoses that were not present in the six months before COVID diagnosis but were present in the time period from one month after COVID through seven months after. We determined which were significantly enriched and calculated odds ratios for each, organized by long COVID subtypes by medical specialty / affected organ system. Demographic analyses were also performed for long COVID patients and patients without any new long COVID ICD10-CM codes. RESULTS/ANTICIPATED RESULTS: This profile shows disorders that are highly upregulated in the post-COVID population and provides strong evidence for a broad definition of long COVID. By breaking this into subtypes by medical specialty, we define cardiac long COVID, neurological long COVID, pulmonary long COVID, and eight others. The long COVID cohort was older with more comorbidities than their non-long COVID counterparts. We also noted any differences regarding sex, race, ethnicity, severity of acute COVID-19 symptoms, vaccination status, as well as some analysis regarding medications taken. DISCUSSION/SIGNIFICANCE: This profile can be utilized to decisively define long COVID as a clinical diagnosis and will lead to consistence in future research. Elucidating an actionable model for long COVID will help clinicians identify those in their care that may be experiencing long COVID, allowing them to be admitted into more intensive monitoring and treatment programs.

OBJECTIVES/GOALS: Guidelines suggest people with HIV (PWH) receive routine HIV viral load (VL) testing at least yearly and upon diagnosis with multidrug-resistant tuberculosis (MDR-TB). Many PWH and MDR-TB in South Africa seem to be missing VL results. This study’s goal was to find results which may be available from the National Health Laboratory Service (NHLS). METHODS/STUDY POPULATION: We abstracted HIV laboratory results, specifically baseline VL and CD4 count and VL at MDR-TB cure, from PWH enrolled in a cluster-randomized clinical trial of nurse case management for PWH and MDR-TB in South Africa who were cured of MDR-TB. For any participant missing one or more of these results, we thoroughly searched the electronic NHLS database using multiple separate searches varying terms including patient name, surname, date of birth, medical record number where available, and South African identification number. Returned results were compared to results abstracted from the parent study and any additional results were entered into the parent study data. RESULTS/ANTICIPATED RESULTS: Of 929 PWH cured of MDR-TB, 879 (94.6%) were missing at least one expected VL or CD4 result in the parent study database. Though our search strategy was successful in identifying participants and returning CD4 and VL results, we rarely found additional results that were not already in the parent study database. Following the search and entry of the few additional results retrieved, 116 (12.4%) participants were missing a baseline CD4, 309 (33.3%) missing baseline VL, and 385 (41.4%) missing VL at MDR-TB cure, representing 572 individuals or 61.6% of participants with at least one unavailable result. This high level of unavailability of key laboratory results used to guide MDR-TB and HIV treatment suggests that these tests were either not ordered, not collected, or not completed due to electronic gatekeeping at NHLS. DISCUSSION/SIGNIFICANCE: Unknown CD4 count or VL leaves PWH open to including MDR-TB treatment failure and death. Our search strategy found additional results but was time-consuming and cumbersome. Limitations included lack of information on why laboratory results were missing, which limits our ability to make recommendations for better collection and reporting.

OBJECTIVES/GOALS: Regionalized sepsis care could improve sepsis outcomes. There are no measures of sepsis capability to guide the identification of hospitals that can best serve sepsis patients. We derived Capability-Based (CB) scores from specific hospital characteristics and evaluated their performance as system predictors of mortality among adults with sepsis. METHODS/STUDY POPULATION: We used the 2018 State Inpatient Databases to identify 90051 adult sepsis encounters at 157 non-federal NY hospitals (derivation cohort), and 130,249 sepsis encounters at 220 hospitals in FL and MA (validation cohort). We used Principal Component Analysis to analyze to reduce 14 hospital-level resource use characteristics to 3 interpretable, linear data combinations (principal components (PC). We calculated CB scores for each hospital as a sum of standardized values for each component multiplied by the respective PC loading. We evaluated the correlation of sepsis volume and each CB score with hospital mortality and with outward sepsis transfer proportions. We fitted linear, nested, predictive models to compare the system predictive abilities of CB scores and sepsis volume in relation to hospital mortality. RESULTS/ANTICIPATED RESULTS: In the derivation cohort, 83963 (93.2%) patients were non-transferred, of which 20230 (24.1%) died. The mean (range) score was 0 (-3 - +5) with higher scores denoting more capable hospitals. Higher scores were weakly and inversely correlated (spearman’s [r]: - 0.28) with outward sepsis transfer proportions. Higher scores had weak but better positive correlation with hospital mortality (r: 0.33), than sepsis volume (r: 0.24). CB scores explained more variation in sepsis mortality (R2 = 0.24, P DISCUSSION/SIGNIFICANCE: Capability-based hospital scores account for three times more variation in sepsis mortality than sepsis volume and outperform sepsis volume as a system predictor of mortality. With further refinement and validation, these scores may find utility for improving system-based approaches to sepsis care.

We conducted a survey study of clinical research coordinators (CRCs) at the member institutions of the Pediatric Emergency Care Applied Research Network, to determine the demographic and linguistic characteristics of CRCs around the network, and any perceived impact of those characteristics on their duties. A total of 53/74 CRCs completed the survey. Most respondents identified as “female,” “white,” and “not Hispanic/Latino.” Most respondents felt that their race/ethnicity and their ability to speak a language other than English would positively impact recruitment. Four female respondents felt that their gender hindered their recruitment efforts and their sense of belonging within the research team.

OBJECTIVES/GOALS: Can we detect Parkinson’s-disease-related motor impairments using computer vision and machine learning? METHODS/STUDY POPULATION: A sample of 29 people with Parkinson’s disease (PD) and 29 non-Parkinson’s disease (non-PD) controls were recruited from the University of Iowa Movement Disorders Clinic. Videos of 3 motor assessment tasks performed using the hands were recorded and hand location information was abstracted using the computer vision program MediaPipe. Measures from the raw data series and FFT were used as features to train a model using boosted trees to classify each video as PD or non-PD. Model performance was evaluated using leave-one-out cross-validation. Additionally, we used recursive feature elimination to reduce model complexity. RESULTS/ANTICIPATED RESULTS: A model using two features identified by recursive feature elimination yielded a model with an overall accuracy of 81% in cross-validation. In our sample, the model had 86.2% sensitivity, 75.9% specificity, and an AUC of 0.839. Additional improvement may be possible with more data processing, especially in the time-domain. DISCUSSION/SIGNIFICANCE: We built a classifier that was able to reliably and accurately discriminate between videos of motor assessments in people with Parkinson’s and people without. This may provide a low cost screening tool in rural areas or primary care clinics with limited access to neurologist expertise.

OBJECTIVES/GOALS: Our objective is to address the gaps in our epidemiologic understanding of Echinococcosis, a neglected and emergent zoonotic parasite in the US. Comparing regional differences in human cases with known Echinococcus genotypes in canine reservoirs will reveal landscape-level transmission risks. METHODS/STUDY POPULATION: Retrospective analysis of de-identified diagnosis codes for human echinococcosis in the US from 2002-2022 in a federal multi-healthcare network database (TriNetX). Analyses included Kaplan-Meier survival and specific parasite species cohort comparisons with descriptive summaries of demography and co-morbidities, and odds ratios for interventions (surgery, antiparasitics, cyst aspiration) and complications (anaphylaxis, sepsis, etc.) Mitochondrial genomes of Echinococcus spp. from next-generation sequencing ova-positive archival animal scat (National Park Service), along with sequences from published sources in the US, will be used to compare regional genotypic and reservoir host differences. RESULTS/ANTICIPATED RESULTS: Over 36,000 US patients were diagnosed with Echinococcosis in the past twenty years. Most cases had an unspecified parasite species, primarily affecting pediatrics (average age 16y +/- 10y) in the South/Southeast US, with very few interventions or medical complications reported. Patients with specific parasite species diagnoses (E. granulosus or E. multilocularis, N=500) had higher rates of mortality (11.7% at 10y), surgical (8.8%) and medical (18.2%) interventions, and complications (2%-17.2%), with demographic differences noted. Sequencing data and analysis pending for 47 Echinococcus positive wolf samples, with 78 additional sequences available for two types of Echinococcus spp. in wildlife, and lacking data for domestic dog-adapted strains in the US. DISCUSSION/SIGNIFICANCE: This study revealed a higher-than-expected burden of Echinococcosis in the US, confirming it is an under-recognized neglected and emergent disease. Future studies will address gaps regarding the origin of unspecified infections, with targeted surveillance of domestic dogs in high-risk areas.

OBJECTIVES/GOALS: Our goal was to assess the ability of a 3D-Printed dual cover-core design alveolar ridge bone graft, to withstand the average maximum masticatory force of a healthy person. To this end, we characterized the materials, ran a finite element analysis (FEA) model, and validated it using a resin 3D-printed version tested under compression with strain gauges. METHODS/STUDY POPULATION: A tricalcium-phosphate/hydroxyapatite paste and mixed methacrylated alginate-gelatin were used for the core, and polycaprolactone for the cover. These were characterized using ASTM standards D695 and D638 for compression, tensile, and rheological testing. Then we converted cone CT-scan images of a mandibular alveolar ridge defect to an .stl file, and designed the cover and core in Meshmixer. The model was then imported into ANSYS 11.0, and a downward compression force of 500 N, the maximum masticatory force of a healthy adult, was applied on the graft and mandible’s top ridge. The different models included solid and porous covers and cores, as well as comparing screws on one or both sides of the cover, then validated by compressing a resin 3D-printed versions. RESULTS/ANTICIPATED RESULTS: The FEA model provided maximum displacements, Von Mises stress (VMS), and stress/strain values for each model. The highest maximum displacement was found on the solid covers with a combination of both buccal and lingual screws, at 0.162 mm. The lowest maximum displacement was found in the porous cover at 0.085 mm. All VMS values were below the tensile yield strength, meaning that the materials would not yield. The highest maximum stress was found on the porous cover at 13.52 MPa, the lowest was 1.06 MPa on the cover with no screws. The highest strain was found on the porous model at 0.010, which was 5.6x higher than the solid cover. The porous cover also showed less stress shielding, thus allowing a beneficial mechanical stimulation of the bone, and the lowest maximum displacement, possibly due to flexion through the pores. DISCUSSION/SIGNIFICANCE: Preliminary FEA models demonstrated that for the considered materials, a cover-core design of the mandibular implant would sustain the desired 500 N of force without yielding. The porous cover provides the most benefits, causing the least stress shielding and allowing diffusion of biological factors to support the osteoinductive role of the core.

This abstract is based on unpublished data. OBJECTIVES/GOALS: The estimates of unbiased first-degree relatives (FDRs) risk of cancers would enhance genetic counseling of at-risk FDRs in families where the pancreatic cancer (PC) proband carrying a germline variant. This study aims at quantifying gene-specific risks of six cancers among FDRs of PC patients with germline variants in cancer-associated genes. METHODS/STUDY POPULATION: In the prospective, clinic-based Mayo Clinic Biospecimen Resource for Pancreas Research registry, 4,562 PC patients had previously undergone germline genetic testing for pancreatic cancer-associated genes through either research studies or clinical testing. Of these, 234 PC probands were found to carry germline pathogenic/likely pathogenic variants (PLPV) among 9 genes of interest and had provided detailed demographic and cancer data on their FDRs by questionnaire. We focused on six cancer types (ovary, breast, uterus, pancreas, colon, and malignant melanoma) in FDRs as reported by the probands. Standardized incidence ratios were calculated to estimate risk of six cancers among FDRs of PC patients carrying PLPV by gene. RESULTS/ANTICIPATED RESULTS: 1,670 FDRs (mean age 58.1+17.8SD; 48.9% female) were included in the study. We found significantly increased risk of ovarian cancer in female FDRs of PC probands who carry PLPV in BRCA1 (SIR 9.49, 95%CI:3.06-22.14) or BRCA2 (3.72, 95%CI:1.36-8.11), and breast cancer risks were higher with BRCA2 (2.62, 95%CI:1.89-3.54). Uterine cancer risk was increased in FDRs of PC probands who carry PLPV for Lynch Syndrome mismatch repair (MMR) (6.53, 95%CI:2.81-12.86). PC risk was also increased (ATM 4.53, 95% CI:2.69-7.16; BRCA2 3.45, 95%CI:1.72-6.17; CDKN2A 7.38, 95%CI:3.18-14.54; PALB2 5.39, 95%CI:1.45-13.79). Increased colon cancer risk was observed in FDRs of probands who carried MMR PLPV (5.83, 95%CI:3.70-8.75), while melanoma risk was elevated for FDRs of probands with CDKN2A PLPV (7.47, 95%CI:3.97-12.77). DISCUSSION/SIGNIFICANCE: PLPV in nine syndrome-associated genes in PC probands are associated with increased risk of six cancers in FDRs. The findings underscore the importance of risk estimation of various other cancers in PC families for screening, early detection, intervention, and cascade genetic testing.

OBJECTIVES/GOALS: Breast cancer has an increased requirement for lipids. The sigma-2 receptor plays a critical role in the effective uptake of lipoproteins by forming a complex with the LDL Receptor. We investigate the role of the sigma02 receptor in modulating lipid uptake pathways in breast cancers, and how this can be leveraged as a viable therapeutic strategy. METHODS/STUDY POPULATION: CRISPR/Cas9 will be used to ablate TMEM97 in the MDAMB231 and MCF7 cell lines. This study seeks to identify pathways that are dysregulated upon TMEM97 knockout (KO) by characterizing RNASeq data to identify differentially expressed genes and perform pathway analysis. RESULTS/ANTICIPATED RESULTS: Knockout of TMEM97 in breast cancer cells is is expected to decrease lipid uptake. Treatment with statins in these knockout cells is expected to result in decreased cell viability and result in a quiescent cell population. DISCUSSION/SIGNIFICANCE: This is an important mechanistic study to understand the importance of lipid homeostasis in cancer cell proliferation and how it can be targeted to improve therapeutic anti-tumor strategies. Understanding the pathways that TMEM97 modulates is vital for therapeutic strategies to curb the proliferation of breast cancer cells.