OBJECTIVES/GOALS: To test the effect of a trusted Community Health Worker (CHW) support model to increase accessibility, feasibility and completion of COVID-19 home-testing in Native American and Latino communities. METHODS/STUDY POPULATION: We conducted a multi-site pragmatic randomized controlled trial among adult Native Americans and Latinos from the Flathead reservation in Montana and Yakima Valley in Washington. Participants were block randomized by site location and age to either an active or passive study arm. Participants in the active arm received assistance with online COVID-19 test kit registration and virtual swabbing support from CHWs, while the passive study arm received the standard-of-care support from the COVID-19 home testing kit vendor. Simple and multivariate logistic regression modeled the association between home-testing distribution mechanism and test completion. Multivariate models included community and sex as covariates. Descriptive feedback was collected in a post-test survey. RESULTS/ANTICIPATED RESULTS: Overall, 63% of the 268 enrolled participants completed COVID-19 tests, and 50% completed tests yielding a valid result. Active arm participants had significantly higher odds of test completion (OR 1.66, 95% CI: [1.01, 2.75], p-value=0.04). Differences were most pronounced among adults ≥60 years, with 84% completing testing kits in the active arm, compared to 58% in the passive arm (p=0.07). Ease of use and not having to leave home were top positive aspects of the home-based test while transporting and mailing samples to lab and long/overwhelming instructions were cited as negative aspects. Most test completers (93%) were satisfied with their experience and 95% found CHW assistance useful. Sample expiration and insufficient identifiers were top causes of non-valid test results. DISCUSSION/SIGNIFICANCE: While test completion rates were low in both study arms, the CHW support led to a higher COVID-19 test completion rate, particularly among older adults. Still, CHW support alone does not fully eliminate testing barriers. Socio-economic differences must be accounted for in future product development for home-based testing to improve health equity.

OBJECTIVES/SPECIFIC AIMS: Compare effectiveness of a patient case-based, interactive teaching approach that included optional student genotyping with traditional didactic teaching strategies for increasing students’ knowledge and ability to effectively use pharmacogenomic data in clinical decision making. METHODS/STUDY POPULATION: The UF College of Pharmacy offers a required Personalized Medicine (PM) course for pharmacy students as well as an elective course, Clinical Applications of Personalized Medicine (CAPM). Students dual enrolled in the PM and elective CAPM courses comprised the intervention (INT) group, with interactive patient case-based teaching and the option to undergo personal genotyping, whereas students enrolled in PM alone comprised the control (CTR) group, which primarily used a traditional didactic teaching format and did not include personal genotyping. Both groups completed a pre- and post-course patient case-based test (15 questions/1 point each) to evaluate their knowledge and abilities to apply genotype and other patient-specific data to drug therapy recommendations. Pre- and post-course test scores for knowledge were compared between the INT and CTR groups using the Student t-test. RESULTS/ANTICIPATED RESULTS: In total, 52 students completed surveys (INT group, n=21; CTR group, n=31). Race was similar between groups, but there were fewer females in the INT compared with CTR group (8 vs. 22, p=0.02). Pre-course knowledge scores did not differ between INT and CTR groups (6.8±2.2 vs. 6.3±1.6 respectively, p=0.34), however, post-course scores were significantly higher in the INT Versus CTR group (10.0±2.3 vs. 7.5±1.7, p<0.0001). DISCUSSION/SIGNIFICANCE OF IMPACT: There have been significant advancements in the clinical applications of pharmacogenomic and genomic data, however, barriers to routine clinical adoption of genomic medicine persist. Developing education and training methods that equip practitioners to effectively translate genomic data into evidence-based clinical recommendations has been identified as a key strategy to overcome such barriers. Our data suggest that a personalized medicine course that employs patient-centered, case-based teaching strategies and includes optional personal genotyping for students compared with traditional didactic instruction improves students’ knowledge and abilities to apply pharmacogenomic data in practice-based scenarios. These results can inform future strategies for educating healthcare professionals on the clinical use of pharmacogenomic and genomic data.

OBJECTIVES/GOALS: Autism spectrum disorder (ASD) is a developmental disorder with a high financial and personal burden. Individuals with ASD experience significant comorbid medical conditions. We identified conditions that appear prior to ASD diagnosis in order to potentially improve early screening practices. METHODS/STUDY POPULATION: We used electronic health record data from an anonymized database at Vanderbilt University Medical Center for individuals with ASD and matched controls to analyze comorbid conditions prior to an ASD diagnosis. Data were censored to include only individuals who first appeared in the databank prior to two years of age (ntotal = 1551, ncontrols = 976, nASD = 575). Comorbidities (~1800 conditions) were compared between the ASD and matched control group using a novel tool (pyPheWAS) to examine presence, count, and duration of comorbidities that occurred between 0-2 years old and before ASD diagnosis. RESULTS/ANTICIPATED RESULTS: Convulsions (p = 0.000404, ß = 0.807), constipation (p = 0.000789, ß = 0.894), and strabismus (p = 0.00243, ß = 1.155) were the most significant comorbid conditions prior to age 2 in individuals who would later be diagnosed with ASD. The group with ASD also had more visits associated with convulsions (p = 0.00511, ß = 0.195), diseases of the esophagus (p = 0.0117, ß = 1.675), and allergic reactions to food (p = 0.0119, ß = 0.540) prior to their diagnosis. The ASD group was also seen for a longer duration regarding convulsions (p = 0.000273, ß = 0.695), constipation (p = 0.00157, ß = 0.712), and malaise and fatigue (p = 0.00188, ß = 0.903) before ASD diagnosis. DISCUSSION/SIGNIFICANCE OF IMPACT: Precise comorbid condition profiles in early childhood may help uncover biomarkers leading to better prediction of a future ASD diagnosis. Medical conditions that precede the onset of measurable behavioral symptoms may enhance early screening, treatment, and intervention in ASD.

OBJECTIVES/SPECIFIC AIMS: The objective of this project is to determine whether HRV, collected peri-operatively, is predictive of cognitive decline among older adults who undergo elective surgery/anesthesia. METHODS/STUDY POPULATION: This project is a part of the ongoing INTUIT/PRIME study, which is collecting pre- and post-operative cognitive testing, fMRI imaging, CSF samples, and EEG recordings from 200 older adults (age ≥ 60) undergoing elective non-cardiac/non-neurologic surgery scheduled to last > 2 hours at Duke University Medical Center and Duke Regional Hospital. This project utilizes data from the first 60 INTUIT participants who contributed continuous heart rate data before and during surgery. Participants undergo cognitive testing prior to surgery (baseline) and at 6 weeks after surgery. Our primary dependent variable is the change in the composite score from baseline to 6-weeks. Delirium is assessed in the hospital with the twice daily 3D-CAM tool, so we will report the proportion of individuals with 6-week cognitive decline who exhibited delirium in the days following surgery. Participants’ echocardiogram (ECG) recordings are extracted pre- and intraoperatively from B650/B850 patient monitors with VSCapture software. HRV is defined as the variability between successive R-spikes or inter-beat-intervals on ECG. RESULTS/ANTICIPATED RESULTS: We anticipate that lower intraoperative HRV is associated with worse cognitive decline at 6 weeks after surgery. As secondary objectives, we will determine whether pre-operative HRV or change in HRV (from pre-operative to intra-operative measures) are predictive of cognitive decline after surgery. We expect that in-hospital delirium will be detected in a higher proportion of those with 6-week cognitive decline, compared to those with stable or improved cognition at 6 weeks. DISCUSSION/SIGNIFICANCE OF IMPACT: HRV may address the present need for pre- and intra-operative cognitive risk stratification in the elderly. Physiological indices like HRV have the potential to dramatically change our understanding of CI in older adults undergoing surgery, as they offer an accessible, cost-effective, and non-invasive means whereby clinicians, particularly those unfamiliar with the nuances of geriatric and CI/dementia-related care, can monitor patients and refer those at high-risk of CI after surgery for early intervention.

OBJECTIVES/GOALS: A diverse workforce is an aspiration of CTSIs and embedded in goals to build D&I workforce capacity. However, little research describes the diversity of the current workforce. We assessed current assets, opportunities, and diversity of D&I efforts at Frontiers and characterized investigators and those supported by services offered. METHODS/STUDY POPULATION: In January 2021, Frontiers convened a working group to identify existing D&I assets and needs in the CTSI multi-state catchment area. The committee catalogued existing training and consultation resources and services, which the CTSI supported with infrastructure to support, track, and evaluate ongoing efforts. We obtained data from the evaluation platform and conducted descriptive analyses of the investigators and service uptake among two programs offered, contrasting the workforce with national data obtained from the American Academy of Medical Colleges (2022) and the National Institutes of Health (2018). RESULTS/ANTICIPATED RESULTS: Ninety individuals at 9 institutions across Kansas and Missouri identified as implementation researchers. Since 2022, 28 D&I consultations were provided, 92% for grant applications. Five early-stage investigators were identified for career development in an NIH-supported Health Equity and Implementation Center (ESI). The network mirrors the larger workforce regarding underrepresented racial/ethnic minorities (18%) and new investigators (60%). More women (76%) are represented in the D&I network and among ESIs (80%) than the academic workforce (44%), but significantly fewer women used consultation services (p<0.001). Lower proportions of underrepresented minority investigators (p<0.001) and investigators from disadvantaged statuses (p=0.027) accessed consultations services. DISCUSSION/SIGNIFICANCE: Investigators underrepresented in science on multiple dimensions were less likely to use consulting services, Outreach for consultation services may be necessary, if needs are not being met in other programs. Further exploration of overall D&I workforce trends is needed to ensure goals for the field and the CTSA network are achieved.

OBJECTIVES/SPECIFIC AIMS: More partial nephrectomies are performed every year as a surgical treatment for kidney cancer. However, this procedure remains technically challenging. Surgeons require a substantial number of cases before their performance plateaus. No established practice mode exists; thus, there is a need for training models to simulate real tumor excisions and kidney suturing. In this study, we seek to validate these silicone models using multiple simulations with urologists of different training levels. METHODS/STUDY POPULATION: We created silicone renal tumor models using 3D printed molds of a patient’s kidney with a mass. Medical students, urology residents, fellows, and attending surgeons are recruited to perform simulated partial nephrectomies on these models. Four trials are performed with a da Vinci surgical robot on 2 different days. We are evaluating surgeon performance and improvement using validated measures as well as operation-specific metrics. Operation-specific metrics include renal artery clamp time and surgical margins. Validated measures of self-assessed operative demand (NASA TLX) and reviewer-assessed surgical performance (GEARS) are also recorded across trials. RESULTS/ANTICIPATED RESULTS: The preliminary results of 2 medical students, 10 urology residents, 3 endourology fellows, and 2 attending urologists are reported here. Model face validity was evaluated on a 0–100 sliding scale anchored at unrealistic and realistic. Mean results thus far are 77.7 for overall feel, 82.7 for needle driving, 75.6 for cutting, and 73.2 for visual representation. Between trials 1 and 4 there was a mean reduction of 3.26 minutes in renal artery clamp time, and a 75% reduction in positive margins. There was a reduced incidence of positive surgical margins with advanced training stage. Fellows, residents, and medical students had positive tumor margins in 25%, 50%, and 75% of their trials, respectively. We expect to recruit 15 additional subjects for this study. Upon completion of data acquisition, more robust statistical comparisons and measures will be reported. DISCUSSION/SIGNIFICANCE OF IMPACT: Face validity measures indicate the model adequately represents reality. Preliminary data suggest improved surgical performance over the course of the training and better performance in urologists of higher training levels. This model may have potential for broader application and integration into minimally invasive surgery training programs.

Objectives/Goals: Create a supportive Clinical Research Coordinator (CRC) and Clinical Research Nurse consortium at UF. Facilitate mentorship groups to enhance knowledge on key topics. Build strong professional relationships among members. Empower members through collaboration. Develop future leaders and mentor in clinical research. Methods/Study Population: The CRC Group Mentorship Program at UF’s Gainesville and Jacksonville campuses addresses mentorship needs identified in a recent needs assessment, reflecting strong interest among CRC/CRNs. Small groups are formed using the Group Mentorship and Co-Mentoring Circles models, meeting bimonthly for six months on shared research interests. Co-lead mentors guide learning, peer support, communication skills, and goal setting while tracking progress. Mentees engage in peer learning, skill development, and networking. A dedicated Microsoft Teams platform provides resources to enhance confidence in Joint Task Force Clinical Trial Competencies and fosters collaboration through Q&A sessions, activities, assessments, and meetings, improving real-time and asynchronous interactions. Results/Anticipated Results: To measure mentor program impact, pre- and post-program surveys assess changes in knowledge, skills, and confidence among mentors and mentees, providing insights into effectiveness and areas for improvement. Monthly, the program features two meetings focusing on Joint Task Force competencies: a workshop for all groups on essential mentorship and CRC/CRN competencies, followed by evaluations, quizzes, and continuing education credits. The second meeting is group-specific, led by co-lead mentors, requiring submissions that demonstrate the application of learned knowledge and skills. This structure ensures continuous relevance and quality enhancement in future programs. Discussion/Significance of Impact: The program meets CRCs and CRNs’ critical needs through structured mentorship, fostering a supportive environment. It promotes continuous learning and professional development, enhancing job satisfaction and ensuring the sustainability of valuable research professionals.

OBJECTIVES/GOALS: Our aim is to understand the role bilirubin oxidation products play in the development of cerebral vasospasm in patients with subarachnoid hemorrhage. We aim to evaluate the time course of bilirubin, HO-1, and SOD1 in relation to the subsequent development of vasospasm in to establish predictors of vasospasm development. METHODS/STUDY POPULATION: Prospective cohort observational study involving collection of CSF samples of pts admitted to KU NeuroICU with SAH and placement of EVD. CSF will be extracted from the EVD of patients on the day of placement of the EVD, and then each subsequent day for a total of 10 days. Bilirubin concentration will be determined by means of spectrophotometry. HO-1 will be measured using a commercially available ELISA kit. Cu/Zn-Superoxide Dismutase will be measured using a commercially available ELISA kit. A review of patients chart will then be performed following discharge from hospital to determine if a diagnosis of vasospasm was made, details of the vasospasm (i.e. symptoms, severity), as well as to obtain demographic data and events occurring during patients admission that could confound statistical analysis. RESULTS/ANTICIPATED RESULTS: First: we will investigate the feasibility of collecting serial CSF samples and processing them for target analyte quantification. We predict that the protocol will yield quality data that will result in insight on the pathophysiology of cerebral vasospasm. Second: we will characterize the changes in target CSF bilirubin breakdown analytes over 10 days. From this we hypothesize that as bilirubin oxidation increases, the propensity for cerebral vasospasm will also increase. DISCUSSION/SIGNIFICANCE: If there is a clear correlation between formation of bilirubin and increase in HO-1, and SOD1, with the clinical signs of vasospasm, this could be used as a biomarker for not only identifying patients at risk for developing these complications but also a means to follow the effectiveness of potential therapies.

OBJECTIVES/GOALS: Fibroids during pregnancy are associated with worse obstetric outcomes. However, theres no recommendation to guide counseling. We aimed to assess the cost-effectiveness of (1) treating prevalent fibroids before pregnancy and (2) screening and treatment of fibroids against the outcomes of postpartum hemorrhage (PPH) and fetal malpresentation. METHODS/STUDY POPULATION: A decision tree model was used to compare (1) preconception myomectomy for prevalent fibroids, without treatment and (2) preconception myomectomy for prevalent cases and universal ultrasound screening with subsequent myomectomy for incident cases. Probabilities and costs, calculated from the U.S. healthcare sectors perspective, were derived from the literature. Effectiveness was measured in incident PPH or malpresentation cases per 1,000 in the population. The incremental cost-effectiveness ratio (ICER) was measured in incremental cost per case averted. One-way and probabilistic sensitivity analyses were conducted to identify influential parameters and assess the impact of parameter uncertainty. RESULTS/ANTICIPATED RESULTS: Treating known fibroids prior to pregnancy averted 65.7 PPH cases at the cost of $8,773,094 and 91.08 malpresentations at the cost of $8,163,315 (ICERs, $133,532 vs $89,628 per case averted, respectively). Universal fibroid screening with treatment of incident and prevalent cases averted 7.34 PPH cases at the cost of $3,725,619 and 2.7 malpresentations at the cost of $3,477,033 (ICERs, US$507,450 vs US$1,335,771 per case averted, respectively). Sensitivity analyses showed cost-effectiveness improved with decreased cost of myomectomy and increased proportion of prevalent and incident cases. DISCUSSION/SIGNIFICANCE: Treatment alone costs $133,532 per PPH averted and $89,628 per malpresentation averted. Likewise, screening with treatment costs $507,450 per PPH averted and $1,335,771 per malpresentation averted. Additionally, ICERs may decrease when focusing on populations where fibroid incidence and prevalence is higher, for example, among Black women.

OBJECTIVES/GOALS: Limited specialty care within safety net health systems reduces availability of follow-up appointments for chronic conditions. We evaluated patient acceptability of a 6 month series of telemedicine group medical visits for chronic migraine at a county hospital-based clinic as a potential method to improve access to specialty care in this setting. METHODS/STUDY POPULATION: We developed and implemented a pilot program of monthly physician-led telemedicine group visits to provide routine follow-up care for adults with chronic migraine. Visits were conducted through the neurology clinic at LAC+USC medical center, a safety net hospital in Los Angeles and included an educational component, peer support, and the opportunity to address individual needs or refill medications. We assessed headache severity (HIT-6) and mood (PHQ-9) through telephone surveys before and 6 months after patients’ first telemedicine group visit and compared timepoints using paired t-tests. Patient acceptability of the group visits was elicited through focus groups and key themes identified using grounded field theory. RESULTS/ANTICIPATED RESULTS: Baseline data was available for 18/20 pilot participants. Patients were predominantly female (89%) with mean age of 46 (SD 8.6). Mean HIT-6 was 65/78 reflecting a very severe impact on daily life, and mean PHQ-9 was 8.7 reflecting mild depressive symptoms. There was no statistically significant change in either HIT-6 (mean difference 2.36, p=0.34) or PHQ-9 (mean difference 2.09, p=0.12) after group participation. Key themes from the focus groups included lack of prior exposure to other people with similar headache burden and logistical barriers to care, such as difficulty contacting a provider or extended clinic wait times. Primary patient-reported benefits included more frequent access to a provider and peer support. DISCUSSION/SIGNIFICANCE: Telemedicine group visits for chronic migraine are feasible in a safety net context and were well-received by patients. However, this pilot study did not show a benefit of telemedicine group visits for headache control or mood symptoms.

OBJECTIVES/GOALS: Immediate negative impact of the COVID pandemic on CTSA T trainees and K scholars was reported in 2020 to be lack of access to research facilities, clinics, human subjects, and team members, and a need for homeschooling. In this study we examined in more detail the perceived impact of the COVID pandemic on training and career development three years later. METHODS/STUDY POPULATION: CTSA T trainees and K scholars were surveyed in May-June 2023 to assess the impact of the COVID-19 pandemic on training and career development. Data were included from 309 T trainees and K scholars appointed in 2018-2023 at 50 institutions, with good representation from states that were heavily impacted by COVID. Respondents included 76 past and 64 current T trainees, and 56 past and 113 current K scholars. There were no significant differences in race, ethnicity, or gender between T and K respondents. Significantly more K scholars reported both being married or in a committed relationship, and having children. Survey items included the same questions asked in the 2020 survey, plus additional new questions. Results compare impact for T trainees and K scholars. RESULTS/ANTICIPATED RESULTS: K scholars were more negatively impacted for access to clinic/human subjects, home environment, child care, access to staff, increased clinical responsibilities, and other hospital service. T trainees and K scholars reported higher positive impact than in 2020, for having more time to think/write and develop new research ideas. About 2/3 of respondents reported returning to research full-time by April 2021, and the remaining by August 2021. Lasting changes in career progression or research direction were reported as both positive and negative (48%), negative (25%), or positive (10%). Most (2/3) respondents in faculty positions reported that a time extension was available for promotion and/or tenure. Additional in-depth analysis will be presented, based on qualitative analysis of open-ended questions. DISCUSSION/SIGNIFICANCE: Despite research shutdowns in response to the COVID-19 pandemic that lasted for about a year, CTSA T trainees and K scholars were remarkably resilient. They were able to continue some research activities and professional development activities, and developed strategies to maintain productivity and minimize impact on their training duration.

OBJECTIVES/SPECIFIC AIMS: Given the heightened risk for suicide seen in individuals with PTSD+MDD, this report explored the effect of repeated ketamine infusions on SI in a cohort of veterans. METHODS/STUDY POPULATION: Veterans with PTSD+MDD (n = 15) received six intravenous infusions of 0.5 mg/kg ketamine on a Monday-Wednesday-Friday schedule over a 12-day period. All subjects endorsed SI at baseline. Outcome measures included the Montgomery-Asberg Depression Rating Scale (MADRS) total score, MADRS suicidal ideation item, and PTSD symptom Checklist for DSM-5 (PCL-5) subscales (intrusion, avoidance, negative alterations in cognition and mood, and marked alterations in arousal and reactivity), and visual analog scale of pain. Measures were collected immediately before and 24-hours after each infusion. RESULTS/ANTICIPATED RESULTS: Significant improvement in SI was observed 24-hours after the first infusion (Z = 3.21; p = .001) and remained significantly improved at all other post-infusion time points. Improvement in SI at the conclusion of the infusion series was significantly correlated with PTSD subscales of avoidance (r(12) = .610, p = .021), negative alterations in cognition and mood (r(12) = .786, p = .001), alterations in arousal and reactivity (r(12) = .729, p = .003), and pain (r(12) = .591, p = .013), even when controlling for improvement in symptoms of depression. DISCUSSION/SIGNIFICANCE OF IMPACT: The present analysis provides evidence of improvement in SI in a cohort of veterans with PTSD+MDD. Improvements in suicidality were correlated with PTSD symptom subscales and pain independent of improvement in depression. This report extends the interpersonal theory of suicide as it applies to posttraumatic pathology by demonstrating a significant association between improvements in all subclusters of PTSD, improvement in pain and improvement in suicidal ideation.

OBJECTIVES/GOALS: Although referrals for specialty consultations are a core clinical process, they are prone to coordination and communication breakdowns that have led to adverse clinical outcomes. This project’s objective is to improve timely documentation, transmission, access, and quality of consultation notes across healthcare systems. METHODS/STUDY POPULATION: There are two specific aims for this project. In Aim 1, we will characterize clinical workflows and information flow during cross-institutional referrals. In Aim 2, we will develop and test a prototype leveraging electronic health information exchange (HIE) to increase closing the loop for cross-institutional referrals and improve the quality of consultation notes. To accomplish these aims, we will use human factors methods, including data analytics, medical-record reviews, semi-structured interviews of consultants, rapid prototyping, and usability evaluations. RESULTS/ANTICIPATED RESULTS: Results will inform the design and integration of clinician-facing technologies into clinical workflows to close the referral loop and improve diagnostic processes. Aim 1 will provide quantitative evidence about the quality of cross-institutional referrals, inform the eventual implementation of our prototype, and identify user interface features required for successful electronic health information exchange. Based on the results from Aim 1, reports and visual representations will be generated to illustrate information flows and clinical workflows. This will prioritize design efforts for the intervention’s prototype. Aim 2 will translate clinicians’ requirements into prototype features and assess clinicians’ experience with the prototype. DISCUSSION/SIGNIFICANCE OF IMPACT: The use and usefulness of HIE has been limited due to usability and implementation issues. Cross-institutional referrals are complex and dependent on HIE due to EHRs’ lack of interoperability. This project will provide evidence-based recommendations for the use of Fast Healthcare Interoperability Resources (FHIR) to improve HIE during referrals.

Objectives/Goals: Effective research relies on a well-trained study coordinator workforce, but mentorship programs are lacking. Retaining and empowering career development for skilled research staff is challenging. To address this, the Michigan Institute for Clinical and Health Research launched the STEP.up program. Methods/Study Population: The Staff Enrichment Program for Research Professionals (STEP.up) was created in 2018. To increase knowledge and awareness of our program, we developed an implementation guide to share best practices and open access to our program structure and content. We identified seven critical elements integral to program success. The implementation guide provides a description and rationale for these elements. We partnered with an instructional designer to build a descriptive and easy-to-use guide that describes insights into the successful implementation of the program, practical strategies for program management, and adaptable resources for institutions to use and tailor to their unique needs. Results/Anticipated Results: In the STEP.up program, early career, new-to-role, or new-to-organization research staff members are paired with senior research professionals in a 9-month structured mentorship and career development experience to promote professional development, job satisfaction, and retention for individuals currently working as research professionals. Of the 82 participants from 2018 to 2024, 76 (93%) have remained in their roles as study coordinators. The STEP.up program implementation guide provides the tools, resources, and insights senior research professionals need to implement this program successfully at their sites. Discussion/Significance of Impact: STEP.up program materials are available as an open-source resource on the DIAMOND portal. This resource can encourage others to invest in structured mentorship for research professionals to help establish a culture of growth and cultivate a resilient, skilled, and committed research workforce.

ABSTRACT IMPACT: We explored the use of machine learning to explore how multi-pollutant air quality is related to type 2 diabetes, which is more representative than the single pollutant models often employed to assess this relationship. OBJECTIVES/GOALS: Single pollutant air pollution models have correlated air pollution components with type 2 diabetes mellitus (DM). However, air pollution is a complex mixture, therefore, we explored the relationship between multi-pollutant air quality and DM incidence using machine learning. METHODS/STUDY POPULATION: Annual diabetes incidence from the CDC for each US county was downloaded for the years 2007-2016. Daily air pollution concentrations for PM2.5, PM10, CO, SO2, NO2, and O3 were downloaded from the US EPA for the years 2006-2015. K-means clustering, an unsupervised machine learning method, was employed to partition all air pollution components, for each day and county monitored, into the optimal number of clusters. Change in DM incidence was matched to air pollution clusters by county, lagged by one year. Additionally, NASA satellite-derived air pollution data will be compared to EPA data to inspect as a potential source for future clustering analysis of counties that do not have an EPA monitor. RESULTS/ANTICIPATED RESULTS: The largest increase of annual DM incidence was associated with the cluster having the highest average PM10, PM2.5, and CO, and the second greatest average NO2 concentrations. Inversely, the most significant decrease of annual DM incidence was associated with the cluster having the lowest PM10, PM2.5, and CO. While average PM10, PM2.5, SO2, NO2, and CO showed a rising tendency with elevating change of DM incidence, ozone did not show any such trend. It is anticipated that the NASA satellite-derived air pollution data will approximate the EPA air quality data and will be usable in assessing the air pollution-DM relationship for areas currently not monitored by the EPA. DISCUSSION/SIGNIFICANCE OF FINDINGS: Using an unsupervised k-means algorithm, we showed multiple ambient air components were related to increased incidence of T2DM even when average concentrations were below the National Ambient Air Quality Standards. This work could help guide policy making regarding air quality standards in the future.

OBJECTIVES/SPECIFIC AIMS: The first goal of this project is to test the reliability and validity of an objective structured clinical exam (OSCE) that was designed to assess competency in clinical and translational research. The second goal is to evaluate the impact of MICHR’s Summer Research Program on the participating trainee’s competency development. METHODS/STUDY POPULATION: The methodology used for this study was reviewed and exempted from oversight by the U-M Institutional Review Board (HUM00113293). The participants in the study include 17 pre-doctoral students in health professions programs at U-M who participated MICHR’s Summer Research Program. The Research OSCE was administered using a pretest, post-test design. The pretest was administered once during the 1st week of program in the Summer of 2016 and the post-test during the 10th week of the program. The Research OSCE was proctored and rated by trained staff members. We will assess the reliability of the Research OSCE using Generalizability Theory (Webb et al., 2006). And the construct validity of the Research OSCE will be tested using factor analysis and other statistical analyses. Growth in the competence of the trainees participating in the Summer Research program will be evaluated by testing for significant differences between their pretest and post-test scores. RESULTS/ANTICIPATED RESULTS: We anticipate that this study will show that the Research OSCE is a reliable competency assessment with proven construct validity. We also anticipate that the use of the Research OSCE will show the trainees participating in the Summer Research program experienced a gain in competence during the course of the 10-week program. DISCUSSION/SIGNIFICANCE OF IMPACT: This project uses a common and standardized testing approach. The primary goal of this project is to evaluate the reliability and validity of an OSCE to assess competency in clinical and translational research. It represents a new application for a well-studied testing method used extensively in the health professions to assess the clinical competency of health practitioners. This project will lead to a better understanding of (a) the reliability and validity of the Research OSCE designed to test research competency and (b) the effectiveness of the Summer Research Program curriculum in better preparing participants to conduct clinical and translational research. Showing how a specific competency assessment can be used for this purpose will provide the administrators, evaluators, and other stakeholders of clinical and translational research training programs with information that can be used to design more rigorous and relevant evaluations of their research training programs.

OBJECTIVES/GOALS: Older adults are affected by insufficient access to digital technology including digital healthcare. The aim of this program is to improve digital literacy in elders who were not using digital devices due to age and socioeconomic inequities. We provided technology and education on topics relevant but not limited to navigating health care. METHODS/STUDY POPULATION: Through partnerships with a non-profit organization helping elders to age well and independently (cohort 1 ongoing n=9) and an urban place of worship (cohort 2 starting), we reached out to elders residing in urban Buffalo, NY’s poorest zip codes. Participants received free tablets and Wi-fi hotspots. Participants received weekly interactive sessions over 6 months at their apartments or a place they felt comfortable with. A curriculum was developed but the sessions were not limited to digital health care, rather were also tailored to other individual needs like shopping on line, communication with loved ones, etc. A baseline, mid and post survey were administered to assess needs before the program and measure the impact of the program. An effort was also deployed in identifying a source of connectivity post program. RESULTS/ANTICIPATED RESULTS: The participants were elders who did not have computer/digital knowledge and/or access to the digital world. Mid-intervention data show that 9/9 used the tablets, learned basic skills and felt more comfortable/confident using a digital device. 5/9 participants used their hotspots and the remaining learned to use Wi-Fi provided by the facility they live in. While at baseline only 1/9 participants had attempted to use patient portals, mid-intervention data showed that 8/9 accessed portals. Importantly, the participants are also using other digital functions essential to their well-being including streaming, shopping, bill paying, and communicating with loved ones. Preliminary post-surveys suggest that all participants now rate their internet literacy and web searching skills at an acceptable/good level. DISCUSSION/SIGNIFICANCE: Tailored support and access to technology led to uptake of digital technology among elders, enabling them to access health-related resources and other web activities which improved their quality of life and led to digital equity. This project can be leveraged to obtain funding to train trusted members of the community as digital literacy ambassadors.

OBJECTIVES/SPECIFIC AIMS: To examine the racial/ethnic variation in the relation between metabolic syndrome (MetS) components and cardiovascular disease (CVD) as well as examine the role of uric acid as a predictor of CVD among population with MetS. METHODS/STUDY POPULATION: We analyzed National Health and Nutrition Examination Surveys data (1999–2010) for adults aged >20 years with MetS. Using the ATP III clinical criteria for diagnosing MetS, subjects were classified as having MetS if they had ≥3 of the following: waist circumference ≥40 inches for men or ≥35 inches for women, triglyceride ≥150 mg/dL, HDL-C for men ≤40 mg/dL; women ≤50 mg/dL, pre-hypertension, or fasting glucose ≥110 mg/dL. We used multiple logistic regression in STATA 14 survey module to examine the relation between MetS components and CVD adjusting for age, gender, race/ethnicity, education, smoking, alcohol, albuminuria, glomerular filtration rate, C-reactive protein, uric acid and white blood count. To assess the racial/ethnic variation, we examined the same model in each race/ethnic group. RESULTS/ANTICIPATED RESULTS: Of the 3212 subjects, 78% were Whites, 10% were Blacks, and 15% had CVD. MetS components, CVD, and uric acid varied significantly by race/ethnicity (p<0.05). In the multivariate model, HDL-C level [odds ratio (OR)=1.5; 95% confidence interval (CI)=1.1–2.0], triglyceride level (OR=2.0; CI=1.4–2.9), and elevated uric acid (OR=1.4; CI=1.1–1.9) were independently related to CVD (p<0.05). While CVD was independently related to HDL-C, triglyceride, and elevated uric acid in Whites (p<0.05), it was associated with pre-hypertension and triglyceride in Blacks (p<0.05) and no predictors in Hispanics (p>0.05). DISCUSSION/SIGNIFICANCE OF IMPACT: Elevated uric acid, HDL-C, and triglyceride levels are significant independent predictors of CVD among population with MetS. These predictors varied by race/ethnicity. Health care providers should be vigilant in the management of MetS components and control of uric acid level in each racial/ethnic group to prevent the CVD risk among the population with MetS.

ABSTRACT IMPACT: Measuring and analyzing qualitative and quantitative traits using phenomics approaches will yield previously unrecognized heart failure subphenotypes and has the potential to improve our knowledge of heart failure pathophysiology, identify novel biomarkers of disease, and guide the development of targeted therapeutics for heart failure. OBJECTIVES/GOALS: Current classification schemes fail to capture the broader pathophysiologic heterogeneity in heart failure. Phenomics offers a newer unbiased approach to identify subtypes of complex disease syndromes, like heart failure. The goal of this research is to use data-driven associations to redefine the classification of the heart failure syndrome. METHODS/STUDY POPULATION: We will identify < 10 subphenotypes of patients with heart failure using unsupervised machine learning approaches for dense multidimensional quantitative (i.e. demographics, comorbid conditions, physiologic measurements, clinical laboratory, imaging, and medication variables; disease diagnosis, procedure, and billing codes) and qualitative data extracted from an integrated health system electronic health record. The heart failure subphenotypes we identify from the integrated health system electronic health record will be replicated in other heart failure population datasets using unsupervised learning approaches. We will explore the potential to establish associations between identified subphenotypes and clinical outcomes (e.g. all-cause mortality, cardiovascular mortality). RESULTS/ANTICIPATED RESULTS: We expect to identify < 10 mutually exclusive phenogroups of patients with heart failure that have differential risk profiles and clinical trajectories. DISCUSSION/SIGNIFICANCE OF FINDINGS: We will attempt to derive and validate a data-driven unbiased approach to the categorization of novel phenogroups in heart failure. This has the potential to improve our knowledge of heart failure pathophysiology, identify novel biomarkers of disease, and guide the development of targeted therapeutics for heart failure.

OBJECTIVES/SPECIFIC AIMS: This work develops an algorithm that identifies patients in a Sequential Multiple Assignment Randomized Trial (SMART) who should switch treatments prior to the end of a stage because clinical effectiveness via their current intervention is unlikely. This algorithm uses as inputs patient baseline and interim measurements to assign a probability that a patient should switch or stay on their current intervention. First, the algorithm will be derived assuming both a linear and non-linear patient trajectory. Second, the performance of the algorithm will be assessed using trial data from the Establishing Moderators and Biosignatures of Antidepressant Response in Clinical Care† (EMBARC) study. The primary objective of the algorithm is to switch treatment in patients who will not reach clinical effectiveness by the end of the stage, and the secondary objective is to avoid accidentally switching treatment in patients who will reach clinical effectiveness by the end of the stage. †Trivedi et al. Journal of Psychiatric Research 78 (2016) 11-23 METHODS/STUDY POPULATION: First, the algorithm was derived assuming a linear or non-linear trajectory. Next, performance of the algorithm was assessed using data from the Establishing Moderators and Biosignatures of Antidepressant Response in Clinical Care† (EMBARC) study. This two-stage SMART design measured the effectiveness of sertraline in 242 patients with nonpsychotic Major Depressive Disorder (MDD). The algorithm was applied to baseline and interim measurements from the EMBARC study to predict end-stage Hamilton Depression (HAMD17) scores, the primary outcome of the study. True positive rate (TPR) and false positive rate (FPR) were used to measure respectively the primary study objective (switching treatment in patients who will not reach clinical effectiveness by the end of the stage), and the secondary study objective (avoiding accidentally switching treatment in patients who will reach clinical effectiveness by the end of the stage). TPR and FPR were calculated for the following prediction scenarios: (1) three separate two-point predictions: Baseline and Week 2, Baseline and Week 4, Baseline and Week 6, and (2) a single three-point prediction: Baseline and Weeks 2 and 6. †Trivedi et al. Journal of Psychiatric Research 78 (2016) 11-23 RESULTS/ANTICIPATED RESULTS: When using two-point prediction, we found TPR to increase and FPR to decrease as the interim measurements approached closer to the end of the stage. We also found TPR to increase when using a three-point prediction, but at the expense of FPR also increasing. Across these scenarios, TPR ranged between 70 and 90%, and FPR ranged between approximately 20 and 50%. DISCUSSION/SIGNIFICANCE OF IMPACT: Although SMART designs ultimately assign patients to more effective treatments, this process can take time and leave a patient (currently on an ineffective treatment) waiting until the end of a stage to try a potentially superior treatment. This disadvantage of the SMART design is currently addressed by this algorithm. By introducing a regression and likelihood approach to predict whether a patient should switch or stay on their current treatment, we move closer to the goal of designing rigorous, patient-centered studies. This work has the potential to improve individual clinical outcomes for patients enrolled in pragmatic clinical trials.