OBJECTIVES/GOALS: Military personnel are at significantly greater risk for developing tinnitus, due to increased exposure to acoustic trauma. Many psychiatric disorders are common among individuals with chronic tinnitus, including posttraumatic stress disorder (PTSD). Although tinnitus and PTSD are clearly different, research supports the notion of shared mechanisms between both disorders. First, there are overlapping symptoms between tinnitus-related distress and PTSD, including irritability, distorted cognitions, persistent negative emotional states, diminished interests in activities, exaggerated startle response, sleep disturbance, concentration problems, and hypervigilance. Second, tinnitus and PTSD are highly comorbid with one another, whereas 34% of veterans with tinnitus also carry a PTSD diagnosis. Third, those with both disorders are significantly more emotionally impaired compared to those with tinnitus and any other psychiatric disorder. Lastly, neuroimaging research has shown similar regions within the auditory vigilance network are implicated among those with tinnitus, and separately, among combat PTSD patients, suggesting shared neurobiological mechanisms between both disorders. Though we are aware that tinnitus and comorbid PTSD presents as a significantly greater clinical concern, the relationship between tinnitus-related distress and PTSD symptomotology it is still unknown. Canonical correlation analyses will be conducted to examine the relationship between tinnitus-related distress and PTSD among veterans as a part of a larger clinical trial for posttraumatic headache. Results of the study will shed light on the relationship between tinnitus-related distress and PTSD, and may suggest a different phenotype for those with both disorders. Researchers and clinicians will further understand and conceptualize the relationships among the cognitive, emotional, and behavioral symptoms associated with tinnitus and PTSD, both individually and conjointly. METHODS/STUDY POPULATION: Baseline data (N = 112) from a larger clinical trial examining the effectiveness of two different psychotherapies for the alleviation of posttraumatic headache was examined. The primary aim of this project was to evaluate the relationship between tinnitus-related distress and PTSD based on the eight subscale scores of the Tinnitus Functional Index (TFI) and the four scales of the Clinician Administered PTSD Scale for the DSM-5 (CAPS-5), respectively. To address this aim, canonical correlation analysis was used where the tinnitus-related symptom subscales made up one variable set and PTSD symptom subscales made up the second variable set. First, we evaluated the overall model fit based on Wilks Lambda to determine if the two variable sets were related at the p < .05 level. Next, we evaluated the canonical correlations (comparable to an eigenvalue) for each canonical dimension to determine the required number of significant canonical dimensions (or latent constructs) that were necessary to understand the association between the two variable sets. Finally, the standardized canonical coefficients, which are analogous to regression coefficients, evaluate the magnitude of variate relationships and determine which subscales best describe significant canonical dimensions. RESULTS/ANTICIPATED RESULTS: Prior to the canonical correlation analysis, total score descriptive statistics and subscale score zero-order correlations were carried out. The CAPS-5 total score was 33.24 (SD = 9.39) and the TFI total score was 50.81 (SD = 21.88) in this sample. Interpretation of the zero-order correlations indicated that TFI Relaxation subscale was the only tinnitus-related subscale moderately associated with a PTSD subscale (i.e., Reexperiencing, r = .35). Canonical correlation omnibus model fit analysis via the Wilks Lambda overall multivariate test indicated that the tinnitus variable set was significantly associated with the PTSD variable set, F = 1.55, p = .04. Evaluation of the canonical correlations indicated that one dimension was significant in explaining the relationship between the two variable sets and accounted for 25% of the overall variance, F = 1.55, p < .04, R2 = .249. Standardized canonical coefficients indicated that the PTSD subscales Reexperiencing (b = 0.64) and Negative Alterations in Cognition and Mood (b = 0.55) were the most representative of the identified canonical dimension. In terms of the TFI, the Relaxation (b = 1.28) and Sleep (b = 0.72) subscales appeared to be most related to the canonical dimension. The TFI subscales Auditory Difficulty (b = −0.30) and Quality of Life (b = 0.30) also appeared to be related the canonical dimension to a lesser degree. DISCUSSION/SIGNIFICANCE OF IMPACT: Findings support prior research suggesting particularly deleterious functional outcomes among individuals with comorbid tinnitus and PTSD. Results of this study suggest a latent variable that can explain the unique experience of individuals with both disorders. This latent variable consists of two PTSD constructs: Reexperiencing traumatic events (i.e., flashbacks, nightmares, intrusive memories), and Negative Alterations in Cognition and Mood (i.e., self- and other-blame, strong negative feelings, loss of interest, feeling distant). This latent variable also consists of two tinnitus-related constructs: Sleep (i.e., trouble falling and staying asleep, peaceful sleep) and Relaxation (i.e., ability to relax, enjoyment of peace and quiet). Auditory Difficulty (i.e., hear clearly, understand people) and Quality of Life (i.e., social activities, relationships, difficulty performing tasks) also contributed to the latent variable, but to a lesser degree. It is suggested that the constellation of symptoms related to the latent variable is a Dysphoric Factor, unique to individuals with PTSD, tinnitus, and posttraumatic headache. It may be necessary to incorporate different techniques into existing evidence-based treatments for both tinnitus and PTSD, for optimal symptom improvement.

OBJECTIVES/GOALS: To compare rates and types of neurological symptoms in children hospitalized with seizures and respiratory infections, including SARS-CoV-2, influenza, and endemic coronaviruses. METHODS/STUDY POPULATION: Retrospective cohort study of children between 0-21 years of age admitted to a single pediatric free-standing quaternary referral center from January 1, 2014 to June 1, 2021 for seizures who had positive respiratory infection PCR for SARS-CoV-2, other coronaviruses (Coronavirus NL63 and Coronavirus OC34), influenza (A and B), adenovirus, Mycoplasma pneumoniae, and parainfluenza 3 or 4 infections. Patient characteristics including age, race, sex, ethnicity, hospital length of stay, intensive care unit admission, intubation, chest x-ray, and MRI results were included. The primary outcomes were rates of neurological diagnoses and mortality. RESULTS/ANTICIPATED RESULTS: A total of 883 children were included: 68 SARS-CoV-2, 232 influenza, and 187 with other coronaviruses (OC), 214 adenovirus, 20 M. pneumoniae, 121 parainfluenza 3, and 41 parainfluenza 4. Mortality rates were 0% M pneumoniae to 4.9% in parainfluenza 4, with 2.9% in SARS-CoV-2. Encephalopathy was noted in 5-15.6% and strokes were seen in all infections except for coronavirus OC43 and M. pneumoniae, with 4.9% in parainfluenza 4 and 5.9% in SARS-CoV-2. The most common brain MRI abnormality was diffusion restriction. Differences between SARS-CoV-2 and OC were observed in stroke (5.9% vs. 0.5%, p-value=0.019), ICU admission (50% vs. 69%, p-value=0.008), and intubation (19.1% vs. 34.8%, p-value=0.021, respectively). However, the rates of neurological symptoms were similar between SARS-CoV-2 and influenza. DISCUSSION/SIGNIFICANCE: We found higher rates of stroke, but lower rates of ICU admission and intubation in SARS-CoV-2 versus OC. Strokes were observed in many infections. Rates of neurological symptoms were similar in SARS-CoV-2 versus influenza patients. Vigilance should be undertaken in treatment of children presenting with all respiratory illnesses.

OBJECTIVES/SPECIFIC AIMS: The main aim of this study was to investigate the interaction between glomerular filtration rate (GFR) and body mass index (as well as serum leptin) as determinants of peripheral and central insulin sensitivity (IS). METHODS/STUDY POPULATION: This was a cross-sectional investigation of 140 nondiabetic participants – 56 with CKD (GFR = 15-59 ml/min/1.73m2) and 94 with normal GFR (≥ 60 ml/min/1.73m2) – recruited as part of the relationship of insulin sensitivity in kidney disease and vascular health (RISKD) study. Peripheral (skeletal muscle) and central (hepatic) IS were assessed with the hyperinsulinemic euglycemic glucose clamp (HEGC) and homeostasis assessment of insulin resistance (HOMA-IR) respectively. Creatinine-based estimated GFR (eGFR) was obtained using the CKD-EPI equation and body mass index (BMI) was computed from baseline weight and height measurements. Linear regression models with robust standard errors (to relax homoscedasticity assumptions) and interaction terms were used to investigate GFR and BMI as predictors of HEGC-derived insulin sensitivity index (ISI) and HOMA-IR. RESULTS/ANTICIPATED RESULTS: The mean (SD) age was 53.9 (14.5) years; 50.7% were female and 36.7% were African-American. Compared to controls, CKD patients had significantly lower mean (SD) ISI [5.4 (3.2) vs. 3.1 (1.6), p < 0.0001]. Log ISI was positively correlated (r = 0.39, p < 0.0001) with eGFR and inversely correlated (−0.30, p < 0.0001) with BMI and log leptin (−0.42, p < 0.0001). In multivariable models adjusted for age, sex and race, a 10 ml/min/1.73m2 lower eGFR was associated with a greater decrease in ISI among non-obese (0.48; 95% CI: −0.25, −0.70) compared to obese participants (−0.18; 95% CI: −0.02, −0.35) (p-interaction = 0.04). Patients with low eGFR (in particular, the lower margin of the CKD stage 3 range, 30ml/min) had lower ISI even with BMI within normal range (Figure 1a). At higher eGFR, BMI had a greater impact on ISI. P-interaction = 0.046, for differential BMI effects at lower vs. higher eGFR. Log HOMA-IR was inversely correlated with eGFR (r = - 0.49, p < 0.0001) and positively correlated with BMI (r = 0.52, p < 0.0001) and log leptin (0.46, p < 0.0001). HOMA-IR was lower for persons with higher GFR compared to lower GFR, at any BMI value. For example, at a BMI of 30 and a GFR of 120, HOMA-IR was 1.2 compared to 4.8 at a GFR of 30 (Figure 1b). Also, persons with high GFR had low HOMA-IR even with BMI in the obese range. BMI had a greater effect on HOMA-IR at lower eGFR. P-interaction = 0.005, for differential BMI effects at lower vs. higher eGFR. Similar findings were obtained when using log leptin in lieu of BMI in models for ISI and HOMA-IR. DISCUSSION/SIGNIFICANCE OF IMPACT: Measures of adiposity (BMI and leptin) and GFR were independently predictive of insulin sensitivity (IS) but the magnitude of the effect of BMI (or leptin) on IS varied significantly across GFR levels and type of IS (peripheral versus central). The effect of BMI on central IS (HOMA-IR) was more pronounced at lower GFR with small changes in BMI translating into greater variations in IS. Conversely, at low GFR, peripheral IS (ISI) is less affected by BMI. Persons with GFR at the lower margin of the CKD stage 3 range were significantly insulin resistant (low ISI) regardless of their BMI. More studies are required to further elucidate these interaction patterns for central and peripheral IS.

OBJECTIVES/SPECIFIC AIMS: To describe adverse behavioral symptoms attributed to droxidopa therapy for neurogenic orthostatic hypotension (nOH). METHODS/STUDY POPULATION: BACKGROUND: Droxidopa, a norepinephrine (NE) precursor, improves symptoms of nOH by replenishing NE levels. Central NE effects are poorly described but may offer potential benefits given the pathophysiologic progression of α-synuclein-related disorders. Here we report a series of cognitive and behavioral side effects linked to droxidopa therapy. METHODS: We identified 5 patients treated at Vanderbilt University who developed behavioral symptoms including mania, irritability, and disorientation shortly after the initiation of droxidopa for nOH. Comprehensive chart reviews were performed for all patients, including analysis of droxidopa titration schedule and dosing, medical comorbidities, clinical course, and outcome. All patients had symptoms of synucleinopathy, manifesting with autonomic failure, REM behavior disorder, and parkinsonism. Four met criteria for idiopathic PD, and one was diagnosed with pure autonomic failure but had concomitant symptoms of parkinsonism and REM sleep behavior disorder. RESULTS/ANTICIPATED RESULTS: Our patients had no significant cognitive or behavioral symptoms before the initiation of droxidopa. The average decrease in blood pressure upon standing was 27 mmHg systolic and 17 mmHg diastolic. Behavioral disturbances were observed early in the titration period and at relatively low doses of droxidopa (total daily doses ranging from 300 to 800 mg/day; droxidopa therapeutic dose range 900–1800 mg/d). The most common symptoms reported were mania, irritability, and confusion. Symptoms resolved with dose reduction in 4 patients, and droxidopa was discontinued in 1 patient due to persistent irritability. No other medical comorbidities or alternative etiologies were identified to explain these effects. DISCUSSION/SIGNIFICANCE OF IMPACT: Droxidopa is a prodrug designed to act peripherally, but may also have important, yet poorly described, central effects. We hypothesize that these behavioral manifestations result from an “overdose” of key NE networks linking orbitofrontal and mesolimbic regions. Further studies are warranted to better characterize central NE effects in patients treated with droxidopa.

Deep learning has pushed the scope of digital pathology beyond simple digitization and telemedicine. The incorporation of these algorithms in routine workflow is on the horizon and maybe a disruptive technology, reducing processing time, and increasing detection of anomalies. While the newest computational methods enjoy much of the press, incorporating deep learning into standard laboratory workflow requires many more steps than simply training and testing a model. Image analysis using deep learning methods often requires substantial pre- and post-processing order to improve interpretation and prediction. Similar to any data processing pipeline, images must be prepared for modeling and the resultant predictions need further processing for interpretation. Examples include artifact detection, color normalization, image subsampling or tiling, removal of errant predictions, etc. Once processed, predictions are complicated by image file size – typically several gigabytes when unpacked. This forces images to be tiled, meaning that a series of subsamples from the whole-slide image (WSI) are used in modeling. Herein, we review many of these methods as they pertain to the analysis of biopsy slides and discuss the multitude of unique issues that are part of the analysis of very large images.

The Mountain West Clinical and Translational Infrastructure Network Community Engagement and Outreach (CEO) Core has fostered academic-community engagement since 2018. States historically receiving lower levels of NIH funding are characterized by significantly higher proportions of rural and remote populations, as well as uniquely elevated percentages of Native American/Alaska Native and Native Hawaiian/Pacific Islander populations compared to most other states. This case study highlights the Core’s efforts in advancing community-engaged research. Key initiatives included forming a CEO Core Steering Committee to recruit interdisciplinary investigators, establishing regional community advisory boards to identify research priorities, and creating a Resource Library and Training Portal for stakeholders. The Core also collaborated with other Cores to provide training, mentorship, and funding for community-engaged research. Despite these achievements, geographical and cultural diversity presented engagement challenges. Regular meetings between investigators and stakeholders ensured bidirectional communication and aligned goals. The Core transformed transactional engagement into meaningful collaboration, emphasizing the need for interdisciplinary teams who understand community needs. Future goals include training academic teams, clinical providers, and community members, empowering early-stage investigators to share findings with partners, leveraging health records for research, and developing strategies to protect investigators’ time.

Exclusion of special populations (older adults; pregnant women, children, and adolescents; individuals of lower socioeconomic status and/or who live in rural communities; people from racial and ethnic minority groups; individuals from sexual or gender minority groups; and individuals with disabilities) in research is a pervasive problem, despite efforts and policy changes by the National Institutes of Health and other organizations. These populations are adversely impacted by social determinants of health (SDOH) that reduce access and ability to participate in biomedical research. In March 2020, the Northwestern University Clinical and Translational Sciences Institute hosted the “Lifespan and Life Course Research: integrating strategies” “Un-Meeting” to discuss barriers and solutions to underrepresentation of special populations in biomedical research. The COVID-19 pandemic highlighted how exclusion of representative populations in research can increase health inequities. We applied findings of this meeting to perform a literature review of barriers and solutions to recruitment and retention of representative populations in research and to discuss how findings are important to research conducted during the ongoing COVID-19 pandemic. We highlight the role of SDOH, review barriers and solutions to underrepresentation, and discuss the importance of a structural competency framework to improve research participation and retention among special populations.

OBJECTIVES/SPECIFIC AIMS: Cancer related pain presents a significant risk for opioid abuse among cancer survivors and contributes to the current opioid crisis. Nearly 90% of breast cancer patients have been reported to have cancer-related pain requiring treatment. Opioids, in combination with NSAIDs, have been widely used for pain management in this population despite the risk of abuse. Long-term NSAID use due to their antineoplastic and neuroprotective effects may offer additional protective effects against opioid abuse. Here, we assess the relationship between NSAID use and opioid abuse among breast cancer patients. METHODS/STUDY POPULATION: Using ICD-9-CM codes, we identified and selected women aged >18 years with breast cancer from the National Inpatient Sample (NIS). Our primary predictor was a history of long-term NSAID use. Opioid abuse was the primary outcome of interest. Secondary outcomes were inpatient mortality and length of stay. Multivariable regression models were employed in assessing the association between predictors and outcomes while adjusting for relevant covariates. RESULTS/ANTICIPATED RESULTS: Among 170,644 women with breast cancer, 7,838 (4.6%) reported a history of long-term NSAID use. Patients with a history of long-term NSAID use had lower odds of opioid abuse (aOR 0.53; 95% CI [0.32-0.88]) and in-hospital mortality (aOR 0.52; 95% CI [0.45-0.60]) and were likely to have shorter hospital stay (7.12 vs. 8.11 days) compared to women with no history of long-term NSAID use. DISCUSSION/SIGNIFICANCE OF IMPACT: Long-term NSAID use may offer a protective effect against opioid abuse and improve in-hospital outcomes translating to better quality of life and healthcare utilization indices among breast cancer patients.

OBJECTIVES/GOALS: We aim to extend a novel statistical method called the Semi-Supervised Mixture Multisource Exchangeability Model (SS-MIX-MEM) and to implement the SS-MIX-MEM approach to supplement ALPS-COVID data with N3C data to achieve analyses with greater precision and actionable conclusions. METHODS/STUDY POPULATION: We will apply the SS-MIX-MEM to supplement the Angiotensin receptor blocker-based Lung Protective Strategy for COVID-19 (ALPS-COVID) RCTs with the National COVID Cohort Collaborative (N3C) database. ALPS-COVID includes both an inpatient and outpatient trial, which investigate losartan as a treatment for COVID-19. The outpatient trial sought to randomize 580 individuals but only enrolled 117, whereas the inpatient trial met its enrollment target and randomized 205 individuals. The N3C database has 3,237,344 COVID-19 cases alongside demographics, lab values, and more. RESULTS/ANTICIPATED RESULTS: In simulation studies, the proposed SS-MIX-MEM approach effectively leveraged a subgroup of supplemental real world data for RCT analyses, improving trial efficiency by increasing precision of treatment effect estimates, decreasing necessary sample size, and introducing minimal bias. In an influenza trial real world data application, the SS-MIX-MEM approach was able to effectively provide insight into treatment effect heterogeneity found in an RCT analogous to incorporating around 80 individuals into a subgroup analysis. We anticipate that leveraging external real world data in a re-analysis of the ALPS-COVID RCTs could provide new insights into losartan, a readily available, potentially beneficial therapeutic for COVID-19. DISCUSSION/SIGNIFICANCE: The high blood pressure drug, losartan, is readily available, has an established safety profile, and might be effective as a treatment for COVID-19. Given that we have very few effective treatment options and are still in the midst of a global pandemic, patients with COVID-19 would greatly benefit from a repurposed, readily available treatment.

OBJECTIVES/SPECIFIC AIMS: Background: Delirium is a well described form of acute brain organ dysfunction characterized by decreased or increased movement, changes in attention and concentration as well as perceptual disturbances (i.e., hallucinations) and delusions. Catatonia, a neuropsychiatric syndrome traditionally described in patients with severe psychiatric illness, can present as phenotypically similar to delirium and is characterized by increased, decreased and/or abnormal movements, staring, rigidity, and mutism. Delirium and catatonia can co-occur in the setting of medical illness, but no studies have explored this relationship by age. Our objective was to assess whether advancing age and the presence of catatonia are associated with delirium. METHODS/STUDY POPULATION: Methods: We prospectively enrolled critically ill patients at a single institution who were on a ventilator or in shock and evaluated them daily for delirium using the Confusion Assessment for the ICU and for catatonia using the Bush Francis Catatonia Rating Scale. Measures of association (OR) were assessed with a simple logistic regression model with catatonia as the independent variable and delirium as the dependent variable. Effect measure modification by age was assessed using a Likelihood ratio test. RESULTS/ANTICIPATED RESULTS: Results: We enrolled 136 medical and surgical critically ill patients with 452 matched (concomitant) delirium and catatonia assessments. Median age was 59 years (IQR: 52–68). In our cohort of 136 patients, 58 patients (43%) had delirium only, 4 (3%) had catatonia only, 42 (31%) had both delirium and catatonia, and 32 (24%) had neither. Age was significantly associated with prevalent delirium (i.e., increasing age associated with decreased risk for delirium) (p=0.04) after adjusting for catatonia severity. Catatonia was significantly associated with prevalent delirium (p<0.0001) after adjusting for age. Peak delirium risk was for patients aged 55 years with 3 or more catatonic signs, who had 53.4 times the odds of delirium (95% CI: 16.06, 176.75) than those with no catatonic signs. Patients 70 years and older with 3 or more catatonia features had half this risk. DISCUSSION/SIGNIFICANCE OF IMPACT: Conclusions: Catatonia is significantly associated with prevalent delirium even after controlling for age. These data support an inverted U-shape risk of delirium after adjusting for catatonia. This relationship and its clinical ramifications need to be examined in a larger sample, including patients with dementia. Additionally, we need to assess which acute brain syndrome (delirium or catatonia) develops first.

OBJECTIVES/GOALS: The Clinical Research Professionals (CRP) at Cincinnati Children’s Hospital Medical Center (CCHMC) identified and addressed gaps in a static on boarding material by transforming it into an interactive, centralized, and customizable REDCap checklist to better meet researcher needs across the institution. METHODS/STUDY POPULATION: The CRP On boarding Checklist is a tool designed to assist clinical researchers in their onboarding process at CCHMC. This tool helps CRPs determine the required/recommended trainings available to assist with skill-building and establishing job role competency. CRP supervisorsand subject matter experts were included incontent revisions, format, and transition to a RED Capsurvey. The new checklist is interactive, targets training requirements by job function, and clearly labels mandatory training. A companion document allows new CRPs to create and track their own individualized training plan. RESULTS/ANTICIPATED RESULTS: The revised CRP On boarding Checklist was launched in April 2022 and announced via email communication. Alive demonstration was presented to all CRPs during the May 2022 CRP Monthly Meeting. The checklist and companion document are linked to the internal CRP website, which is accessible institutionally. Sincelaunch, almost 100 new and internally transferring CRPs have utilized the online tool to guide their training needs. The checklist is intended to reflect real-time changes in educational offerings. In addition to feedback and change requests from the CRP community, the checklist is updated as necessary and routinely reviewed on a biannual basisby the CRP Education Committee. DISCUSSION/SIGNIFICANCE: The creation and maintenance of the CRP Onboarding Checklist is a modern and accessible way for CRPs and supervisors to explore role-applicable training and take active roles in the on boarding process. The RED Capformat allows easy sharing and adoptability to other institutions via data dictionary.

OBJECTIVES/SPECIFIC AIMS: To develop a regulatory science case study as an educational resource to inform the regulatory science considerations in medical product development for a range of scientific priority areas and emerging technologies. METHODS/STUDY POPULATION: Precision medicine represents one of the major regulatory science priority areas and the use of biomarkers holds promise for predicting the response to individual treatment strategies. Although progress has been made toward developing biomarkers, the development and validation of clinically useful biomarkers has presented significant regulatory science challenges, including the utilization of biomarkers in predicting responses to different cancer therapies. This case study reviews the technical, regulatory, and policy issues related to the development and use of lung cancer drugs Opdivo® and Keytruda® and an understanding of the codevelopment and utilization of their associated biomarkers. RESULTS/ANTICIPATED RESULTS: A detailed instructor guide with extensive resources such as diagrams and timelines will accompany the case study and will be used to highlight the development and approval process of 2 competing drugs and their associated biomarkers. The resources will provide a better understanding of their progression through the FDA regulatory process and opportunities and challenges for their use. DISCUSSION/SIGNIFICANCE OF IMPACT: Building on the case study framework we have developed, the detailed timelines and a collection of available resources, an extensive and modular case study will be finalized and made available to academic institutions, industry, regulatory agencies, and the public. The full case study and links to a series of resources will be disseminated as a standalone resource for integration into courses or programs interested in learning about specific regulatory science needs and opportunities to enhance medical product development and approval.

OBJECTIVES/GOALS: 1. To characterize domains of maternal psychosocial stress from the Edinburgh Postnatal Depression Scale (EPDS) and Cohens Perceived Stress Scale (PSS) administered during pregnancy using principal components analysis (PCA). 2. To identify sociodemographic, perinatal, and lifestyle correlates of maternal psychosocial stress domains. METHODS/STUDY POPULATION: Using data from 1,079 pregnant women in the Healthy Start Study who completed both the EPDS and PSS in early pregnancy, we ran PCA and retained factors representative of uncorrelated domains of maternal psychosocial stress based on the Scree plot and Eigenvalues >1. We then used linear regression to identify sociodemographic, perinatal, and lifestyle correlates of each maternal stress domain, followed by multivariable models that mutually adjusted for all characteristics that were statistically significant at alpha = 0.10. RESULTS/ANTICIPATED RESULTS: We identified three domains of maternal psychosocial stress based on PCA results: Feeling Overwhelmed (Domain 1), Anhedonia (Domain 2), and Lack of Control (Domain 3). In unadjusted analyses, lower household income and poor diet quality were associated with higher scores for all three domains. In adjusted analyses, lower household income, being multiparous, inadequate or excessive GWG, and poor diet quality were associated with Feeling Overwhelmed. Older age, Hispanic ethnicity, and poor diet quality were associated with Anhedonia. Non-Hispanic, Black race/ethnicity, lower educational attainment, having a partner born outside the US, larger household size, receiving public assistance, and smoking during pregnancy were associated with Lack of Control. DISCUSSION/SIGNIFICANCE: We identify three unique domains of maternal psychosocial stress that are differentially related to sociodemographic, perinatal, and lifestyle characteristics. Correlates of stress domains shed light on upstream determinants and biological and psychosocial mechanisms through which experiences of stress manifest.

OBJECTIVES/GOALS: Research in Action is an on-demand, interactive curriculum designed to increase the ability of clinicians to advance the Academic Learning Health System (aLHS). The 7-module course provides clinicians with the knowledge and skills to lead rigorous quality improvement (QI) projects, translating research evidence into practice. METHODS/STUDY POPULATION: We engaged nurses, physicians, and advanced practice providers (APPs) working in the health system to participate in focus group and advise us in the creation of the curriculum. We conducted focus groups with these stakeholders on the proposed learning objectives, course content, and mode of delivery (in person, virtual, hybrid). Informed by the focus groups, the course was designed for hybrid format so participants could either (1) access the modules on-demand, or (2) learners could participate in a facilitator moderated course where the modules served as the curriculum to guide development of a QI project. The Iowa Model of Evidence-Based Practice was the framework for curriculum development. Upon completion of the modules, stakeholders reviewed each module and provided feedback for improvement. RESULTS/ANTICIPATED RESULTS: Research in Action is a 7-module course, with modules addressing the following topics: (1) Introduction to Quality Improvement, (2) Identify the Problem and Write a Purpose Statement, (3) Form a Team, (4) Appraise and Synthesize the Literature, (5) Design and Pilot the Project, (6) Integrate and Sustain Practice Change, (7) Disseminate the Results. The curriculum is being piloted with multiple clinician groups in the health system. In the next phase of development, a facilitator guide will be created to guide a cohort of clinicians to apply knowledge through discussion sessions and completion of a QI project in the healthcare setting. We anticipate scaling the program for spread to diverse clinician groups in the health system. Pre- and post-implementation data are being collected from current pilot sites. DISCUSSION/SIGNIFICANCE: The aLHS is an essential means for improving healthcare delivery. Research in Action, a hybrid training curriculum, engages frontline clinicians in creating and leading QI projects that implement research evidence into practice to solve problems commonly encountered in the healthcare setting; thus, supporting the advancement of the aLHS.

ABSTRACT IMPACT: The findings from this study will inform the development of an FDA-approved patient-rated outcome measure of drug and alcohol craving that can be used in clinical trials aimed at developing or testing effective treatments for substance use disorder. OBJECTIVES/GOALS: Craving is a potential target of investigative medications to reduce drug use due to the strong link between craving and drug use. We will identify all existing craving measures as the first step for developing an FDA-approved patient-rated outcome measure for use in clinical trials. METHODS/STUDY POPULATION: Following PRISMA guidelines, we will update Rosenberg’s (2009) craving review by conducting a systematic review of all existing published and unpublished measures of craving for alcohol, nicotine, cannabis, opioid, and stimulant use. Electronic database (i.e., Ovid MEDLINE, Embase, PsycINFO, Web of Science, Cochrane), forward, backward, and author searches will be conducted. We will also request unpublished craving measures on major listservs (e.g., Research Society on Alcoholism, the Collaborative Perspectives on Addiction, and the College on Problems of Drug Dependence). All papers included in Rosenberg’s (2009) review through September 2020 will be included. RESULTS/ANTICIPATED RESULTS: The findings from this review will provide a comprehensive summary of the construct of craving and its hypothesized and tested domains. This review will elucidate whether the literature suggests there are components of craving unique to alcohol, nicotine, cannabis, opioid, and/or stimulant use, and whether there are key elements of craving common across the disorders. Therefore, these findings will inform whether a single patient-rated outcome measure of craving can be developed for use across substances or if unique patient-rated outcome measures of craving need to be developed for each substance. DISCUSSION/SIGNIFICANCE OF FINDINGS: While many different measures of craving exist, none have gone through the developmental steps required to qualify as an FDA-approved patient-rated outcome measure on which drug treatment labeling can be based. Completing this systematic review is the first step in this process.

ABSTRACT IMPACT: Investigation of tumor-associated blood vessels may serve as an imaging biomarker of response to systemic therapy and cancer outcomes. OBJECTIVES/GOALS: Aberrancies in the tumor microvasculature limit the systemic delivery of anticancer agents, which impedes tumor response. Using human intravital microscopy (HIVM), we hypothesized that HIVM would be feasible in patients with peritoneal carcinomatosis (PC) and generate clinical utility. METHODS/STUDY POPULATION: During cytoreductive surgery with hyperthermic intraperitoneal chemotherapy for PC, HIVM was performed in both tumor and non-tumor areas. The primary outcome was HIVM feasibility to measure vessel characteristics. We secondarily evaluated associations between HIVM vessel characteristics and oncologic outcomes (RECIST response to neoadjuvant therapy and disease-specific survival). RESULTS/ANTICIPATED RESULTS: Thirty patients with PC were enrolled. Nineteen patients (63.3%) received neoadjuvant therapy. HIVM was feasible in all patients. Compared to non-tumor (control) areas, PC areas had a lower density of functional vessels, higher proportion of non-functional vessels, smaller lumenal diameters, and lower blood flow velocity. Qualitative differences in these vessel characteristics were observed among patients who had partial response, stable disease, or progressive disease after receiving neoadjuvant therapy. However, no statistically significant relationships were found between HIVM vessel characteristics and oncologic outcomes. DISCUSSION/SIGNIFICANCE OF FINDINGS: These novel findings comprise the first-in-human, real-time evidence of the microscopic differences between normal and tumor-associated vessels and form the basis for our larger, ongoing clinical trial appropriately powered to determine the clinical utility of HIVM (NCT03823144).

Objectives/Goals: Syncope is a common diagnosis in observation medicine, and characterization of observation patients is often limited to single unit, single center, or single payer systems. TriNetX, a federated deidentified multicenter national public database, provides an opportunity to study these patients from across the USA. Methods/Study Population: This retrospective cohort study queried data from 56 health care organizations (HCO) in TriNetX to examine differences between observation patients with syncope who required admission vs. those who were discharged. All observation stays with a diagnosis of syncope, defined by ICD-10, CPD, and SNOWMED codes, were queried. A total of 281,162 observation encounters were included in analysis, of which 46.4% (n = 130,357) were admitted and 53.6% (n = 150,805) were discharged. Data on age, gender, race, ethnicity, presence of congestive heart failure, EKG, and serum labs were collected for comparative analysis. T-test and Chi-square analyses were deployed with significance  =  p Results/Anticipated Results: The cohorts demonstrated statistically significant differences across all demographic factors, however, they were not clinically meaningful. Clinically significant differences include that only 72.8% of admitted patients and 68.3% of discharged patients had an EKG recorded in TriNetX during the period of observation (p Discussion/Significance of Impact: Patients admitted from observation status were more likely to have CHF, higher BNP, and pro-BNP values. TriNetX is a powerful tool to study patients across multiple hospital systems and payer types. Limitations, however, include incomplete data and inaccuracies among claims records.