OBJECTIVES/SPECIFIC AIMS: Missing data is a common problem in research studies that may lead to inconclusive or inaccurate results. It may even lead to harm secondary to wrong research conclusions. The purpose of this ancillary study is to measure the differences in missing data following implementation of a variety of mechanisms to improve data quality and documentation in a global quality improvement study. Many of the sites involved in the study were in low-income or middle-income countries with minimal research infrastructure. Missing data is defined as “values that are not available that would be meaningful for analysis if they were observed” (The prevention and treatment of missing data, New Engl J Med 367; 14, nejm.org, October 4, 2012). METHODS/STUDY POPULATION: All study sites used REDCap software to enter various data points including hospital and ICU admission and discharge dates as well as whether items on a Checklist relevant to processes of care in the ICU were reviewed. After initial general data collection phase, we categorized data as “must have” and “good to have.” “Must have” variables were defined as data variables that were essential for the study outcomes. “Good to have” variables would not affect the main outcomes of the study if missing. We measured completeness of data using the in-built REDCap data quality check feature. We used several strategies to encourage reduction of missing data. We initially did random data checks but noted that the amount of missing data was substantial and could not be adequately addressed this way. Second, we created excel sheets highlighting missing data for each site and notified sites. This proved onerous to create and made it burdensome for sites to identify easily where data was missing. Third, we built a custom report form in REDCap specifically able to identify which “must have” data points were missing. This could be easily accessed by the principal investigator at each site and made completing the data forms more straightforward. We encouraged all sites to complete their data collection by sending weekly data reports to each site highlighting the patients with missing data. An instructional YouTube tutorial was also created and the link was shared with all sites to demonstrate how to use the custom built report form in REDCap and how to appropriately fill in the missing data. Since this was a global study, we communicated with sites using a variety of locally favored mechanisms including Zoom, FaceTime, WeChat, WhatsApp as well as email. By harnessing the buy-in of local champions our approach was successful. RESULTS/ANTICIPATED RESULTS: The total number of patients recruited for the CERTAIN study is 4843. The rate of all missing variables improved with the efforts described above. Hospital admission dates were missing in 8.4% pre efforts and 4.2% post efforts (p<0.01). ICU admission dates were missing in 5.5% pre and 2.0% post (p<0.01). Documentation of completion of processes of care (including central line review, urinary catheter review, consideration for blood transfusion) improved significantly from pre to post (p<0.01). DISCUSSION/SIGNIFICANCE OF IMPACT: Missing data can be a problem in all types of research studies. This study provides some preliminary evidence for effective approaches that can reduce the problem of missing data when conducting a global study at sites with limited research infrastructure in place. By addressing the concern about missing data, we can be more confident that our results can be accurately analyzed and interpreted, improving the quality of the research.

ABSTRACT IMPACT: This work will impact participants of clinical trials by better informing them of their trial’s results and their important role within the clinical research process. OBJECTIVES/GOALS: This project aims to equip researchers with an online tool for the development, dissemination, and collection of participant feedback for plain language clinical trial (CT) result summaries (PLCTRS). PLCTRS ensure that participants fully understand their trial’s results and their role in the CT process. METHODS/STUDY POPULATION: This online development platform is a web application made with CSS, HTML, and JavaScript. First, general trial identification information including study aims and eligibility will be input by researchers. Then, they will be prompted with tips and suggestions for composing in plain language and to ensure inclusion of all essential trial information. Next, the platform will disseminate this writing electronically to participants. Participants then provide meaningful feedback on the platform about their comprehension for the researcher, which the platform will aggregate and summarize for revisions. This process of drafting and feedback is repeated until a satisfactory PLCTRS is finalized. RESULTS/ANTICIPATED RESULTS: The anticipated results of this project are overall improved comprehension of clinical trial results by participants. This comprehension will be measured by participants ability to answer certain questions not only regarding trial outcomes, but also about the trial in general. For instance, before and after interacting with the PLCTRS, trial participants will be asked if they can identify which investigational drug was being studied and its possible side effects. This project could anticipate identification of trial elements and results deemed difficult to comprehend by participants; thus they would be better informed after interacting with the platform. DISCUSSION/SIGNIFICANCE OF FINDINGS: This project will ensure that participants better comprehend the trials they participated in beyond the required informed consent process - which only covers their comprehension prospectively. This project seeks to address the gap of ensuring participant comprehension retrospectively.

Mini-sabbaticals are formal short-term training and educational experiences away from an investigator’s home research unit. These may include rotations with other research units and externships at government research or regulatory agencies, industry and non-profit programs, and training and/or intensive educational programs. The National Institutes of Health have been encouraging training institutions to consider offering mini-sabbaticals, but given the newness of the concept, limited data are available to guide the implementation of mini-sabbatical programs. In this paper, we review the history of sabbaticals and mini-sabbaticals, report the results of surveys we performed to ascertain the use of mini-sabbaticals at Clinical and Translational Science Award hubs, and consider best practice recommendations for institutions seeking to establish formal mini-sabbatical programs.

Despite the critical role academic medical institutions play in promoting equity and inclusion, these efforts are often undermined by fragmented and siloed evaluation approaches, a lack of theory-driven models, and inadequate data-driven methodologies. This commentary critically examines the factors contributing to the persistent challenges in implementing and advancing equity and inclusion initiatives in the United States (U.S.), focusing on academic medical institutions in particular. It underscores the need for theory-guided frameworks to better structure and evaluate such initiatives and highlights existing gaps in accountability and data-driven decision-making. Moreover, it argues for an integrated approach that combines multidisciplinary strategies, promoting collaboration across different sectors to develop more comprehensive and sustainable solutions. Ultimately, effective evaluation – grounded in data, theory, and diverse perspectives – is essential for promoting equity and inclusion and addressing disparities in U.S. academic medical institutions. By addressing these structural and evaluative shortcomings, institutions can move towards more impactful and equitable outcomes for underrepresented groups in STEM fields and the biomedical workforce more broadly.

Well-designed, accessible short-term research training programs are needed to recruit and retain underrepresented persons into clinical and translational research training programs and diversify the workforce. The Michigan Institute for Clinical and Health Research developed a summer research program, training over 270 students in 15 years. In response to the 2020 COVID-19 pandemic, we pivoted swiftly from an in-person format to a fully remote format. We describe this process, focusing on factors of diversity, equity, and inclusion including enabling student participation in remote research activities. We collected data about students’ learning experiences since the program’s inception; therefore, we could evaluate the impact of remote vs. in-person formats. We examined data from five cohorts: three in-person (2017–2019; n = 57) and two remote (2020–2021; n = 45). While there was some concern about the value of participating in a remote format, overall students in both formats viewed the program favorably, with students in the remote cohorts rating some aspects of the program significantly more favorably. In addition, more students who identified as Black or African American participated in the remote format than in the in-person format. We describe lessons learned from this unprecedented challenge and future program directions.

Clinical translational neuroscience (CTN) is positioned to generate novel discoveries for advancing treatments for mental health disorders, but it is held back today by the siloing of bioethical considerations from critical consciousness. In this article, we suggest that bioethical and critical consciousness can be paired to intersect with structures of power within which science and clinical practice are conducted. We examine barriers to the adoption of neuroscience findings in mental health from this perspective, especially in the context of current collective attention to widespread disparities in the access to and outcomes of mental health services, lack of representation of marginalized populations in the relevant sectors of the workforce, and the importance of knowledge that draws upon multicultural perspectives. We provide 10 actionable solutions to confront these barriers in CTN research, as informed by existing frameworks such as structural competency, adaptive calibration models, and community-based participatory research. By integrating critical consciousness with bioethical considerations, we believe that practitioners will be better positioned to benefit from cutting-edge research in the biological and social sciences than in the past, alert to biases and equipped to mitigate them, and poised to shepherd in a robust generation of future translational therapies and practitioners.

OBJECTIVES/GOALS: Nearly half of mothers who report electronic (e)-cigarette use during pregnancy believe e-cigarettes are less harmful than traditional cigarettes. We aim to determine the association of quitting e-cigarette use in pregnancy with the risk of preterm birth and low birth weight. METHODS/STUDY POPULATION: We conducted a cross-sectional study of women participating in the Pregnancy Risk Assessment Monitoring System and with live singleton birth during 2016-2019. Women were classified based on their e-cigarette use: before pregnancy only (quitters), last three months of pregnancy only (initiators), at both times (sustained users), and neither time (non-users). We used a modified Poisson regression to determine the association between quitting e-cigarette use and preterm birth (<37 weeks) and low birth weight (<2,500 grams) adjusting for demographic, social-economic, and behavior-related risk factors. Analyses were weighted to account for the survey design and non-response. RESULTS/ANTICIPATED RESULTS: Based on 150,950 women who responded to the survey, there were estimated 2.9% quitters, 0.2% initiators, 1.0% sustained users, and 95.9% non-users in the U.S. Compared to sustained e-cigarette users, quitters had a similar risk in preterm birth (adjusted risk ratio [ARR]: 0.84, 95% confidence interval [CI]: 0.65, 1.08) and a significantly reduced risk in low birth weight (ARR: 0.77, 95%CI: 0.61, 0.97) adjusting for traditional cigarette use, age, race/ethnicity, education, marital status, family income, prior preterm birth, prior live births, BMI prior to pregnancy, pregnancy weight gain, kotelchuck index, multivitamin use, drinking prior to pregnancy, year of birth, and residential state. DISCUSSION/SIGNIFICANCE: As FDA authorizes the sales of certain e-cigarettes, women smokers may switch to e-cigarettes, believing they are reducing harm. Our study shows that quitting e-cigarette use is associated with a reduction of low birth weight. Clear messaging is needed to help women cease e-cigarette use in pregnancy.

OBJECTIVES/SPECIFIC AIMS: The iobio project enables anyone (eg, diagnosticians, MDs, genetic counselors, citizen scientists) to perform useful analysis of genomic data, without a need to rely on bioinformaticians. iobio uses a novel real-time analysis framework, coupled with powerful visualizations delivered in a standard web browser. The project successfully supports free academic/nonprofit users, but occasions exist where it is more applicable for the project to be delivered commercially. Frameshift Genomics is developing commercial applications and functionality, which will exist alongside and in coordination with the academic project. These products will be marketed to large institutions including genome institutes, hospitals, diagnostic labs etc., but also to individual users who do not have access to large compute resources, or bioinformatic analysts, and everything in between. METHODS/STUDY POPULATION: The commercial iobio project under Frameshift Genomics aims to develop applications and features that cannot be successfully supported by an academic model. For example, when analyses are scaled up to processing of extremely large data sets, a commercial product with access to compute resources makes more sense than an academic tool. Bam.iobio is an application that samples data from sequencing alignment files, taking seconds to generate and visualize statistics representative of the entire file. This app is offered for free academically. When analysis involves thousands of such files, however, the commercial application, multibam.iobio, is more suitable. Other examples, including support for licensed third-party software and permitting extensive computation via cloud platforms, can also only be reasonably be supported via commercial software. Finally, development of commercial applications is driving adoption of more rigorous testing platforms, delivering more robust products. A particular strength of the iobio platform is allowing non-bioinformaticians to understand their data, for example providing quality control functionality providing confidence in data sets and the conclusions drawn from them. Such analyses are critical to all users of genomic data, and the iobio platform is ideally suited to provide an intuitive, integrated framework for performing them. RESULTS/ANTICIPATED RESULTS: The iobio project has been readily adopted by many in the community and shows significant promise for democratizing genomic analysis. Work is ongoing, supported by NIH small business grants, to develop commercial applications that will be marketed to analysts and medical professionals from large genome institutes and universities, to individual project users and citizen scientists. DISCUSSION/SIGNIFICANCE OF IMPACT: There are currently a number of iobio tools available academically, and they have been embraced by many in the genomics community. In fact, a number of popular platforms (eg, Galaxy, the International Cancer Genome Consortium (ICGC) data portal, mygene2 at the University of Washington) have incorporated iobio tools into their own platforms. To date, the gene.iobio variant interrogation tool has been used in a number of diagnostic projects, aiding identification of putative causative variants, and the pre-release version of the commercial multibam.iobio tool has been critical in unearthing data quality problems in project level data.

Objectives/Goals: Intra-amniotic inflammation (IAI) is one of the leading causes of maternal/fetal morbidity globally, yet it is undiagnosed in 90–95% of cases. The purpose of this study was to assess precision and accuracy of a novel microsampling device for measuring cytokines in amniotic fluid (AF) to enable noninvasive evaluation of localized inflammation. Methods/Study Population: AF was obtained from discarded amniocentesis samples from 3 deidentified patients without known inflammation. Samples were spiked to 5 concentrations of interleukin-6 (IL-6) and tumor necrosis factor-a (TNF-a), then sampled using the Neoteryx Mitra volumetric microsampling device (20 µL). Dried/reconstituted samples were analyzed using the Luminex R&D Mag XL multiplex (IL-6, TNF-α) and compared to free-flowing AF. Inter-and intra-assay performances were evaluated across 5-runs in 3 standard cytokine concentrations. Recovery/linearity was assessed by a recovery curve and parameter estimates. Precision was assessed between-run and within-run using coefficients of variance (%CV). Accuracy was evaluated as agreement between microsampled and free-flowing AF using Bland–Altman plots. Results/Anticipated Results: TNF-α results were linear for all 3 patients across 5 concentrations. However, accuracy and recovery consistently failed (mean±SD percent recovery 176±21%). TNF-α results had acceptable precision with %CV within-run of 6.8–12.1% and across-runs of 14.0–15.9%. Microsampled TNF-α agreed with free-flowing sample: 16 of 18 (89%) were within 1SD of the mean difference (-24±36 pg/ml). IL-6 results were linear for 1/3 patients and had unacceptable accuracy and recovery for 13/15 samples (mean±SD percent recovery 764±469%). IL-6 results had acceptable precision (%CV within-run 6.2%, 7.5% and 11.2%; across-run .9–15.2%). Microsampled IL-6 agreed with free-flowing sample; 17 of 18 (94%) were within 1SD of the mean difference (-148±180pg/ml). Free-flowing vs. microsampling methods agreed best at low concentration. Discussion/Significance of Impact: This study provides preliminary support for noninvasive measurement of cytokines leveraging small amounts of leaking AF providing a promising alternative to amniocentesis and potential for assessing inflammation intrapartum. Clinical application requires development of reference ranges and association between cytokine levels and outcomes.

ABSTRACT IMPACT: The importance of this study is to evaluate the responses following the exposure of opioid drugs in young adults to address the current opioid epidemics OBJECTIVES/GOALS: To compare the proportion of patients between 18 and 25 years of age, who develop an opioid abuse disorder following dental surgery, to those following other surgical procedures, when an opioid drug is used for acute postoperative pain control. METHODS/STUDY POPULATION: We fashioned an IRB-sponsored retrospective cohort study of patients, ages 18 to 25 years old, who presented for dental surgery or other medical surgical procedures, at Strong Memorial Hospital Medical Center, at the University of Rochester and received opioid drug treatments, for acute surgical pain management. Patients with the diagnosis of acute surgical pain were included in the study. However, those with chronic pain or other related abnormalities were excluded, even if a diagnosis of acute surgical pain was present in the electronic chart. The clinical data were retrieved from electronic medical records and NYS-iStop records. All statistics were significant at the level of <0.1 RESULTS/ANTICIPATED RESULTS: We identified 167 subjects, of whom, only 150 subjects met inclusion criteria (n=100) in dentistry and (n=50) in other medical specialties. Patients were followed up in a 7-year period. Most of the subjects were females (n=91), Caucasian (n=80), and lived in a suburban location (n=78). The most frequently prescribed opioid included hydrocodone (n=119). A significantly higher proportion (8.7%) of patients developed opioid abuse disorders in the control group, compared to 1% of subjects in the experimental group (p 0.02). Those in the control group received marginally significant higher doses of MMEs 447.2 +/-644.8 mg vs 306.2 +/-354.7mg in the experimental group (p 0.086). Those in the control group had significantly longer periods of opioid treatment 10 (+/-12) compared to 6(+/-6) days in the experimental group DISCUSSION/SIGNIFICANCE OF FINDINGS: It is paramount to evaluate the morphine milligram equivalents, and duration of opioid treatment given to the young population with acute surgical pain, to prevent opioid abuse disorders in this vulnerable cohort.

Objectives/Goals: Triple-negative breast cancer (TNBC) is a highly aggressive and prevalent breast cancer subtype that lacks targeted therapies. This study aims to investigate whether the niclosamide derivative HJC0152 can modulate tumor-derived PD-L1 expression and enhance the effectiveness of anti-PD-1 immunotherapy in treating TNBC. Methods/Study Population: Niclosamide derivative HJC0152 was developed as a novel cancer therapeutic and immunomodulating agent. Human TNBC cell line (MDA-MB-231) was treated with HJC0152, and activation of the STAT3 signaling pathway was evaluated using Western blotting. RNA-Seq was employed to analyze the expression of protein-coding genes, particularly those related to immune response. To study therapeutic potential in vivo, TNBC mouse models will be treated with single agent treatments as well as a combination therapy of HJC0152 and anti-PD-1. Tumor volume and mass will be measured over time to determine growth inhibition. Results/Anticipated Results: Preliminary studies indicate that HJC0152 exhibits enhanced solubility compared to Niclosamide, along with high anticancer potency both in vitro and in vivo. HJC0152 was found to effectively inhibit the activation of phosphorylated STAT3 (p-STAT3) in MDA-MB-231 cells, a key signaling pathway associated with cancer progression and immune evasion. RNA-Seq analysis of HJC0152-treated MDA-MB-231 cells revealed a decrease in PD-L1 expression, an essential immune checkpoint protein involved in tumor immune suppression. These findings suggest that HJC0152 is a promising immune modulator that may enhance the efficacy of immune checkpoint blockade therapy for TNBC. Discussion/Significance of Impact: This study explores an innovative immunotherapy for TNBC using the Niclosamide derivative HJC0152, which inhibits STAT3 signaling and downregulates PD-L1. Results from this study will provide a foundation for HJC0152’s inclusion in clinical trials and potentially offer a new and promising therapeutic option for TNBC treatment.

Objectives/Goals: Within the machine learning “fairness” literature, models audits are point estimates, and only effect size is considered. The well-developed frameworks in biostatistics for diagnostic testing apply directly to classifiers more generally; these principles can be extended to have statistically valid fairness audits. Methods/Study Population: We made original linkages between machine learning methodology and biostatistics, particularly to diagnostic testing, to get analytic biostatistical methods for model evaluation that are applicable to fairness testing. Results/Anticipated Results: The use of odds ratios to compare ratios of binomial proportions is superior to taking ratios of binomial proportions directly, as is currently standard in machine learning. Odds ratios also have an analytic asymptotic approximation for standard errors, by which we can test if a point estimate (effect size) is greater than what we would expect from noise. In diagnostic testing, the odds ratios considered are generally across the cells of a confusion matrix, but we can form odds ratios for specific marginal quantities (positive predictive value, negative predictive value, true positive rate, true negative rate) for specific aspects of model performance or fairness. Discussion/Significance of Impact: Biostatistics can make direct contributions to instantly improve the state of machine learning practice, giving ready-made methods that can take account generations of hard-won lessons about the importance of uncertainty quantification and sample size in making claims and conclusions.

OBJECTIVES/SPECIFIC AIMS: Smoking during pregnancy (SDP) is associated with negative health outcomes, both proximal (e.g., preterm labor, cardiovascular changes, low birth weight) and distal (e.g., increased child externalizing behaviors and attention deficit/hyperactivity disorder (ADHD) symptoms, increased risk of child smoking). As pregnancy provides a unique, strong incentive to quit smoking, investigating SDP allows analysis of individual predictive factors of recalcitrant smoking behaviors. Utilizing a female twin-pair cohort provides a model system for characterizing genotype×environment interactions using statistical approaches. METHODS/STUDY POPULATION: Using women from the Missouri Adolescent Female Twin Study, parental report of twin ADHD inattentive and hyperactive symptoms at twin median age 15, and twin report of DSM-IV lifetime diagnosis of major depressive disorder, trauma exposure (physical assault and childhood sexual abuse), collected at median age 22, were merged with Missouri birth record data for enrolled twins, leading to 1553 individuals of European ancestry and 163 individuals of African-American ancestry included in final analyses. A SDP propensity score was calculated from sociodemographic variables (maternal age, marital status, educational attainment, first born child) and used as a 6-level ordinal covariate in subsequent logistic regressions. RESULTS/ANTICIPATED RESULTS: For European ancestry individuals, parental report of hyperactive ADHD symptoms and exposure to childhood sexual abuse were predictive of SDP, while a lifetime diagnosis of major depressive disorder, parental report of inattentive ADHD symptoms, and exposure to assaultive trauma were all not significantly predictive of future SDP. For African-American individuals, none of these variables were significant in predicting future SDP. DISCUSSION/SIGNIFICANCE OF IMPACT: Understanding this relationship of risk-mechanisms is important for clinical understanding of early predictors of SDP and tailoring interventions to at risk individuals. Ultimately, the focus of this research is to mitigate risk to pregnant smokers and their children. Additionally, the cohort-ecological approach informs how well research and administrative (vital record) data agree. This allows for evaluation of whether administrative data improve prediction in research cohorts, and conversely if research data improve prediction over standard sociodemographic variables available in administrative data.

OBJECTIVES/GOALS: Low statistical power is a problem is many fields. We performed a systematic review to determine the median statistical power of studies of epilepsy surgery outcomes. METHODS/STUDY POPULATION: We performed a PubMed search for studies reporting epilepsy surgery outcomes for the years 1980-2000, focusing on studies using stereo-electroencephalography (SEEG). We extracted patient count data for comparisons of surgical outcome between groups, based on a prognostic factor. We defined a clinically meaningful difference the surgical outcome for MRI positive (66.9%) compared to MRI negative (45.5%) in the largest study in the series. The statistical power of a Chi-square test was computed as the percentage of simulated runs (10,000 repetitions) assuming this difference with a p-value less than 0.05. RESULTS/ANTICIPATED RESULTS: Based on 69 studies, the median sample size was 38 patients, and the median statistical power was 24%. This implies at least a 17% (0.5/[0.24+0.05)) chance a study with a significant result in false, assuming 1:1 pre-test odds. A 'typical’ SEEG study with 33 patients and 2:1 allocation had a median significant odds ratio of 6.5, which over-estimates the true odds ratio of 2.4. DISCUSSION/SIGNIFICANCE: Studies of epilepsy surgery outcomes using SEEG are statistically underpowered. This means true effects will be missed, the chance a study with a significant result is false will be inflated, and significant effects found will be over-estimated. Studies of surgery outcome need better statistical rigor if they are to reliably guide treatment.

OBJECTIVES/GOALS: We adapted the Serious Illness Care Program (SICP), an evidence-based intervention designed to promote early serious illness conversation, to be delivered via telehealth for older patients with acute myeloid leukemia and myelodysplastic syndromes. The purpose of this study is to assess the feasibility and usability of the adapted intervention. METHODS/STUDY POPULATION: We are conducting a single-arm pilot study of an adapted SICP that is delivered via telehealth for older patients with AML or MDS (>=60 years) and their caregivers (if available). The adapted SICP includes: 1) Patient preparation pamphlet: sent to patient prior the visit with their clinician, 2) Geriatric assessment: completed by study team and provided to clinician prior to their visit with the patient, 3) A 30-60 minute telehealth visit with their primary oncologist or oncology advance practitioner, 4) Serious Illness Conversation Guide (SICG): used by the clinician during the visit to elicit patient values, 5) Family guide: provided to patient following their visit to help patient’s share their values with their family, 6) Electronic medical record note template for clinicians to document their visit the patient. RESULTS/ANTICIPATED RESULTS: We hypothesize that the adapted SICP intervention will be feasible and usable. We will assess feasibility based on retention rate (percent of patients who consent and complete the visit); >80% is considered feasible. Usability will be assessed using the telehealth usability questionnaire; an average score of >5 is considered usable. Other measures include psychological health, advance care planning engagement, quality of life, and disease understanding. We plan to enroll 20 patients in this study. To date, 11 patients have consented to participate, 10 patients have scheduled SICP visits, 9 patients have completed their visits, 7 patients have completed post-intervention qualitative interviews, and 4 patients have completed post-intervention surveys. DISCUSSION/SIGNIFICANCE: The adapted telehealth-based SICP may promote early serious illness conversation, patient-reported outcomes, and end-of-life experience for older patients with AML and MDS. Results from this study will be used to inform development of clinical trials testing the impact of the adapted SICP on patient- and caregiver-reported outcomes.

OBJECTIVES/SPECIFIC AIMS: 1. Determine positive predictive value, negative predictive value, sensitivity, and specificity of Neuro ICU nurse interpretation of real-time bedside qEEG. 2. Determine difference in time to detection of first seizure between Neuro ICU nurse qEEG interpretation and EEG fellow reads of cEEG. 3. Determine what qualities of seizures make detection by neuro ICU nurses more or less likely – e.g. duration of seizures, type of seizures, spatial extent of seizures. METHODS/STUDY POPULATION: Recruit neuro ICU nurses taking care of 150 patients admitted to the Neuro ICU at Duke University Hospital who are initiated on cEEG monitoring. Nurses will be consented for their participation in the study. Neuro ICU nurses will evaluate the qEE RESULTS/ANTICIPATED RESULTS: From literature estimates of a 20% seizure prevalence in critical care settings, we hope to have 30 patients with seizures and 120 without. Based on prior study in the Duke Neuro ICU, we hypothesize that Neuro ICU nurses will have sensitivity and DISCUSSION/SIGNIFICANCE OF IMPACT: This is the first prospective study of neuro ICU nurse interpretation of real-time bedside qEEG in patients with unknown NCSE/NCS presence. If nurse sensitivity, specificity, and positive predictive value are clinically useful, which we deem would be so at a sensitivity of 70% or greater, with acceptable false alarm rate, nurse readings of qEEG could significantly decrease the time to treatment of seizures in the Neuro ICU patient population, and perhaps could improve patient outcomes.

OBJECTIVES/GOALS: Open surgery prevails in low- and middle-income countries (LMICs) due to scarcity of laparoscopic equipment and poor access to training. LaparosopiX is a box trainer system designed for teaching hospitals in LMICs; it includes an open-source laser print design and an app to allow surgical trainees to receive feedback from laparoscopic experts. METHODS/STUDY POPULATION: This study aims to assess the usability of Laparoscopix for surgical trainees and mentors at five large teaching hospitals in Kenya. Surgical trainees and mentors who participate in this study will be observed while setting up and using the app to identify natural pain-points. A post-session survey will be conducted to assess immediate perceptions of the platform including ease of navigation and intuitive design. Over three months, aggregate data regarding platform usage at these hospital sites will be collected and analyzed to assess user retention rates, usage and traffic patterns, and skill progression over time. Surveys will be sent out to assess attitudes towards the platform and to elucidate any aspects of the system we can improve. RESULTS/ANTICIPATED RESULTS: We hope to find overall positive impressions towards the LaparoscopiX system during this study. We expect there to be some pain-points that arise during navigation of the app, but we expect no large changes to the application architecture required. We anticipate an immediate increase and eventual plateau of users recruited. We hope to see that surgical trainees are advancing through the app while gaining practice and confidence. We will gather insightful data on which aspects of the app were helpful for trainees, and which can be improved. We also hope to learn what factors may play into trainee and mentor retention in the system. DISCUSSION/SIGNIFICANCE: Through this study, we hope to elucidate ways in which we can improve the LaparoscopiX platform, identify which features to prioritize, and determine the direction of future app development. We believe and hope that LaparoscopiX can expand access to laparoscopic surgical mentorship to improve surgical outcomes and health equity worldwide.