An Integrated Hepatocyte Stability Assay for Simultaneous Metabolic Stability Assessment and Metabolite Profiling.

The determination of metabolic stability is critical for drug discovery programs, allowing for the optimization of chemical entities and compound prioritization. As such, it is common to perform high-volume in vitro metabolic stability experiments early in the lead optimization process to understand metabolic liabilities. Additional metabolite identification experiments are subsequently performed for a more comprehensive understanding of the metabolic clearance routes to aid medicinal chemists in the structural design of compounds. Collectively, these experiments require extensive sample preparation and a substantial amount of time and resources. To overcome the challenges, a high-throughput integrated assay for simultaneous hepatocyte metabolic stability assessment and metabolite profiling was developed. This assay platform consists of four parts: 1) an automated liquid-handling system for sample preparation and incubation, 2) a liquid chromatography and high-resolution mass spectrometry-based system to simultaneously monitor the parent compound depletion and metabolite formation, 3) an automated data analysis and report system for hepatic clearance assessment; and 4) streamlined autobatch processing for software-based metabolite profiling. The assay platform was evaluated using eight control compounds with various metabolic rates and biotransformation routes in hepatocytes across three species. Multiple sample preparation and data analysis steps were evaluated and validated for accuracy, repeatability, and metabolite coverage. The combined utility of an automated liquid-handling instrument, a high-resolution mass spectrometer, and multiple streamlined data processing software improves the process of these highly demanding screening assays and allows for simultaneous determination of metabolic stability and metabolite profiles for more efficient lead optimization during early drug discovery. SIGNIFICANCE STATEMENT: Metabolic stability assessment and metabolite profiling are pivotal in drug discovery to fully comprehend metabolic liabilities for chemical entity optimization and lead selection. Process of these assays can be repetitive and resource demanding. Here, we developed an integrated hepatocyte stability assay that combines automation, high-resolution mass spectrometers, and batch-processing software to improve and combine the workflow of these assays. The integrated approach allows simultaneous metabolic stability assessment and metabolite profiling, significantly accelerating screening and lead optimization in a resource-effective manner.

Disparities in seizure outcomes revealed by large language models.

OBJECTIVE: Large-language models (LLMs) can potentially revolutionize health care delivery and research, but risk propagating existing biases or introducing new ones. In epilepsy, social determinants of health are associated with disparities in care access, but their impact on seizure outcomes among those with access remains unclear. Here we (1) evaluated our validated, epilepsy-specific LLM for intrinsic bias, and (2) used LLM-extracted seizure outcomes to determine if different demographic groups have different seizure outcomes. MATERIALS AND METHODS: We tested our LLM for differences and equivalences in prediction accuracy and confidence across demographic groups defined by race, ethnicity, sex, income, and health insurance, using manually annotated notes. Next, we used LLM-classified seizure freedom at each office visit to test for demographic outcome disparities, using univariable and multivariable analyses. RESULTS: We analyzed 84 675 clinic visits from 25 612 unique patients seen at our epilepsy center. We found little evidence of bias in the prediction accuracy or confidence of outcome classifications across demographic groups. Multivariable analysis indicated worse seizure outcomes for female patients (OR 1.33, P ≤ .001), those with public insurance (OR 1.53, P ≤ .001), and those from lower-income zip codes (OR ≥1.22, P ≤ .007). Black patients had worse outcomes than White patients in univariable but not multivariable analysis (OR 1.03, P = .66). CONCLUSION: We found little evidence that our LLM was intrinsically biased against any demographic group. Seizure freedom extracted by LLM revealed disparities in seizure outcomes across several demographic groups. These findings quantify the critical need to reduce disparities in the care of people with epilepsy.

Four-dimensional flow MRI for quantitative assessment of cerebrospinal fluid dynamics: Status and opportunities.

Neurological disorders can manifest with altered neurofluid dynamics in different compartments of the central nervous system. These include alterations in cerebral blood flow, cerebrospinal fluid (CSF) flow, and tissue biomechanics. Noninvasive quantitative assessment of neurofluid flow and tissue motion is feasible with phase contrast magnetic resonance imaging (PC MRI). While two-dimensional (2D) PC MRI is routinely utilized in research and clinical settings to assess flow dynamics through a single imaging slice, comprehensive neurofluid dynamic assessment can be limited or impractical. Recently, four-dimensional (4D) flow MRI (or time-resolved three-dimensional PC with three-directional velocity encoding) has emerged as a powerful extension of 2D PC, allowing for large volumetric coverage of fluid velocities at high spatiotemporal resolution within clinically reasonable scan times. Yet, most 4D flow studies have focused on blood flow imaging. Characterizing CSF flow dynamics with 4D flow (i.e., 4D CSF flow) is of high interest to understand normal brain and spine physiology, but also to study neurological disorders such as dysfunctional brain metabolite waste clearance, where CSF dynamics appear to play an important role. However, 4D CSF flow imaging is challenged by the long T1 time of CSF and slower velocities compared with blood flow, which can result in longer scan times from low flip angles and extended motion-sensitive gradients, hindering clinical adoption. In this work, we review the state of 4D CSF flow MRI including challenges, novel solutions from current research and ongoing needs, examples of clinical and research applications, and discuss an outlook on the future of 4D CSF flow.

Scalable Incident Detection via Natural Language Processing and Probabilistic Language Models.

Post marketing safety surveillance depends in part on the ability to detect concerning clinical events at scale. Spontaneous reporting might be an effective component of safety surveillance, but it requires awareness and understanding among healthcare professionals to achieve its potential. Reliance on readily available structured data such as diagnostic codes risk under-coding and imprecision. Clinical textual data might bridge these gaps, and natural language processing (NLP) has been shown to aid in scalable phenotyping across healthcare records in multiple clinical domains. In this study, we developed and validated a novel incident phenotyping approach using unstructured clinical textual data agnostic to Electronic Health Record (EHR) and note type. It's based on a published, validated approach (PheRe) used to ascertain social determinants of health and suicidality across entire healthcare records. To demonstrate generalizability, we validated this approach on two separate phenotypes that share common challenges with respect to accurate ascertainment: 1) suicide attempt; 2) sleep-related behaviors. With samples of 89,428 records and 35,863 records for suicide attempt and sleep-related behaviors, respectively, we conducted silver standard (diagnostic coding) and gold standard (manual chart review) validation. We showed Area Under the Precision-Recall Curve of ∼ 0.77 (95% CI 0.75-0.78) for suicide attempt and AUPR ∼ 0.31 (95% CI 0.28-0.34) for sleep-related behaviors. We also evaluated performance by coded race and demonstrated differences in performance by race were dissimilar across phenotypes and require algorithmovigilance and debiasing prior to implementation.

Disparities in seizure outcomes revealed by large language models.

Objective: Large-language models (LLMs) in healthcare have the potential to propagate existing biases or introduce new ones. For people with epilepsy, social determinants of health are associated with disparities in access to care, but their impact on seizure outcomes among those with access to specialty care remains unclear. Here we (1) evaluated our validated, epilepsy-specific LLM for intrinsic bias, and (2) used LLM-extracted seizure outcomes to test the hypothesis that different demographic groups have different seizure outcomes. Methods: First, we tested our LLM for intrinsic bias in the form of differential performance in demographic groups by race, ethnicity, sex, income, and health insurance in manually annotated notes. Next, we used LLM-classified seizure freedom at each office visit to test for outcome disparities in the same demographic groups, using univariable and multivariable analyses. Results: We analyzed 84,675 clinic visits from 25,612 patients seen at our epilepsy center 2005-2022. We found no differences in the accuracy, or positive or negative class balance of outcome classifications across demographic groups. Multivariable analysis indicated worse seizure outcomes for female patients (OR 1.33, p = 3×10-8), those with public insurance (OR 1.53, p = 2×10-13), and those from lower-income zip codes (OR ≥ 1.22, p ≤ 6.6×10-3). Black patients had worse outcomes than White patients in univariable but not multivariable analysis (OR 1.03, p = 0.66). Significance: We found no evidence that our LLM was intrinsically biased against any demographic group. Seizure freedom extracted by LLM revealed disparities in seizure outcomes across several demographic groups. These findings highlight the critical need to reduce disparities in the care of people with epilepsy.

Longitudinal Lung Function Assessment of Patients Hospitalized With COVID-19 Using 1H and 129Xe Lung MRI.

BACKGROUND: Microvascular abnormalities and impaired gas transfer have been observed in patients with COVID-19. The progression of pulmonary changes in these patients remains unclear. RESEARCH QUESTION: Do patients hospitalized with COVID-19 without evidence of architectural distortion on structural imaging exhibit longitudinal improvements in lung function measured by using 1H and 129Xe MRI between 6 and 52 weeks following hospitalization? STUDY DESIGN AND METHODS: Patients who were hospitalized with COVID-19 pneumonia underwent a pulmonary 1H and 129Xe MRI protocol at 6, 12, 25, and 51 weeks following hospital admission in a prospective cohort study between November 2020 and February 2022. The imaging protocol was as follows: 1H ultra-short echo time, contrast-enhanced lung perfusion, 129Xe ventilation, 129Xe diffusion-weighted, and 129Xe spectroscopic imaging of gas exchange. RESULTS: Nine patients were recruited (age 57 ± 14 [median ± interquartile range] years; six of nine patients were male). Patients underwent MRI at 6 (n = 9), 12 (n = 9), 25 (n = 6), and 51 (n = 8) weeks following hospital admission. Patients with signs of interstitial lung damage were excluded. At 6 weeks, patients exhibited impaired 129Xe gas transfer (RBC to membrane fraction), but lung microstructure was not increased (apparent diffusion coefficient and mean acinar airway dimensions). Minor ventilation abnormalities present in four patients were largely resolved in the 6- to 25-week period. At 12 weeks, all patients with lung perfusion data (n = 6) showed an increase in both pulmonary blood volume and flow compared with 6 weeks, although this was not statistically significant. At 12 weeks, significant improvements in 129Xe gas transfer were observed compared with 6-week examinations; however, 129Xe gas transfer remained abnormally low at weeks 12, 25, and 51. INTERPRETATION: 129Xe gas transfer was impaired up to 1 year following hospitalization in patients who were hospitalized with COVID-19 pneumonia, without evidence of architectural distortion on structural imaging, whereas lung ventilation was normal at 52 weeks.

The Current Pediatric Surgery Job Market: A Perspective of Recent Fellowship Graduates.

PURPOSE: This study describes the job market from the perspective of recent pediatric surgery graduates. METHODS: An anonymous survey was circulated to the 137 pediatric surgeons who graduated from fellowships 2019-2021. RESULTS: The survey response rate was 49%. The majority of respondents were women (52%), Caucasian (72%), and had a median student debt burden of $225,000. Considering job opportunities, respondents strongly emphasized camaraderie (93%), mentorship (93%), case mix (85%), geography (67%), faculty reputation (62%), spousal employment (57%), compensation (51%), and call frequency (45%). 30% were satisfied with the employment opportunities available, and 21% felt strongly prepared to negotiate for their first job. All respondents were able to secure a job. Most jobs were university-based (70%) or hospital employed (18%) positions where surgeons covered median of two hospitals. 49% wanted protected research time, and 12% of respondents were able to secure substantial, protected research time. The median compensation for university-based jobs was $12,583 below the median AAMC benchmark for assistant professors for the corresponding year of graduation. CONCLUSION: These data highlight the ongoing need for assessment of the pediatric surgery workforce and for professional societies and training programs to further assist graduating fellows in preparing to negotiate their first job. TYPE OF STUDY: Survey LEVEL OF EVIDENCE: Level V.

Interactive, on-line visualization tools to measure and drive equity in COVID-19 vaccine administrations.

Equitable distribution of vaccines is necessary to ensure those at highest risk of illness are protected from COVID-19 (coronavirus disease 2019). Unfortunately, there is significant evidence that vaccines have not been reaching the most vulnerable. At our large hospital system, we created interactive online tools to measure and visualize equitability of vaccine administrations and to help stakeholders identify populations at highest risk within state-designated eligible vaccine groups. Using race, ethnicity, gender, and social vulnerability, we are able to measure and reflect our vaccine administration performance against the communities that we serve. With our visualization tools, stakeholders have been able to target interventions to improve equity in vaccine administrations, including improvements in race, ethnicity, and social vulnerability. We plan to use the data elements incorporated in our electronic health record and data warehouse due to the COVID-19 pandemic to guide further population health efforts at decreasing disparities.

Electronic health records and clinician burnout: A story of three eras.

OBJECTIVE: The study sought to provide physicians, informaticians, and institutional policymakers with an introductory tutorial about the history of medical documentation, sources of clinician burnout, and opportunities to improve electronic health records (EHRs). We now have unprecedented opportunities in health care, with the promise of new cures, improved equity, greater sensitivity to social and behavioral determinants of health, and data-driven precision medicine all on the horizon. EHRs have succeeded in making many aspects of care safer and more reliable. Unfortunately, current limitations in EHR usability and problems with clinician burnout distract from these successes. A complex interplay of technology, policy, and healthcare delivery has contributed to our current frustrations with EHRs. Fortunately, there are opportunities to improve the EHR and health system. A stronger emphasis on improving the clinician's experience through close collaboration by informaticians, clinicians, and vendors can combine with specific policy changes to address the causes of burnout. TARGET AUDIENCE: This tutorial is intended for clinicians, informaticians, policymakers, and regulators, who are essential participants in discussions focused on improving clinician burnout. Learners in biomedicine, regardless of clinical discipline, also may benefit from this primer and review. SCOPE: We include (1) an overview of medical documentation from a historical perspective; (2) a summary of the forces converging over the past 20 years to develop and disseminate the modern EHR; and (3) future opportunities to improve EHR structure, function, user base, and time required to collect and extract information.

Assessment of vascular stiffness in the internal carotid artery proximal to the carotid canal in Alzheimer's disease using pulse wave velocity from low rank reconstructed 4D flow MRI.

Clinical evidence shows vascular factors may co-occur and complicate the expression of Alzheimer's disease (AD); yet, the pathologic mechanisms and involvement of different compartments of the vascular network are not well understood. Diseases such as arteriosclerosis diminish vascular compliance and will lead to arterial stiffness, a well-established risk factor for cardiovascular morbidity. Arterial stiffness can be assessed using pulse wave velocity (PWV); however, this is usually done from carotid-to-femoral artery ratios. To probe the brain vasculature, intracranial PWV measures would be ideal. In this study, high temporal resolution 4D flow MRI was used to assess transcranial PWV in 160 subjects including AD, mild cognitive impairment (MCI), healthy controls, and healthy subjects with apolipoprotein ɛ4 positivity (APOE4+) and parental history of AD dementia (FH+). High temporal resolution imaging was achieved by high temporal binning of retrospectively gated data using a local-low rank approach. Significantly higher transcranial PWV in AD dementia and MCI subjects was found when compared to old-age-matched controls (AD vs. old-age-matched controls: P <0.001, AD vs. MCI: P = 0.029, MCI vs. old-age-matched controls P = 0.013). Furthermore, vascular changes were found in clinically healthy middle-age adults with APOE4+ and FH+ indicating significantly higher transcranial PWV compared to controls (P <0.001).

In Vitro Assessment of Flow Variability in an Intracranial Aneurysm Model Using 4D Flow MRI and Tomographic PIV.

Aneurysm rupture has been suggested to be related to aneurysm geometry, morphology, and complex flow activity; therefore, understanding aneurysm-specific hemodynamics is crucial. 4D Flow MRI has been shown to be a feasible tool for assessing hemodynamics in intracranial aneurysms with high spatial resolution. However, it requires averaging over multiple heartbeats and cannot account for cycle-to-cycle hemodynamics variations. This study aimed to assess cycle-to-cycle flow dynamics variations in a patient-specific intracranial aneurysm model using tomographic particle image velocimetry (tomo-PIV) at a high image rate under pulsatile flow conditions. Time-resolved and time-averaged velocity flow fields within the aneurysm sac and estimations of wall shear stress (WSS) were compared with those from 4D Flow MRI. A one-way ANOVA showed a significant difference between cardiac cycles (p value < 0.0001); however, differences were not significant after PIV temporal and spatial resolution was matched to that of MRI (p value 0.9727). This comparison showed the spatial resolution to be the main contributor to assess cycle-to-cycle variability. Furthermore, the comparison with 4D Flow MRI between velocity components, streamlines, and estimated WSS showed good qualitative and quantitative agreement. This study showed the feasibility of patient-specific in-vitro experiments using tomo-PIV to assess 4D Flow MRI with high repeatability in the measurements.

Mobile Momentary Assessment and Biobehavioral Feedback for Adolescents with Type 1 Diabetes: Feasibility and Engagement Patterns.

BACKGROUND: Integration of momentary contextual and psychosocial factors within self-management feedback may provide more specific, engaging, and personalized targets for problem solving. METHODS: Forty-four youth ages 13-19 with type 1 diabetes (T1D) were provided a Bluetooth meter and completed the 30-day protocol. Participants were randomized to "app + meter" or "meter-only" groups. App + meter participants completed mealtime and bedtime assessment each day. Assessments focused on psychosocial and contextual information relevant for self-management. Graphical feedback integrated self-monitored blood glucose (SMBG), insulin, and Bluetooth-transmitted blood glucose data with the psychosocial and contextual data. App + meter participants completed an interview to identify data patterns. RESULTS: The median number of momentary assessments per participant was 80.0 (range 32-120) with 2.60 per day. By 2 weeks participants had an average of 40.77 (SD 12.23) assessments. Dose-response analyses indicated that the number of app assessments submitted were significantly related to higher mean daily SMBG (r = -0.44, P < 0.05) and to lower% missed mealtime SMBG (r = -0.47, P < 0.01). Number of feedback viewing sessions was also significantly related to a lower% missed mealtime SMBG (r = -0.44, P < 0.05). Controlling for baseline variables, mixed-effects analyses did not indicate group × time differences in mean daily SMBG. Engagement analyses resulted in three trajectory groups distinguished by assessment frequencies and rates of decline. Engagement group membership was significantly related to gender, mean daily SMBG, and HbA1c values. CONCLUSIONS: Momentary assessment combined with device data provided a feasible means to provide novel personalized biobehavioral feedback for adolescents with T1D. A 2-week protocol provided sufficient data for self-management problem identification. In addition to feedback, more intensive intervention may need to be integrated for those patients with the lowest self-management at baseline.

Aortic flow patterns and wall shear stress maps by 4D-flow cardiovascular magnetic resonance in the assessment of aortic dilatation in bicuspid aortic valve disease.

BACKGROUND: In patients with bicuspid valve (BAV), ascending aorta (AAo) dilatation may be caused by altered flow patterns and wall shear stress (WSS). These differences may explain different aortic dilatation morphotypes. Using 4D-flow cardiovascular magnetic resonance (CMR), we aimed to analyze differences in flow patterns and regional axial and circumferential WSS maps between BAV phenotypes and their correlation with ascending aorta dilatation morphotype. METHODS: One hundred and one BAV patients (aortic diameter ≤ 45 mm, no severe valvular disease) and 20 healthy subjects were studied by 4D-flow CMR. Peak velocity, flow jet angle, flow displacement, in-plane rotational flow (IRF) and systolic flow reversal ratio (SFRR) were assessed at different levels of the AAo. Peak-systolic axial and circumferential regional WSS maps were also estimated. Unadjusted and multivariable adjusted linear regression analyses were used to identify independent correlates of aortic root or ascending dilatation. Age, sex, valve morphotype, body surface area, flow derived variables and WSS components were included in the multivariable models. RESULTS: The AAo was non-dilated in 24 BAV patients and dilated in 77 (root morphotype in 11 and ascending in 66). BAV phenotype was right-left (RL-) in 78 patients and right-non-coronary (RN-) in 23. Both BAV phenotypes presented different outflow jet direction and velocity profiles that matched the location of maximum systolic axial WSS. RL-BAV velocity profiles and maximum axial WSS were homogeneously distributed right-anteriorly, however, RN-BAV showed higher variable profiles with a main proximal-posterior distribution shifting anteriorly at mid-distal AAo. Compared to controls, BAV patients presented similar WSS magnitude at proximal, mid and distal AAo (p = 0.764, 0.516 and 0.053, respectively) but lower axial and higher circumferential WSS components (p < 0.001 for both, at all aortic levels). Among BAV patients, RN-BAV presented higher IRF at all levels (p = 0.024 proximal, 0.046 mid and 0.002 distal AAo) and higher circumferential WSS at mid and distal AAo (p = 0.038 and 0.046, respectively) than RL-BAV. However, axial WSS was higher in RL-BAV compared to RN-BAV at proximal and mid AAo (p = 0.046, 0.019, respectively). Displacement and axial WSS were independently associated with the root-morphotype, and circumferential WSS and SFRR with the ascending-morphotype. CONCLUSIONS: Different BAV-phenotypes present different flow patterns with an anterior distribution in RL-BAV, whereas, RN-BAV patients present a predominant posterior outflow jet at the sinotubular junction that shifts to anterior or right anterior in mid and distal AAo. Thus, RL-BAV patients present a higher axial WSS at the aortic root while RN-BAV present a higher circumferential WSS in mid and distal AAo. These results may explain different AAo dilatation morphotypes in the BAV population.

Gay and Gray Session: An Interdisciplinary Approach to Transgender Aging.

With the overarching goals of improving the healthcare of older transgender individuals and of inspiring pertinent clinical research, a session at the 2017 American Association for Geriatric Psychiatry Annual Meeting focused on an interdisciplinary approach to transgender aging. The older the transgender adult, the more likely the individual grew up in a historical context when there was greater social stigma towards their gender identity, even among mental health professionals. In order to provide optimal healthcare to transgender adults, mental health care providers should become familiar with the basic terminology presented in this article. Transgender older adults face greater risks of poor physical health, disability, anxiety and depressive symptoms, victimization, and stigma, and higher rates of smoking, excessive alcohol use, and risky sexual behavior compared with non-transgender older adults. In spite of notable health disparities, some evidence points to resilience among transgender older adults. The mental health professional often serves as the first contact for a patient who is struggling with gender identity. The role of a mental health professional can be divided into five categories: 1) assessment of gender dysphoria; 2) psychoeducation of patients and family members about the diversity of gender identities and various options for alleviating gender dysphoria; 3) referral to and collaboration with other healthcare professionals; 4) treatment of coexisting mental health concerns; 5) advocating for transgender patients and for the transgender community. Recently, the criteria for medical and surgical transition have been simplified. End-of-life preparations are especially important for transgender individuals.

Enhancing Health IT Functionality for Children: The 2015 Children's EHR Format.

Electronic health record (EHR) use throughout the United States has advanced considerably, but functionality to support the optimal care of children has been slower to develop and deploy. A previous team of experts systematically identified gaps in EHR functionality during collaborative work from 2010 to 2013 that produced the Children's EHR Format (Format), funded under the Children's Health Insurance Program Reauthorization Act of 2009, Public Law 111-3. After that, a team of practitioners, software developers, health policy leaders, and other stakeholders examined the Format's exhaustive list of 547 EHR functional requirements in 26 topic areas and found them to be valuable but in need of further refinement and prioritization. Work began in 2014 to develop a shortened high priority list of requirements and provide guidance to improve their use. Through a modified Delphi process that included key document review, selection criteria, multiple rounds of voting, and small group discussion, a multistakeholder work group identified and refined 47 items on the basis of earlier requirements to form the 2015 Children's EHR Format Priority List and developed 16 recommended uses of the Format. The full report of the Format enhancement activities is publicly available. In this article, we aim to promote awareness of these high priority EHR functional requirements for the care of children, sharpen industry focus on adopting these changes, and align all stakeholders in prioritizing specific health information technology functionalities including those essential for well-child preventive care, medication management, immunization tracking, and growth data for specific pediatric subgroups.

Mining 100 million notes to find homelessness and adverse childhood experiences: 2 case studies of rare and severe social determinants of health in electronic health records.

Objective: Understanding how to identify the social determinants of health from electronic health records (EHRs) could provide important insights to understand health or disease outcomes. We developed a methodology to capture 2 rare and severe social determinants of health, homelessness and adverse childhood experiences (ACEs), from a large EHR repository. Materials and Methods: We first constructed lexicons to capture homelessness and ACE phenotypic profiles. We employed word2vec and lexical associations to mine homelessness-related words. Next, using relevance feedback, we refined the 2 profiles with iterative searches over 100 million notes from the Vanderbilt EHR. Seven assessors manually reviewed the top-ranked results of 2544 patient visits relevant for homelessness and 1000 patients relevant for ACE. Results: word2vec yielded better performance (area under the precision-recall curve [AUPRC] of 0.94) than lexical associations (AUPRC = 0.83) for extracting homelessness-related words. A comparative study of searches for the 2 phenotypes revealed a higher performance achieved for homelessness (AUPRC = 0.95) than ACE (AUPRC = 0.79). A temporal analysis of the homeless population showed that the majority experienced chronic homelessness. Most ACE patients suffered sexual (70%) and/or physical (50.6%) abuse, with the top-ranked abuser keywords being "father" (21.8%) and "mother" (15.4%). Top prevalent associated conditions for homeless patients were lack of housing (62.8%) and tobacco use disorder (61.5%), while for ACE patients it was mental disorders (36.6%-47.6%). Conclusion: We provide an efficient solution for mining homelessness and ACE information from EHRs, which can facilitate large clinical and genetic studies of these social determinants of health.

Racial Disparities and Sociodemographic Differences in Incidence and Survival Among Pediatric Patients in the United States With Primary Liver Cancer: A Surveillance, Epidemiology, and End Results (SEER) Population Study.

BACKGROUND: Primary liver cancer, including Hepatoblastoma (HB) and hepatocellular carcinoma (HCC), in pediatric populations is often fatal. The outcomes are poor despite universal health care access in pediatric patients. AIM: We investigated the sociodemographic factors affecting outcomes in pediatric patients with primary liver cancer. MATERIALS AND METHODS: This is a large population database study of Surveillance, Epidemiology, and End Results cancer registry data from 1973 to 2011. HB and HCC were analyzed regarding age, sex, race, geographic area, and treatment-related information including survival. RESULTS: In total, 998 patients, the median age at time of diagnosis was 1 year for HB [0-19; 95% confidence interval (CI), 1.5-1.9] and 14 years for HCC (0-19; 95% CI, 12.1-13.3) (P<0.001). Overall Survival (OS) in HB was 374 months (25% failures 19) versus HCC 21 months (25% failures 5; P<0.0001). In HCC, the fibrolamellar subgroup OS was 41 months (32-.) versus 16 months (11-21) in all others [hazard ratio (HR) 2.0; P=0.005]. Diagnosis between 2000 and 2011 (HB: 25% failures not reached; HCC: 38) versus diagnosis 1973 to 1999 (HB: 374; HCC: 12) had different survival (P=0.01; HR 1.9). For HB, OS in patients with age of diagnosis under 2, 25% failures was not reached versus 374 months over the age of 2 (HR 1.7; P<0.0007). African American children with HB had OS of 67 (17-.) versus all others (25% failures 21) and 48% of African American children were diagnosed after the age of 2 versus 34% of whites (HR 1.9; P=0.01). CONCLUSIONS: Later diagnosis and decreased survival in African American children with HB warrants further research.

Four-dimensional flow magnetic resonance imaging and ultrasound assessment of cerebrospinal venous flow in multiple sclerosis patients and controls.

A possibly causal relationship between multiple sclerosis and chronic cerebrospinal venous insufficiency has recently been hypothesized. Studies investigating chronic cerebrospinal venous insufficiency have reported conflicting results and few have employed multiple diagnostic imaging modalities across a large patient and control population. In this study, three complementary imaging modalities were used to investigate the chronic cerebrospinal venous insufficiency hypothesis in patients with multiple sclerosis and two age- and sex-matched control groups: healthy volunteers and patients with other neurological diseases. Strictly blinded Doppler ultrasound according to the original chronic cerebrospinal venous insufficiency hypothesis; four-dimensional flow magnetic resonance imaging of venous flow in the head, neck, and chest; and contrast-enhanced magnetic resonance venography for neck and chest venous luminography were acquired. An internal jugular vein stenosis evaluation was also performed across modalities. Percentage of subjects meeting ultrasound-based chronic cerebrospinal venous insufficiency criteria was small and similar between groups. In group-wise and pairwise testing, no four-dimensional flow magnetic resonance imaging variables were statistically significantly different, for any measurement location. In contrast-enhanced magnetic resonance venography of the internal jugular and azygos veins, no statistically significant differences were observed in stenosis scores between groups. These results represent compelling evidence against the chronic cerebrospinal venous insufficiency hypothesis in multiple sclerosis.

ePrescribing: Reducing Costs through In-Class Therapeutic Interchange.

INTRODUCTION: Spending on pharmaceuticals in the US reached $373.9 billion in 2014. Therapeutic interchange offers potential medication cost savings by replacing a prescribed drug for an equally efficacious therapeutic alternative. METHODS: Hard-stop therapeutic interchange recommendation alerts were developed for four medication classes (HMG-CoA reductase inhibitors, serotonin receptor agonists, intranasal steroid sprays, and proton-pump inhibitors) in an electronic prescription-writing tool for outpatient prescriptions. Using prescription data from January 2012 to June 2015, the Compliance Ratio (CR) was calculated by dividing the number of prescriptions with recommended therapeutic interchange medications by the number of prescriptions with non-recommended medications to measure effectiveness. To explore potential cost savings, prescription data and medication costs were analyzed for the 45,000 Vanderbilt Employee Health Plan members. RESULTS: For all medication classes, significant improvements were demonstrated - the CR improved (proton-pump inhibitors 2.8 to 5.32, nasal steroids 2.44 to 8.16, statins 2.06 to 5.51, and serotonin receptor agonists 0.8 to 1.52). Quarterly savings through the four therapeutic interchange interventions combined exceeded $200,000 with an estimated annual savings for the health plan of $800,000, or more than $17 per member. CONCLUSION: A therapeutic interchange clinical decision support tool at the point of prescribing resulted in increased compliance with recommendations for outpatient prescriptions while producing substantial cost savings to the Vanderbilt Employee Health Plan - $17.77 per member per year. Therapeutic interchange rules require rational targeting, appropriate governance, and vigilant content updates.