The histone chaperones Vps75 and Nap1 form ring-like, tetrameric structures in solution.

NAP-1 fold histone chaperones play an important role in escorting histones to and from sites of nucleosome assembly and disassembly. The two NAP-1 fold histone chaperones in budding yeast, Vps75 and Nap1, have previously been crystalized in a characteristic homodimeric conformation. In this study, a combination of small angle X-ray scattering, multi angle light scattering and pulsed electron-electron double resonance approaches were used to show that both Vps75 and Nap1 adopt ring-shaped tetrameric conformations in solution. This suggests that the formation of homotetramers is a common feature of NAP-1 fold histone chaperones. The tetramerisation of NAP-1 fold histone chaperones may act to shield acidic surfaces in the absence of histone cargo thus providing a 'self-chaperoning' type mechanism.

Interactive visualization tool to understand and monitor health disparities in diabetes care and outcomes.

Objective: Type 2 diabetes (T2DM) poses a significant public health challenge, with pronounced disparities in control and outcomes. Social determinants of health (SDoH) significantly contribute to these disparities, affecting healthcare access, neighborhood environments, and social context. We discuss the design, development, and use of an innovative web-based application integrating real-world data (electronic health record and geospatial files), to enhance comprehension of the impact of SDoH on T2 DM health disparities. Methods: We identified a patient cohort with diabetes from the institutional Diabetes Registry (N = 67,699) within the Duke University Health System. Patient-level information (demographics, comorbidities, service utilization, laboratory results, and medications) was extracted to Tableau. Neighborhood-level socioeconomic status was assessed via the Area Deprivation Index (ADI), and geospatial files incorporated additional data related to points of interest (i.e., parks/green space). Interactive Tableau dashboards were developed to understand risk and contextual factors affecting diabetes management at the individual, group, neighborhood, and population levels. Results: The Tableau-powered digital health tool offers dynamic visualizations, identifying T2DM-related disparities. The dashboard allows for the exploration of contextual factors affecting diabetes management (e.g., food insecurity, built environment) and possesses capabilities to generate targeted patient lists for personalized diabetes care planning. Conclusion: As part of a broader health equity initiative, this application meets the needs of a diverse range of users. The interactive dashboard, incorporating clinical, sociodemographic, and environmental factors, enhances understanding at various levels and facilitates targeted interventions to address disparities in diabetes care and outcomes. Ultimately, this transformative approach aims to manage SDoH and improve patient care.

Development of an interactive dashboard for gun violence pattern analysis and intervention design at the local level.

Introduction: Gun violence remains a concerning and persistent issue in our country. Novel dashboards may integrate and summarize important clinical and non-clinical data that can inform targeted interventions to address the underlying causes of gun violence. Methods: Data from various clinical and non-clinical sources were sourced, cleaned, and integrated into a customizable dashboard that summarizes and provides insight into the underlying factors that impact local gun violence episodes. Results: The dashboards contained data from 7786 encounters and 1152 distinct patients from our Emergency Department's Trauma Registry with various patterns noted by the team. A multidisciplinary executive team, including subject matter experts in community-based interventions, epidemiology, and social sciences, was formed to design targeted interventions based on these observations. Conclusion: Targeted interventions to reduce gun violence require a multimodal data sourcing and standardization approach, the inclusion of neighborhood-level data, and a dedicated multidisciplinary team to act on the generated insights.

Predictive Modeling to Identify Children With Complex Health Needs At Risk for Hospitalization.

BACKGROUND: Identifying children at high risk with complex health needs (CCHN) who have intersecting medical and social needs is challenging. This study's objectives were to (1) develop and evaluate an electronic health record (EHR)-based clinical predictive model ("model") for identifying high-risk CCHN and (2) compare the model's performance as a clinical decision support (CDS) to other CDS tools available for identifying high-risk CCHN. METHODS: This retrospective cohort study included children aged 0 to 20 years with established care within a single health system. The model development/validation cohort included 33 months (January 1, 2016-September 30, 2018) and the testing cohort included 18 months (October 1, 2018-March 31, 2020) of EHR data. Machine learning methods generated a model that predicted probability (0%-100%) for hospitalization within 6 months. Model performance measures included sensitivity, positive predictive value, area under receiver-operator curve, and area under precision-recall curve. Three CDS rules for identifying high-risk CCHN were compared: (1) hospitalization probability ≥10% (model-predicted); (2) complex chronic disease classification (using Pediatric Medical Complexity Algorithm [PMCA]); and (3) previous high hospital utilization. RESULTS: Model development and testing cohorts included 116 799 and 27 087 patients, respectively. The model demonstrated area under receiver-operator curve = 0.79 and area under precision-recall curve = 0.13. PMCA had the highest sensitivity (52.4%) and classified the most children as high risk (17.3%). Positive predictive value of the model-based CDS rule (19%) was higher than CDS based on the PMCA (1.9%) and previous hospital utilization (15%). CONCLUSIONS: A novel EHR-based predictive model was developed and validated as a population-level CDS tool for identifying CCHN at high risk for future hospitalization.

Development and Performance of a Clinical Decision Support Tool to Inform Resource Utilization for Elective Operations.

Importance: Hospitals ceased most elective procedures during the height of coronavirus disease 2019 (COVID-19) infections. As hospitals begin to recommence elective procedures, it is necessary to have a means to assess how resource intensive a given case may be. Objective: To evaluate the development and performance of a clinical decision support tool to inform resource utilization for elective procedures. Design, Setting, and Participants: In this prognostic study, predictive modeling was used on retrospective electronic health records data from a large academic health system comprising 1 tertiary care hospital and 2 community hospitals of patients undergoing scheduled elective procedures from January 1, 2017, to March 1, 2020. Electronic health records data on case type, patient demographic characteristics, service utilization history, comorbidities, and medications were and abstracted and analyzed. Data were analyzed from April to June 2020. Main Outcomes and Measures: Predicitons of hospital length of stay, intensive care unit length of stay, need for mechanical ventilation, and need to be discharged to a skilled nursing facility. These predictions were generated using the random forests algorithm. Predicted probabilities were turned into risk classifications designed to give assessments of resource utilization risk. Results: Data from the electronic health records of 42 199 patients from 3 hospitals were abstracted for analysis. The median length of stay was 2.3 days (range, 1.3-4.2 days), 6416 patients (15.2%) were admitted to the intensive care unit, 1624 (3.8%) received mechanical ventilation, and 2843 (6.7%) were discharged to a skilled nursing facility. Predictive performance was strong with an area under the receiver operator characteristic ranging from 0.76 to 0.93. Sensitivity of the high-risk and medium-risk groupings was set at 95%. The negative predictive value of the low-risk grouping was 99%. We integrated the models into a daily refreshing Tableau dashboard to guide decision-making. Conclusions and Relevance: The clinical decision support tool is currently being used by surgical leadership to inform case scheduling. This work shows the importance of a learning health care environment in surgical care, using quantitative modeling to guide decision-making.

Identified themes of interactive visualizations overlayed onto EHR data: an example of improving birth center operating room efficiency.

OBJECTIVE: While electronic health record (EHR) systems store copious amounts of patient data, aggregating those data across patients can be challenging. Visual analytic tools that integrate with EHR systems allow clinicians to gain better insight and understanding into clinical care and management. We report on our experience building Tableau-based visualizations and integrating them into our EHR system. MATERIALS AND METHODS: Visual analytic tools were created as part of 12 clinician-initiated quality improvement projects. We built the visual analytic tools in Tableau and linked it within our EPIC environment. We identified 5 visual themes that spanned the various projects. To illustrate these themes, we choose 1 exemplary project which aimed to improve obstetric operating room efficiency. RESULTS: Across our 12 projects, we identified 5 visual themes that are integral to project success: scheduling & optimization (in 11/12 projects); provider assessment (10/12); executive assessment (8/12); patient outcomes (7/12); and control and goal charts (2/12). DISCUSSION: Many visualizations share common themes. Identification of these themes has allowed our internal team to be more efficient and directed in developing visualizations for future projects. CONCLUSION: Organizing visual analytics into themes can allow informatics teams to more efficiently provide visual products to clinical collaborators.

Triage of patients with venous and lymphatic diseases during the COVID-19 pandemic - The Venous and Lymphatic Triage and Acuity Scale (VELTAS) : A consensus document of the International Union of Phlebology (UIP), Australasian College of Phlebology (ACP), American Vein and Lymphatic Society (AVLS), American Venous Forum (AVF), European College of Phlebology (ECoP), European Venous Forum (EVF), Interventional Radiology Society of Australasia (IRSA), Latin American Venous Forum, Pan-American Society of Phlebology and Lymphology and the Venous Association of India (VAI) This consensus document has been co-published in Phlebology [DOI: 10.1177/0268355520930884] and Journal of Vascular Surgery: Venous and Lymphatic Disorders [DOI: 10.1016/j.jvsv.2020.05.002]. The publications are identical except for minor stylistic and spelling differences in keeping with each journal's style. The contribution has been published under a Attribution-Non Commercial-No Derivatives 4.0 International (CC BY-NC-ND 4.0), (https://creativecommons.org/licenses/by-nc-nd/4.0/).

The coronavirus disease 2019 (COVID-19) global pandemic has resulted in diversion of healthcare resources to the management of patients infected with SARS-CoV-2 virus. Elective interventions and surgical procedures in most countries have been postponed and operating room resources have been diverted to manage the pandemic. The Venous and Lymphatic Triage and Acuity Scale was developed to provide an international standard to rationalise and harmonise the management of patients with venous and lymphatic disorders or vascular anomalies. Triage urgency was determined based on clinical assessment of urgency with which a patient would require medical treatment or surgical intervention. Clinical conditions were classified into six categories of: (1) venous thromboembolism (VTE), (2) chronic venous disease, (3) vascular anomalies, (4) venous trauma, (5) venous compression and (6) lymphatic disease. Triage urgency was categorised into four groups and individual conditions were allocated to each class of triage. These included (1) medical emergencies (requiring immediate attendance), example massive pulmonary embolism; (2) urgent (to be seen as soon as possible), example deep vein thrombosis; (3) semi-urgent (to be attended to within 30-90 days), example highly symptomatic chronic venous disease, and (4) discretionary/non-urgent- (to be seen within 6-12 months), example chronic lymphoedema. Venous and Lymphatic Triage and Acuity Scale aims to standardise the triage of patients with venous and lymphatic disease or vascular anomalies by providing an international consensus-based classification of clinical categories and triage urgency. The scale may be used during pandemics such as the current COVID-19 crisis but may also be used as a general framework to classify urgency of the listed conditions.

Triage of patients with venous and lymphatic diseases during the COVID-19 pandemic - The Venous and Lymphatic Triage and Acuity Scale (VELTAS):: A consensus document of the International Union of Phlebology (UIP), Australasian College of Phlebology (ACP), American Vein and Lymphatic Society (AVLS), American Venous Forum (AVF), European College of Phlebology (ECoP), European Venous Forum (EVF), Interventional Radiology Society of Australasia (IRSA), Latin American Venous Forum, Pan-American Society of Phlebology and Lymphology and the Venous Association of India (VAI).

The coronavirus disease 2019 (COVID-19) global pandemic has resulted in diversion of healthcare resources to the management of patients infected with SARS-CoV-2 virus. Elective interventions and surgical procedures in most countries have been postponed and operating room resources have been diverted to manage the pandemic. The Venous and Lymphatic Triage and Acuity Scale was developed to provide an international standard to rationalise and harmonise the management of patients with venous and lymphatic disorders or vascular anomalies. Triage urgency was determined based on clinical assessment of urgency with which a patient would require medical treatment or surgical intervention. Clinical conditions were classified into six categories of: (1) venous thromboembolism (VTE), (2) chronic venous disease, (3) vascular anomalies, (4) venous trauma, (5) venous compression and (6) lymphatic disease. Triage urgency was categorised into four groups and individual conditions were allocated to each class of triage. These included (1) medical emergencies (requiring immediate attendance), example massive pulmonary embolism; (2) urgent (to be seen as soon as possible), example deep vein thrombosis; (3) semiurgent (to be attended to within 30-90 days), example highly symptomatic chronic venous disease, and (4) discretionary/nonurgent- (to be seen within 6-12 months), example chronic lymphoedema. Venous and Lymphatic Triage and Acuity Scale aims to standardise the triage of patients with venous and lymphatic disease or vascular anomalies by providing an international consensus-based classification of clinical categories and triage urgency. The scale may be used during pandemics such as the current COVID-19 crisis but may also be used as a general framework to classify urgency of the listed conditions.

From CBA to Precautionary Appraisal: Practical Responses to Intractable Problems.

The purpose of this essay is to critically review the design of methods for ethically robust forms of technology appraisal in the regulation of research and innovation in synthetic biology. It will focus, in particular, on the extent to which cost-benefit analysis offers a basis for informing decisions about which technological pathways to pursue and which to discourage. A further goal is to consider what (if anything) the precautionary principle might offer in enabling better decisions. And this, in turn, raises questions about why mention of precaution can excite accusations of unscientific bias or irrational, "anti-innovation" extremism. What does the polarized debate tell us about the politics around synthetic biology? In seeking more rigorous, timely, and practical ways to govern these remarkable new technologies, what might we be missing? The sophistication, diversity, and scope of synthetic biology may seem to make it a rather idiosyncratic area for exploring these general issues. It may seem to be a special case, with the bewildering pace of change amplifying the difficulties. But at root, some of the trickiest issues are just specific instances of familiar and long-standing conundrums in the governance of science and technology. The basic challenge is how to weigh up, for a wide range of potential options, the various pros and cons, as viewed from divergent perspectives, and find a way to justify the best course of action on behalf of society as a whole. This is the central problem addressed by a number of techniques in CBA. On the face of it, synthetic biology seems to present just one more application of these well-established and self-confident prescriptive methods. But there do emerge several obstinate, even prohibitive, difficulties for CBA. Although they are well acknowledged by the scholarly literature on and around this topic, they are often sidelined in practice. Yet all are central to the case for applying the concept of precaution to a field like synthetic biology. This essay will briefly explore multicriteria mapping, an appraisal method for exploring contrasting perspectives on emerging technologies, as one practical way to address them. The essay focuses on MCM, not because it presents any sort of panacea for appraisal, but because it is illustrative of the concrete implications of precaution. Setting out even just one among potentially many practical alternative methods at least refutes the last-ditch argument that CBA is the only operational choice.

Towards inclusive social appraisal: risk, participation and democracy in governance of synthetic biology.

Frameworks that govern the development and application of novel products, such as the products of synthetic biology, should involve all those who are interested or potentially affected by the products. The governance arrangements for novel products should also provide a democratic mechanism that allows affected parties to express their opinions on the direction that innovation does or does not take. In this paper we examine rationales, obstacles and opportunities for public participation in governance of novel synthetic biology products. Our analysis addresses issues such as uncertainties, the considering of alternative innovations, and broader social and environmental implications. The crucial issues in play go beyond safety alone, to include contending social values around diverse notions of benefit and harm. The paper highlights the need for more inclusive social appraisal mechanisms to inform governance of Synthetic Biology and alternative products, and discusses a few practical methods to help achieve this goal.