Impact of financial compensation on enrollment and participation in a remote, mobile-app based research study.

Background: There is no consensus on how to determine appropriate financial compensation for research recruitment. Selecting incentive amounts that are reasonable and respectful, without undue inducement, remains challenging. Previously, we demonstrated that incentive amount significantly impacts participants' willingness to complete various hypothetical research activities. Here we further explore this relationship in a mock decentralized study. Methods: Adult ResearchMatch volunteers were invited to join a prospective study where interested individuals were given an opportunity to view details for a study along with participation requirements, then offered a randomly generated compensation amount between $0 and $50 to enroll and participate. Individuals agreeing to participate were then asked to complete tasks using a remote mobile application (MyCap), for two weeks. Tasks included a weekly survey, a daily gratitude journal and daily phone tapping task. Results: Willingness to participate was 85% across all incentive levels but not significantly impacted by amount. Task completion appeared to increase as a function of compensation until a plateau at $25. While participants described the study as low burden and reported that compensation was moderately important to their decision to join, only 31% completed all study tasks. Conclusion: While offering compensation in this study did not have a strong effect on enrollment rate, this work provides insight into participant motivation when joining and participating in studies employing mobile applications.

Identifying and Extracting Rare Diseases and Their Phenotypes with Large Language Models.

Purpose: Phenotyping is critical for informing rare disease diagnosis and treatment, but disease phenotypes are often embedded in unstructured text. While natural language processing (NLP) can automate extraction, a major bottleneck is developing annotated corpora. Recently, prompt learning with large language models (LLMs) has been shown to lead to generalizable results without any (zero-shot) or few annotated samples (few-shot), but none have explored this for rare diseases. Our work is the first to study prompt learning for identifying and extracting rare disease phenotypes in the zero- and few-shot settings. Methods: We compared the performance of prompt learning with ChatGPT and fine-tuning with BioClinicalBERT. We engineered novel prompts for ChatGPT to identify and extract rare diseases and their phenotypes (e.g., diseases, symptoms, and signs), established a benchmark for evaluating its performance, and conducted an in-depth error analysis. Results: Overall, fine-tuning BioClinicalBERT resulted in higher performance (F1 of 0.689) than ChatGPT (F1 of 0.472 and 0.610 in the zero- and few-shot settings, respectively). However, ChatGPT achieved higher accuracy for rare diseases and signs in the one-shot setting (F1 of 0.778 and 0.725). Conversational, sentence-based prompts generally achieved higher accuracy than structured lists. Conclusion: Prompt learning using ChatGPT has the potential to match or outperform fine-tuning BioClinicalBERT at extracting rare diseases and signs with just one annotated sample. Given its accessibility, ChatGPT could be leveraged to extract these entities without relying on a large, annotated corpus. While LLMs can support rare disease phenotyping, researchers should critically evaluate model outputs to ensure phenotyping accuracy.

Empowering the Participant Voice (EPV): Design and implementation of collaborative infrastructure to collect research participant experience feedback at scale.

Empowering the Participant Voice (EPV) is an NCATS-funded six-CTSA collaboration to develop, demonstrate, and disseminate a low-cost infrastructure for collecting timely feedback from research participants, fostering trust, and providing data for improving clinical translational research. EPV leverages the validated Research Participant Perception Survey (RPPS) and the popular REDCap electronic data-capture platform. This report describes the development of infrastructure designed to overcome identified institutional barriers to routinely collecting participant feedback using RPPS and demonstration use cases. Sites engaged local stakeholders iteratively, incorporating feedback about anticipated value and potential concerns into project design. The team defined common standards and operations, developed software, and produced a detailed planning and implementation Guide. By May 2023, 2,575 participants diverse in age, race, ethnicity, and sex had responded to approximately 13,850 survey invitations (18.6%); 29% of responses included free-text comments. EPV infrastructure enabled sites to routinely access local and multi-site research participant experience data on an interactive analytics dashboard. The EPV learning collaborative continues to test initiatives to improve survey reach and optimize infrastructure and process. Broad uptake of EPV will expand the evidence base, enable hypothesis generation, and drive research-on-research locally and nationally to enhance the clinical research enterprise.

ResearchMatch on FHIR: Development and evaluation of a recruitment registry and electronic health record system interface for volunteer profile completion.

Background: Obtaining complete and accurate information in recruitment registries is essential for matching potential participants to research studies for which they qualify. Since electronic health record (EHR) systems are required to make patient data available to external systems, an interface between EHRs and recruitment registries may improve accuracy and completeness of volunteers' profiles. We tested this hypothesis on ResearchMatch (RM), a disease- and institution-neutral recruitment registry with 1357 studies across 255 institutions. Methods: We developed an interface where volunteers signing up for RM can authorize transfer of demographic data, medical conditions, and medications from the EHR into a registration form. We obtained feedback from a panel of community members to determine acceptability of the planned integration. We then developed the EHR interface and performed an evaluation study of 100 patients to determine whether RM profiles generated with EHR-assisted adjudication included more conditions and medications than those without the EHR connection. Results: Community member feedback revealed that members of the public were willing to authenticate into the EHR from RM with proper messaging about choice and privacy. The evaluation study showed that out of 100 participants, 75 included more conditions and 69 included more medications in RM profiles completed with the EHR connection than those without. Participants also completed the EHR-connected profiles in 16 fewer seconds than non-EHR-connected profiles. Conclusions: The EHR to RM integration could lead to more complete profiles, less participant burden, and better study matches for many of the over 148,000 volunteers who participate in ResearchMatch.

Elevating nucleic acid delivery via a stable anionic peptide-dextran ternary system.

Nucleic acid-based therapies hold promise for treating previously intractable diseases but require effective delivery vectors to protect the therapeutic agents and ensure efficient transfection. Cationic polymeric vectors are particularly notable for their adaptability, high transfection efficiency, and low cost, but their positive charge often attracts blood proteins, causing aggregation and reduced transfection efficiency. Addressing this, we designed an anionic peptide-grafted dextran (Dex-LipE5H) to serve as a cross-linkable coating to bolster the stability of cationic polymer/nucleic acid complexes. The Dex-LipE5H was synthesized through a Michael addition reaction, combining an anionic peptide (LipE5H) with dextran modified by divinyl sulfone. We demonstrated Dex-lipE5H utility in a novel ternary nucleic acid delivery system, CDex-LipE5H/PEI/nucleic acid. CDex-LipE5H/PEI/nucleic acid demonstrated lower cytotoxicity and superior anti-protein absorption ability compared to PEI/pDNA and Dex-LipE5H/PEI/pDNA. Most notably, the crosslinked CDex-LipE5H/PEI/pDNA demonstrated remarkable transfection performance in HepG2 cells, which poses significant transfection challenges, even in a medium with 20% serum. This system's effective siRNA interference performance was further validated through a PCSK9 gene knockdown assay. This investigation provides novel insights and contributes to the design of cost-effective, next-generation nucleic acid delivery systems with enhanced blood stability and transfection efficiency.

Toroidal-spiral particles as a CAR-T cell delivery device for solid tumor immunotherapy.

Chimeric antigen receptor (CAR) T cell therapy has resulted in positive effects on patients with hematologic malignancy but shows limited efficacy in solid tumor treatments due to insufficient trafficking and tumor infiltration, intensive CAR-T-related toxicities, and antigen escape. In this work, we developed and investigated a biodegradable and biocompatible polymeric toroidal-spiral particle (TSP) as a in vivo cell incubator and delivery device that can be implanted near tumor through a minimally invasive procedure or injected near or into solid tumors by using a biopsy needle. The main matrix structure of the millimeter-sized TSP is made from crosslinking of gelatin methacrylamine (GelMA) and poly (ethylene glycol) diacrylate (PEGDA) with a tunable degradation rate from a few days to months, providing appropriate mechanical properties and sustained release of co-encapsulated drugs and/or stimulation compounds. The toroidal-spiral layer of the particles, presenting an internal void volume for high-capacity cell loading and flexibility of co-encapsulating small and large molecular compounds with individually manipulated release schedules, is filled with collagen and suspended T cells. The TSPs promote cell proliferation, activation, and migration in the tumor micro-environment in a prolonged and sustained manner. In this study, the efficacy of mesothelin (MSLN) CAR-T cells released from the TSPs was tested in preclinical mouse tumor models. Compared to systemic and intratumoral injection, peritumoral delivery of MSLN CAR-T cells using the TSPs resulted in a superior antitumor effect. The TSPs made of FDA approved materials as an in vivo reactor may provide an option for efficiently local delivery of CAR-T cells to solid tumors for higher efficacy and lower toxicity, with a minimally invasive administration procedure.

Simple Bioparticle Filtration Device Based on an Ultralow-Fouling Zwitterionic Polyurethane Membrane for Rapid Large-Volume Separation of Plasma and Viruses from Whole Blood.

Plasma separation from whole blood is oftent required as an essential first step when performing blood tests with a viral assay. However, developing a point-of-care plasma extraction device with a large output and high virus recovery remains a significant obstacle to the success of on-site viral load tests. Here, we report a portable, easy-to-use, cost-efficient, membrane-filtration-based plasma separation device that enables rapid large-volume plasma extraction from whole blood, designed for point-of-care virus assays. The plasma separation is realized by a low-fouling zwitterionic polyurethane-modified cellulose acetate (PCBU-CA) membrane. The zwitterionic coating on the cellulose acetate membrane can decrease surface protein adsorption by 60% and increase plasma permeation by 46% compared with a pristine membrane. The PCBU-CA membrane, with its ultralow-fouling properties, enables rapid plasma separation. The device can yield a total of 1.33 mL plasma from 10 mL whole blood in 10 min. The extracted plasma is cell-free and exhibits a low hemoglobin level. In addition, our device demonstrated a 57.8% T7 phage recovery in the separated plasma. The results of real-time polymerase chain reaction analysis confirmed that the nucleic acid amplification curve of the plasma extracted by our device is comparable to that obtained by centrifugation. With its high plasma yield and good phage recovery, our plasma separation device provides an excellent replacement for traditional plasma separation protocols for point-of-care virus assays and a broad spectrum of clinical tests.

Evaluating automated electronic case report form data entry from electronic health records.

Background: Many clinical trials leverage real-world data. Typically, these data are manually abstracted from electronic health records (EHRs) and entered into electronic case report forms (CRFs), a time and labor-intensive process that is also error-prone and may miss information. Automated transfer of data from EHRs to eCRFs has the potential to reduce data abstraction and entry burden as well as improve data quality and safety. Methods: We conducted a test of automated EHR-to-CRF data transfer for 40 participants in a clinical trial of hospitalized COVID-19 patients. We determined which coordinator-entered data could be automated from the EHR (coverage), and the frequency with which the values from the automated EHR feed and values entered by study personnel for the actual study matched exactly (concordance). Results: The automated EHR feed populated 10,081/11,952 (84%) coordinator-completed values. For fields where both the automation and study personnel provided data, the values matched exactly 89% of the time. Highest concordance was for daily lab results (94%), which also required the most personnel resources (30 minutes per participant). In a detailed analysis of 196 instances where personnel and automation entered values differed, both a study coordinator and a data analyst agreed that 152 (78%) instances were a result of data entry error. Conclusions: An automated EHR feed has the potential to significantly decrease study personnel effort while improving the accuracy of CRF data.

Clinical Assessment of Low Calcium In traUMa (CALCIUM).

Major trauma frequently occurs in the deployed, combat setting and is especially applicable in the recent conflicts with explosives dominating the combat wounded. In future near-peer conflicts, we will likely face even more profound weapons including mortars and artillery. As such, the number of severely wounded will likely increase. Hypocalcemia frequently occurs after blood transfusions, secondary to the preservatives in the blood products; however, recent data suggests major trauma in and of itself is a risk factor for hypocalcemia. Calcium is a major ion involved in heart contractility; thus, hypocalcemia can lead to poor contractility. Smaller studies have linked hypocalcemia to worse outcomes, but it remains unclear what causes hypocalcemia and if intervening could potentially save lives. The objective of this study is to determine the incidence of hypocalcemia on hospital arrival and the association with survival. We are seeking to address the following scientific questions, (1) Is hypocalcemia present following traumatic injury prior to transfusion during resuscitation? (2) Does hypocalcemia influence the amount of blood products transfused? (3) To what extent is hypocalcemia further exacerbated by transfusion? (4) What is the relationship between hypocalcemia following traumatic injury and mortality? We will conduct a multicenter, prospective, observational study. We will gather ionized calcium levels at 0, 3, 6, 12, 18, and 24 hours as part of scheduled calcium measurements. This will ensure we have accurate data to assess the early and late effects of hypocalcemia throughout the course of resuscitation and hemorrhage control. These data will be captured by a trained study team at every site. Our findings will inform clinical practice guidelines and optimize the care delivered in the combat and civilian trauma setting. We are seeking 391 patients with complete data to meet our a priori inclusion criteria. Our study will have major immediate short-term findings including risk prediction modeling to assess who is at risk for hypocalcemia, data assessing interventions associated with the incidence of hypocalcemia, and outcome data including mortality and its link to early hypocalcemia.

HL7 FHIR-based tools and initiatives to support clinical research: a scoping review.

OBJECTIVES: The HL7® fast healthcare interoperability resources (FHIR®) specification has emerged as the leading interoperability standard for the exchange of healthcare data. We conducted a scoping review to identify trends and gaps in the use of FHIR for clinical research. MATERIALS AND METHODS: We reviewed published literature, federally funded project databases, application websites, and other sources to discover FHIR-based papers, projects, and tools (collectively, "FHIR projects") available to support clinical research activities. RESULTS: Our search identified 203 different FHIR projects applicable to clinical research. Most were associated with preparations to conduct research, such as data mapping to and from FHIR formats (n = 66, 32.5%) and managing ontologies with FHIR (n = 30, 14.8%), or post-study data activities, such as sharing data using repositories or registries (n = 24, 11.8%), general research data sharing (n = 23, 11.3%), and management of genomic data (n = 21, 10.3%). With the exception of phenotyping (n = 19, 9.4%), fewer FHIR-based projects focused on needs within the clinical research process itself. DISCUSSION: Funding and usage of FHIR-enabled solutions for research are expanding, but most projects appear focused on establishing data pipelines and linking clinical systems such as electronic health records, patient-facing data systems, and registries, possibly due to the relative newness of FHIR and the incentives for FHIR integration in health information systems. Fewer FHIR projects were associated with research-only activities. CONCLUSION: The FHIR standard is becoming an essential component of the clinical research enterprise. To develop FHIR's full potential for clinical research, funding and operational stakeholders should address gaps in FHIR-based research tools and methods.

Risk factors for hippocampal cavities in a marginally housed population.

Cavities in the hippocampus are morphological variants of uncertain significance. Aberrant neurodevelopment along with vascular and inflammatory etiologies have been proposed. We sought to characterize these cavities and their potential risk factors in a marginally housed population, with high rates of viral infection, addiction, and mental illness. (1) The volume of hippocampal cavities (HCavs) is greater in this highly multimorbid population compared to the general population. (2) Conventional vascular risk factors such as greater age and systolic blood pressure are associated with higher HCav volume. (3) Nonprescribed substance-related risk factors such as stimulant use or dependence, and smoking are associated with increased HCav volume independent of vascular risk factors. This is a retrospective analysis of an ongoing prospective study. We analyzed baseline data, including medical history, physical exam, psychiatric diagnosis, and MRI from a total of 375 participants. Hippocampal cavities were defined as spaces isointense to CSF on T1 MRI sequences, bounded on all sides by hippocampal tissue, with a volume of at least 1 mm3 . Risk factors were evaluated using negative binomial multiple regression. Stimulant use was reported by 87.3% of participants, with stimulant dependence diagnosed in 83.3% of participants. Prevalence of cavities was 71.6%, with a mean total bilateral HCav volume of 13.89 mm3 . On average, a 1 mmHg greater systolic blood pressure was associated with a 2.17% greater total HCav volume (95% CI = [0.57%, 3.79%], p = .0076), while each cigarette smoked per day trended toward a 2.69% greater total HCav volume (95% CI = [-0.87%, 5.54%], p = .058). A diagnosis of stimulant dependence was associated with a 95.6% greater total HCav volume (95% CI = [5.39%, 263.19%], p = .0335). Hypertension and diagnosis of stimulant dependence were associated with a greater total volume of HCav.

MyCap: a flexible and configurable platform for mobilizing the participant voice.

This paper provides a description of the MyCap data collection platform, utilization metrics, and vignettes associated with use from diverse research institutions. MyCap is a participant-facing mobile application for survey data collection and the automated administration of active tasks (activities performed by participants using mobile device sensors under semi-controlled conditions). Launched in 2018, MyCap is a no-code solution for research teams conducting longitudinal studies, integrates tightly with REDCap and is available at no cost to research teams at academic, nonprofit, or government organizations. MyCap has been deployed at multiple research institutions with application usage logged across 135 countries in 2021. Vignettes demonstrate that MyCap empowered research teams to explore and implement novel methods of information collection and use. MyCap's integration with REDCap provides a comprehensive data collection ecosystem and is best suited for longitudinal studies with frequent requests for information from participants.

Identification of a promiscuous conserved CTL epitope within the SARS-CoV-2 spike protein.

ABSTRACTThe COVID-19 disease caused by infection with SARS-CoV-2 and its variants is devastating to the global public health and economy. To date, over a hundred COVID-19 vaccines are known to be under development, and the few that have been approved to fight the disease are using the spike protein as the primary target antigen. Although virus-neutralizing epitopes are mainly located within the RBD of the spike protein, the presence of T cell epitopes, particularly the CTL epitopes that are likely to be needed for killing infected cells, has received comparatively little attention. This study predicted several potential T cell epitopes with web-based analytic tools and narrowed them down from several potential MHC-I and MHC-II epitopes by ELIspot and cytolytic assays to a conserved MHC-I epitope. The epitope is highly conserved in current viral variants and compatible with a presentation by most HLA alleles worldwide. In conclusion, we identified a CTL epitope suitable for evaluating the CD8+ T cell-mediated cellular response and potentially for addition into future COVID-19 vaccine candidates to maximize CTL responses against SARS-CoV-2.

Comparison of Wild Type DNA Sequence of Spike Protein from SARS-CoV-2 with Optimized Sequence on The Induction of Protective Responses Against SARS-Cov-2 Challenge in Mouse Model.

Genetic optimization of Nucleic Acid immunogens is important for potentially improving their immune potency. A COVID-19 DNA vaccine is in phase III clinical trial which is based on a promising highly developable technology platform. Here, we show optimization in mice generating a pGX-9501 DNA vaccine encoding full-length spike protein, which results in induction of potent humoral and cellular immune responses, including neutralizing antibodies, that block hACE2-RBD binding of live CoV2 virus in vitro. Optimization resulted in improved induction of cellular immunity by pGX-9501 as demonstrated by increased IFN-γ expression in both CD8+ and CD4 + T cells and this was associated with more robust antiviral CTL responses compared to unoptimized constructs. Vaccination with pGX-9501 induced subsequent protection against virus challenge in a rigorous hACE2 transgenic mouse model. Overall, pGX-9501 is a promising optimized COVID-19 DNA vaccine candidate inducing humoral and cellular immunity contributing to the vaccine's protective effects.

Development and implementation of the National Heart, Lung, and Blood Institute COVID-19 common data elements.

Background: Coronavirus Disease 2019 (COVID-19) instigated a flurry of clinical research activity. The unprecedented pace with which trials were launched left an early void in data standardization, limiting the potential for subsequent data pooling. To facilitate data standardization across emerging studies, the National Heart, Lung, and Blood Institute (NHLBI) charged two groups with harmonizing data collection, and these groups collaborated to create a concise set of COVID-19 Common Data Elements (CDEs) for clinical research. Methods: Our iterative approach followed three guiding principles: 1) draw from existing multi-center COVID-19 clinical trials as precedents, 2) incorporate existing data elements and data standards whenever possible, and 3) alignment to data standards that facilitate data sharing and regulatory submission. We also supported rapid implementation of the CDEs in NHLBI-funded studies and iteratively refined the CDEs based on feedback from those study teams. Results: The NHLBI COVID-19 CDEs are publicly available and being used for current COVID-19 clinical trials. CDEs are organized into domains, and each data element is classified within a three-tiered prioritization system. The CDE manual is hosted publicly at https://nhlbi-connects.org/common_data_elements with an accompanying data dictionary and implementation guidance. Conclusions: The NHLBI COVID-19 CDEs are designed to aid data harmonization across studies to achieve the benefits of pooled analyses. We found that organizing CDE development around our three guiding principles focused our efforts and allowed us to adapt as COVID-19 knowledge advanced. As these CDEs continue to evolve, they could be generalized for use in other acute respiratory illnesses.

Dynamic networks of psychotic symptoms in adults living in precarious housing or homelessness.

BACKGROUND: People living in precarious housing or homelessness have higher than expected rates of psychotic disorders, persistent psychotic symptoms, and premature mortality. Psychotic symptoms can be modeled as a complex dynamic system, allowing assessment of roles for risk factors in symptom development, persistence, and contribution to premature mortality. METHOD: The severity of delusions, conceptual disorganization, hallucinations, suspiciousness, and unusual thought content was rated monthly over 5 years in a community sample of precariously housed/homeless adults (n = 375) in Vancouver, Canada. Multilevel vector auto-regression analysis was used to construct temporal, contemporaneous, and between-person symptom networks. Network measures were compared between participants with (n = 219) or without (n = 156) history of psychotic disorder using bootstrap and permutation analyses. Relationships between network connectivity and risk factors including homelessness, trauma, and substance dependence were estimated by multiple linear regression. The contribution of network measures to premature mortality was estimated by Cox proportional hazard models. RESULTS: Delusions and unusual thought content were central symptoms in the multilevel network. Each psychotic symptom was positively reinforcing over time, an effect most pronounced in participants with a history of psychotic disorder. Global connectivity was similar between those with and without such a history. Greater connectivity between symptoms was associated with methamphetamine dependence and past trauma exposure. Auto-regressive connectivity was associated with premature mortality in participants under age 55. CONCLUSIONS: Past and current experiences contribute to the severity and dynamic relationships between psychotic symptoms. Interrupting the self-perpetuating severity of psychotic symptoms in a vulnerable group of people could contribute to reducing premature mortality.

Making Clinical Data Acquisition Standards Harmonization (CDASH) Electronic Case Report Forms Available on the REDCap Shared Data Instrument Library.

Introduction: A guiding principle behind the development and deployment of the REDCap data management platform has always included attention to workflow design that allows easy implementation of best practices for clinical and translational researchers. CDISC standards such as CDASH have helped the clinical research community improve the efficiency, actionability, and quality of their clinical trials data, but have had limited uptake among the academic institutions. Objective: To create a scalable methodology to convert CDISC CDASH eCRF instrument metadata into REDCap data dictionaries for the purpose of simplifying adoption and use of CDASH instruments by research teams across the REDCap Consortium. Implementation: We have used our replicable methods to translate metadata from 34 CDASH Foundational eCRFs and 20 CDASH Crohn's Disease eCRFs into REDCap eCRF metadata and have made these instruments available in the REDCap Shared Data Instrument Library for widespread sharing and uptake across the REDCap Consortium. Users can import the standardized eCRFs directly into their REDCap projects for immediate use in clinical trial data collection. Conclusion: Disseminating CDISC standards through the REDCap community will increase the accessibility of these standards for academic medical centers. Having academic clinical researchers using CDISC standards may lead to more research datasets that interoperate with pharmaceutical sponsored trials, and more discoveries from secondary use of clinical research data.

Follow-up Interactive Long-Term Expert Ranking (FILTER): a crowdsourcing platform to adjudicate risk for survivorship care.

OBJECTIVES: To develop an online crowdsourcing platform where oncologists and other survivorship experts can adjudicate risk for complications in follow-up. MATERIALS AND METHODS: This platform, called Follow-up Interactive Long-Term Expert Ranking (FILTER), prompts participants to adjudicate risk between each of a series of pairs of synthetic cases. The Elo ranking algorithm is used to assign relative risk to each synthetic case. RESULTS: The FILTER application is currently live and implemented as a web application deployed on the cloud. DISCUSSION: While guidelines for following cancer survivors exist, refinement of survivorship care based on risk for complications after active treatment could improve both allocation of resources and individual outcomes in long-term follow-up. CONCLUSION: FILTER provides a means for a large number of experts to adjudicate risk for survivorship complications with a low barrier of entry.

A multicenter cluster randomized, stepped wedge implementation trial for targeted normoxia in critically ill trauma patients: study protocol and statistical analysis plan for the Strategy to Avoid Excessive Oxygen (SAVE-O2) trial.

BACKGROUND: Targeted normoxia (SpO2 90-96% or PaO2 60-100 mmHg) may help to conserve oxygen and improve outcomes in critically ill patients by avoiding potentially harmful hyperoxia. However, the role of normoxia for critically ill trauma patients remains uncertain. The objective of this study is to describe the study protocol and statistical analysis plan for the Strategy to Avoid Excessive Oxygen for Critically Ill Trauma Patients (SAVE-O2) clinical trial. METHODS: Design, setting, and participants: Protocol for a multicenter cluster randomized, stepped wedge implementation trial evaluating the effectiveness of a multimodal intervention to target normoxia in critically ill trauma patients at eight level 1 trauma centers in the USA. Each hospital will contribute pre-implementation (control) and post-implementation (intervention) data. All sites will begin in the control phase with usual care. When sites reach their randomly assigned time to transition, there will be a one-month training period, which does not contribute to data collection. Following the 1-month training period, the site will remain in the intervention phase for the duration of the trial. MAIN OUTCOME MEASURES: The primary outcome will be supplemental oxygen-free days, defined as the number of days alive and not on supplemental oxygen. Secondary outcomes include in-hospital mortality to day 90, hospital-free days to day 90, ventilator-free days (VFD) to day 28, time to room air, Glasgow Outcome Score (GOS), and duration of time receiving supplemental oxygen. DISCUSSION: SAVE-O2 will determine if a multimodal intervention to improve compliance with targeted normoxia will safely reduce the need for concentrated oxygen for critically injured trauma patients. These data will inform military stakeholders regarding oxygen requirements for critically injured warfighters, while reducing logistical burden in prolonged combat casualty care. TRIAL REGISTRATION: ClinicalTrials.gov NCT04534959 . Registered September 1, 2020.

Breast Cancer Disparities Through the Lens of the COVID-19 Pandemic.

Purpose of Review: The emergency medicine and critical care needs of the COVID-19 pandemic forced a sudden and dramatic disruption of cancer screening and treatment programs in the USA during the winter and spring of 2020. This review commentary addresses the impact of the pandemic on racial/ethnic minorities such as African Americans and Hispanic-Latina Americans, with a focus on factors related to breast cancer. Recent Findings: African Americans and Hispanic-Latina Americans experienced disproportionately higher morbidity and mortality from COVID-19; many of the same socioeconomic and tumor biology/genetic factors that explain breast cancer disparities are likely to account for COVID-19 outcome disparities. Summary: The breast cancer clinical and research community should partner with public health experts to ensure participation of diverse patients in COVID-19 treatment trials and vaccine programs and to overcome COVID-19-related breast health management delays that are likely to have been magnified among African Americans and Hispanic-Latina Americans.