EHR-based cohort assessment for multicenter RCTs: a fast and flexible model for identifying potential study sites

ObjectiveThe Recruitment Innovation Center (RIC), partnering with the Trial Innovation Network and institutions in the National Institutes of Health-sponsored Clinical and Translational Science Awards (CTSA) Program, aimed to develop a service line to retrieve study population estimates from electronic health record (EHR) systems for use in selecting enrollment sites for multicenter clinical trials. Our goal was to create and field-test a low burden, low tech, and high-yield method.Materials and MethodsIn building this service line, the RIC strove to complement, rather than replace, CTSA hubs’ existing cohort assessment tools. For each new EHR cohort request, we work with the investigator to develop a computable phenotype algorithm that targets the desired population. CTSA hubs run the phenotype query and return results using a standardized survey. We provide a comprehensive report to the investigator to assist in study site selection.ResultsFrom 2017 to 2020, the RIC developed and socialized 36 phenotype-dependent cohort requests on behalf of investigators. The average response rate to these requests was 73%.DiscussionAchieving enrollment goals in a multicenter clinical trial requires that researchers identify study sites that will provide sufficient enrollment. The fast and flexible method the RIC has developed, with CTSA feedback, allows hubs to query their EHR using a generalizable, vetted phenotype algorithm to produce reliable counts of potentially eligible study participants.ConclusionThe RIC’s EHR cohort assessment process for evaluating sites for multicenter trials has been shown to be efficient and helpful. The model may be replicated for use by other programs.     

The provision of a time-critical elective surgical service during the COVID-19 Crisis: a UK experience

IntroductionWith the emergence of the COVID-19 pandemic, all elective surgery was temporarily suspended in the UK, allowing for diversion of resource to manage the anticipated surge of critically unwell patients. Continuing to deliver time-critical surgical care is important to avoid excess morbidity and mortality from pathologies unrelated to COVID-19. We describe the implementation and short-term surgical outcomes from a system to deliver time-critical elective surgical care to patients during the COVID-19 pandemic.Materials and methodsA protocol for the prioritisation and safe delivery of time-critical surgery at a COVID-19 ‘clean’ site was implemented at the Nuffield Health Exeter Hospital, an independent sector hospital in the southwest of England. Outcomes to 30 days postoperatively were recorded, including unplanned admissions after daycase surgery, readmissions and complications, as well as the incidence of perioperative COVID-19 infection in patients and staff.ResultsA total of 128 surgical procedures were performed during a 31-day period by a range of specialties including breast, plastics, urology, gynaecology, vascular and cardiology. There was one unplanned admission and and two readmissions. Six complications were identified, and all were Clavien-Dindo grade 1 or 2. All 128 patients had preoperative COVID-19 swabs, one of which was positive and the patient had their surgery delayed. Ten patients were tested for COVID-19 postoperatively, with none testing positive.ConclusionThis study has demonstrated the implementation of a safe system for delivery of time-critical elective surgical care at a COVID-19 clean site. Other healthcare providers may benefit from implementation of similar methodology as hospitals plan to restart elective surgery.     

Expression of ICAM-R (ICAM-3), a novel counter-receptor for LFA-1, in rheumatoid and nonrheumatoid synovium

Objective. To study the distribution of intercellular adhesion molecule receptor (ICAM-R, or ICAM-3), a novel ligand for the leukointegrin lymphocyte function-associated antigen 1 (LFA-1), in normal and rheumatoid synovial membranes and to compare this with the distribution of ICAM-1, ICAM-2, vascular cell adhesion molecule 1 (VCAM-1), and endothelial leukocyte adhesion molecule 1 (ELAM-1). Methods. We performed immunohistochemical analyses of frozen sections of normal and rheumatoid synovial tissue using monoclonal antibodies to the molecules examined. Results. ICAM-1 staining was detectable on the vascular endothelium and the synovial lining cells of both normal and rheumatoid synovial membranes. A variable proportion of lymphocytes infiltrating rheumatoid tissues expressed ICAM-1. ICAM-2 staining was demonstrable in the vascular endothelium of both normal and inflamed tissues, the latter demonstrating a significantly higher proportion of positive vessels. ELAM-1 staining was not detectable in normal synovial membranes but was seen on the endothelium of a limited number of rheumatoid synovial vessels, usually close to the synovial lining cell layer. VCAM-1 staining was intense in both normal and rheumatoid synovial lining cells, but vascular staining was weak in both. In contrast, ICAM-R staining was not detected in association with any synovial blood vessels, but was widely expressed by lymphocytes and macrophages. Cells of the lining layer did not stain for ICAM-R. Conclusion. Although ICAM-R is a ligand for LFA-1 and shares considerable sequence homology with ICAM-1 and ICAM-2, it does not appear to be expressed by the endothelium of normal or inflamed synovial vessels. Intense expression of ICAM-R by rheumatoid synovial lymphocytes and macrophages suggests that it may play a role in processes requiring cell-cell contact, such as antigen presentation and homotypic aggregation.     

Quantum Monte Carlo computations of phase stability,equations of state,and elasticity of high-pressure silica

Silica (SiO₂) is an abundant component of the Earth whose crystalline polymorphs play key roles in its structure and dynamics. First principle density functional theory (DFT) methods have often been used to accurately predict properties of silicates, but fundamental failures occur. Such failures occur even in silica, the simplest silicate, and understanding pure silica is a prerequisite to understanding the rocky part of the Earth. Here, we study silica with quantum Monte Carlo (QMC), which until now was not computationally possible for such complex materials, and find that QMC overcomes the failures of DFT. QMC is a benchmark method that does not rely on density functionals but rather explicitly treats the electrons and their interactions via a stochastic solution of Schrödinger’s equation. Using ground-state QMC plus phonons within the quasiharmonic approximation of density functional perturbation theory, we obtain the thermal pressure and equations of state of silica phases up to Earth’s core–mantle boundary. Our results provide the best constrained equations of state and phase boundaries available for silica. QMC indicates a transition to the dense α-PbO₂ structure above the core-insulating D” layer, but the absence of a seismic signature suggests the transition does not contribute significantly to global seismic discontinuities in the lower mantle. However, the transition could still provide seismic signals from deeply subducted oceanic crust. We also find an accurate shear elastic constant for stishovite and its geophysically important softening with pressure.