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.

Implementing DASH-Aligned Meals and Self-Measured Blood Pressure to Reduce Hypertension at Senior Centers: A RE-AIM Analysis.

Low-income, minority seniors face high rates of hypertension that increase cardiovascular risk. Senior centers offer services, including congregate meals, that can be a valuable platform to reach older adults in underserved communities. We implemented two evidence-based interventions not previously tested in this setting: DASH-aligned congregate meals and Self-Measured Blood Pressure (SMBP), to lower blood pressure (BP) at two senior centers serving low-income, racially diverse communities. The study enrolled congregate meal program participants, provided training and support for SMPB, and nutrition and BP education. DASH-aligned meals delivered 40% (lunch) or 70% (breakfast and lunch) of DASH requirements/day. Primary outcomes were change in BP, and BP control, at Month 1. Implementation data collected included client characteristics, menu fidelity, meal attendance, SMBP adherence, meal satisfaction, input from partner organizations and stakeholders, effort, and food costs. We used the RE-AIM framework to analyze implementation. Study Reach included 94 older, racially diverse participants reflecting neighborhood characteristics. Effectiveness: change in systolic BP at Month 1 trended towards significance (-4 mmHg, p = 0.07); change in SMBP reached significance at Month 6 (-6.9 mmHg, p = 0.004). We leveraged existing community-academic partnerships, leading to Adoption at both target sites. The COVID pandemic interrupted Implementation and Maintenance and may have attenuated BP effectiveness. DASH meals served were largely aligned with planned menus. Meal attendance remained consistent; meal satisfaction was high. Food costs increased by 10%. This RE-AIM analysis highlights the acceptability, feasibility, and fidelity of this DASH/SMBP health intervention to lower BP at senior centers. It encourages future research and offers important lessons for organizations delivering services to older adults and addressing cardiovascular risk among vulnerable populations.

Implementing DASH-aligned Congregate Meals and Self-Measured Blood Pressure in two senior centers: An open label study.

BACKGROUND AND AIMS: Cardiovascular Disease (CVD) poses significant health risks for seniors, especially among low-income and minority communities. Senior centers offer multiple services. We tested whether implementing two evidence-based interventions- DASH-aligned meals provided through an existing congregate meal program, and support for home Self-Measured Blood Pressure (SMBP) monitoring-lowers blood pressure among participants at two senior centers serving low-income, racially diverse communities. METHODS AND RESULTS: Open-label study, enrolling clients aged ≥60, eating ≥4 meals/week at two NYC senior centers. Participants received DASH-aligned congregate meals, and training in nutrition, BP management education, and personal SMBP device. Co-Primary outcomes: a) change in systolic BP measured by independent health professionals, and b) change in percent with "controlled BP" (Eighth Joint National Committee (JNC-8) Guidelines), at Month 1 compared to Baseline. SECONDARY OUTCOMES: Changes in BP at Months 3 and 5/6 (last measure). We enrolled 94 participants; COVID closures interrupted implementation mid-study. Mean systolic BP at Month-1 changed by -4.41 mmHg (n = 61 p = 0.07) compared to Baseline. Participants with controlled BP increased (15.7%) at Month 1. Change in mean BP at Month 1 was significantly correlated with BMI (p = 0.02), age (p = 0.04), and baseline BP (p < 0.001). Mean systolic SMBP changed by -6.9 mmHg (p = 0.004) at Months 5/6. CONCLUSIONS: Implementing an evidence-based multi-component BP-lowering intervention within existing congregate meal programs at senior centers serving minority and low-income communities is feasible, and early findings show promising evidence of effectiveness. This approach to cardiovascular risk reduction should be further tested for widespread adoption and impact. Registered on ClinicalTrials.gov NCT03993808 (June 21st, 2019).

Molecular Types of Methicillin-Resistant Staphylococcus aureus and Methicillin-Sensitive S. aureus Strains Causing Skin and Soft Tissue Infections and Nasal Colonization, Identified in Community Health Centers in New York City.

In November 2011, The Rockefeller University Center for Clinical and Translational Science (CCTS), the Laboratory of Microbiology and Infectious Diseases, and Clinical Directors Network (CDN) launched a research and learning collaborative project with six community health centers in the New York City metropolitan area to determine the nature (clonal type) of community-acquired Staphylococcus aureus strains causing skin and soft tissue infections (SSTIs). Between November 2011 and March 2013, wound and nasal samples from 129 patients with active SSTIs suspicious for S. aureus were collected and characterized by molecular typing techniques. In 63 of 129 patients, the skin wounds were infected by S. aureus: methicillin-resistant S. aureus (MRSA) was recovered from 39 wounds and methicillin-sensitive S. aureus (MSSA) was recovered from 24. Most-46 of the 63-wound isolates belonged to the CC8/Panton-Valentine leukocidin-positive (PVL(+)) group of S. aureus clone USA300: 34 of these strains were MRSA and 12 were MSSA. Of the 63 patients with S. aureus infections, 30 were also colonized by S. aureus in the nares: 16 of the colonizing isolates were MRSA, and 14 were MSSA, and the majority of the colonizing isolates belonged to the USA300 clonal group. In most cases (70%), the colonizing isolate belonged to the same clonal type as the strain involved with the infection. In three of the patients, the identity of invasive and colonizing MRSA isolates was further documented by whole-genome sequencing.

On the combination of two visual cognition systems using combinatorial fusion.

When combining decisions made by two separate visual cognition systems, statistical means such as simple average (M 1) and weighted average (M 2 and M 3), incorporating the confidence level of each of these systems have been used. Although combination using these means can improve each of the individual systems, it is not known when and why this can happen. By extending a visual cognition system to become a scoring system based on each of the statistical means M 1, M 2, and M 3 respectively, the problem of combining visual cognition systems is transformed to the problem of combining multiple scoring systems. In this paper, we examine the combined results in terms of performance and diversity using combinatorial fusion, and study the issue of when and why a combined system can be better than individual systems. A data set from an experiment with twelve trials is analyzed. The findings demonstrated that combination of two visual cognition systems, based on weighted means M 2 or M 3, can improve each of the individual systems only when both of them have relatively good performance and they are diverse.

TreeParser-aided Klee diagrams display taxonomic clusters in DNA barcode and nuclear gene datasets.

Indicator vector analysis of a nucleotide sequence alignment generates a compact heat map, called a Klee diagram, with potential insight into clustering patterns in evolution. However, so far this approach has examined only mitochondrial cytochrome c oxidase I (COI) DNA barcode sequences. To further explore, we developed TreeParser, a freely-available web-based program that sorts a sequence alignment according to a phylogenetic tree generated from the dataset. We applied TreeParser to nuclear gene and COI barcode alignments from birds and butterflies. Distinct blocks in the resulting Klee diagrams corresponded to species and higher-level taxonomic divisions in both groups, and this enabled graphic comparison of phylogenetic information in nuclear and mitochondrial genes. Our results demonstrate TreeParser-aided Klee diagrams objectively display taxonomic clusters in nucleotide sequence alignments. This approach may help establish taxonomy in poorly studied groups and investigate higher-level clustering which appears widespread but not well understood.

Bioinformatics tools enabling u-statistics for microarrays.

It is rare that a single gene is sufficient to represent all aspects of genomic activity. Similarly, most common diseases cannot be explained by a mutations at a single locus. Since complex systems tend to be neither linear nor hierarchical in nature, but to have correlated components of unknown relative importance, the assumptions of traditional (parametric) multivariate statistical methods can rarely be justified on theoretical grounds. Empirical "validation" is not only problematic, but also time consuming. Here we demonstrates how bioinformatics tools, ranging from spreadsheets to grids, can enable u-statistics as a non-parametric alternative for scoring multivariate ordinal data. Applications are shown to improve assessment of genetic risk factors, quality control of microarrays and signal value estimation, scoring genomic profiles that best correlated with complex risk factors (cardiovascular diseases), and complex responses to an intervention (treatment of psoriasis).