Journal of Clinical and Translational Science最新文献

Objective: DeGAUSS is a privacy-preserving application that ingests addresses and generates output that includes latitude, longitude, census tract, deprivation index and drive times to major hospitals. The application uses a complex command line interface and a container management platform to perform analysis. Our objective was to develop a user-friendly DeGAUSS-based application that simplifies place-based analysis. We also enabled automated geomarker generation by providing an API modality to DeGAUSS.

Methods: We developed a self-service platform based on the DeGAUSS application. The application was linked to user authentication platforms. The self-service application can be implemented as an API, enabling high-volume geocoding transactions. We surveyed active users for feedback.

Results: The self-service geomarker application was deployed at Children's Mercy and the University of Kansas Medical Center. During the period evaluated, more than 2 million addresses were geocoded for 24 users through the user interface and more than 15 million addresses through the API. Users expressed high satisfaction with the system. All respondents used the census block group feature and the core geocoding. Most respondents, 60%, used the deprivation index and 30% used the drive time feature. Population health and social determinants of health were the most common uses (80% each) followed by health equity analyses (70%).

Conclusion: Population health and social determinants of health research require access to precise geographic information about patients or research subjects. The self-service geomarker capability enables users who may not be comfortable with a command line interface to generate geocoded addresses in support of their research and analysis.

[This corrects the article DOI: 10.1017/cts.2025.10208.].

In 2013, the National Institute of Neurological Disorders and Stroke established National Institutes of Health (NIH) StrokeNet to support multi-site clinical trials focused on stroke prevention, treatment, and recovery. The University of Cincinnati (UC) serves as the National Coordinating Center for StrokeNet. As part of the initiative, the UC StrokeNet Central IRB (SN-CIRB) was established at UC to serve as a single IRB to oversee StrokeNet trials. Since the SN-CIRB approved the first StrokeNet study in 2014, it has reviewed and approved 16 additional studies. Over this period, the UC Human Research Protection Program refined its review processes based on insights from earlier reviews. These improvements have improved efficiency while still ensuring the protection of study participants. The successful implementation and ongoing conduct of the SN-CIRB at UC demonstrate that an academic-based IRB can effectively serve as a Central IRB for a large clinical trial network.

Background/objective: Chronic pain research studies are important for both finding new treatments and improving existing treatments for individuals with chronic pain. For clinical trials to be effective, participants need to be engaged and willing to participate in treatment groups. Our research applies the theory of planned behavior (TPB) to understand how attitudes, perceived social norms, and perceived control over intervention engagement are associated with willingness to participate in interventions for chronic low back pain (CLBP).

Methods: Adult Michigan Medicine patients were identified using electronic medical records and emailed a link to an online, cross-sectional survey. Participants who self-reported CLBP, ability to read and write in English, and consented to participate were able to complete the survey (N = 405).

Results: The results showed more positive attitudes, positive social norms, and higher perceived behavioral control related to specific chronic low back pain interventions are associated with greater willingness to participate after controlling for demographic and pain-related characteristics.

Conclusion: The findings suggest that TPB constructs may be useful in guiding recruitment efforts for chronic pain intervention trials.

Older adults aged 75 and older (75+) represent the fastest-growing demographic in the USA yet remain underrepresented in prevention-focused clinical research. This scoping review evaluated recruitment strategies used in healthy aging clinical trials targeting this population, with particular attention to technology-enabled and belonging-focused approaches. A PubMed search initially identified only four US-based studies focused on adults aged 75+. To broaden the scope and enrich the analysis, additional studies involving adults aged 65+ and those with pre-existing conditions were included, yielding a total of 23 relevant studies. Recruitment strategies were analyzed using the Design for Belonging framework to assess how inclusion and engagement were fostered. Findings revealed that adults aged 75+ preferred traditional methods - targeted mailings, phone calls, and in-person outreach - due to barriers related to digital access and usability. In contrast, adults aged 65+ showed greater receptivity to digital tools such as electronic health records, social media, and web-based enrollment. Community engagement and culturally tailored materials are effective across all age groups. However, few studies addressed later-stage engagement strategies like advocacy and trust repair. These results underscore the importance of tailoring recruitment strategies to aging subgroups, combining personalized outreach with inclusive design to enhance equity and retention in clinical research.

Introduction: General Practitioners (GPs) in Australia continue to provide primary medical care for patients enrolled in specialist-led clinical trials (CTs), yet research on GPs' experiences in this role remains limited. This study explored Australian GPs' experiences managing CT patients and their perspectives on primary care involvement in clinical research.

Methods: This phenomenological study involved 11 semi-structured interviews with GPs in New South Wales, Australia, between July to October 2024, who previously managed patients enrolled in other non-GP subspecialist CTs. The recruitment applied purposive, snowballing and convenience sampling approaches. Interviews were transcribed, inductively coded and thematically analyzed.

Results: Analysis revealed four themes: (i) lack of communication from CT teams, (ii) patients' insufficient understanding about their CTs, (iii) time and resource barriers to GP involvement in CTs, (iv) varied opinions about GPs playing an active role as researchers in CTs.

Conclusions: This exploratory study highlighted the lack of proper communication gaps between CT teams and GPs, potentially compromising the quality of patient care. Digital health records (such as Australia's My Health Record) could facilitate information sharing. While GPs support primary care research, barriers include limited research training, time constraints, and inadequate resources. Integrating research education into GP training and establishing practice-based research networks could enhance GP participation in CTs.

Background: Long COVID remains poorly characterized at the genomic level. The primary aim of this study was to examine the relationship between viral sequences and the incidence of Long COVID at a tertiary care center in Louisiana between April 2020 and December 2022. A secondary aim was analysis of the Spike protein to identify conserved regions for multivalent vaccine targets.

Method: To estimate Long COVID incidence across variants, we linked 4789 SARS-CoV-2 sequences to 3090 de-identified patient electronic health record information. The base population was defined as any patient with an International Classification of Diseases-10-Clinical Modification COVID-19 diagnosis code (U07.1) based definitions of Long COVID presentation developed by the N3C consortium.

Results: 1,554 patients (1,536 Long COVID-negative) met Long COVID definitions, with 56.3% being female, 36.1% self-reported as African American, 5.5% self-reported as Hispanic/Latino, and 54.5% had received at least one vaccine dose 14 days prior to SARS-CoV-2 collection. Long COVID-positive patients were older (mean age 43.1 years) than negative patients (35.9 years; p = 0.0054) and were more likely to be female (p = 0.0001). Among unvaccinated patients, those with Long COVID were significantly younger than their vaccinated counterparts (p < 0.00001). Long COVID incidence varied by PANGO lineage, ranging between 14% in AY.13 to 67.8% in B.1.1.7. Analysis of spike protein diversity revealed eight conserved amino acid regions (Shannon entropy < 0.43), representing potential targets for vaccine design.

Conclusion: Long COVID rates across thousands of annotated SARS-CoV-2 sequences revealed lineage-specific risk and conserved epitopes for future interventions.

Purpose: We describe the steps taken to assess and improve the research readiness of data within PCORnet®, specifically focusing on the results of the PCORnet data curation process between Cycle 7 (October 2019) and Cycle 16 (October 2024).

Material and methods: We describe the process for extending the PCORnet® CDM and for creating data checks.

Results: We highlight growth in the number of records available across PCORnet between data curation Cycles 7 and 16 (e.g., diagnoses increasing from ∼3.7B to ∼6.9B and laboratory results from ∼7.7B to ∼15.1B among legacy DataMarts), present the current list of data checks and describe performance of the network. We highlight examples of data checks with relatively stable performance (e.g., future dates), those where performance has improved (e.g., RxNorm mapping), and others performance is more variable (e.g., persistence of records).

Conclusion: Studies are a crucial source of information on the design of new data checks. The attention of PCORnet partners is focused primarily on those metrics that are generally modifiable. A transparent data curation process is an essential component of PCORnet, allowing network partners to learn from one another, while also informing the decisions of study investigators on which sites to include in their projects. The quality issues that exist within PCORnet stem from the way that data are captured within healthcare generally. We have been able to make to make great strides on improving data quality and research readiness. Many of the techniques piloted within PCORnet will be broadly applicable to other efforts.

Rural America remains deeply under-represented in clinical trials. St Lawrence Health (SLH) was the sole rural site and one of the top recruiters in the Accelerating COVID-19 Therapeutic Interventions and Vaccines (ACTIV)-1 trial, which was a large international trial that studied the efficacy of three immune modulators in hospitalized patients with COVID-19. In this article, we analyze the structural and clinical factors that enabled SLH's success in the context of previously described barriers to research participation in rural areas. We conclude with lessons learned from the SLH experience and offer a broader replicable model for developing clinical research capacity in rural areas. SLH's success in ACTIV-1 can be attributed to early and sustained support from the ACTIV-1 network, a small and integrated inpatient COVID-19 treatment team, regular and consistent communication between this team and the clinical research team at SLH, and SLH's ongoing support and development of its clinical research department. SLH was, in turn, able to overcome several known barriers to implementation of clinical trials at community sites, including lack of provider time and a lack of trained research and clinical staff, and its experience in ACTIV-1 offers a replicable model for developing clinical research capacity in rural communities.