Widespread sharing of data from electronic health records and patient-reported outcomes can strengthen the national capacity for conducting cost-effective clinical trials and allow research to be embedded within routine care delivery. While pragmatic clinical trials (PCTs) have been performed for decades, they now can draw on rich sources of clinical and operational data that are continuously fed back to inform research and practice. The Health Care Systems Collaboratory program, initiated by the NIH Common Fund in 2012, engages healthcare systems as partners in discussing and promoting activities, tools, and strategies for supporting active participation in PCTs. The NIH Collaboratory consists of seven demonstration projects, and seven problem-specific working group 'Cores', aimed at leveraging the data captured in heterogeneous 'real-world' environments for research, thereby improving the efficiency, relevance, and generalizability of trials. Here, we introduce the Collaboratory, focusing on its Phenotype, Data Standards, and Data Quality Core, and present early observations from researchers implementing PCTs within large healthcare systems. We also identify gaps in knowledge and present an informatics research agenda that includes identifying methods for the definition and appropriate application of phenotypes in diverse healthcare settings, and methods for validating both the definition and execution of electronic health records based phenotypes.
Further research focused on defining the clinical characteristics of standard diabetes cohorts is important to identify appropriate phenotype definitions for health, policy, and research.
The Coronavirus Disease 2019 (COVID-19) pandemic forced researchers to reconsider in-person assessments due to transmission risk. We conducted a pilot study to evaluate the feasibility of using the Tasso-SST (Tasso, Inc, Seattle, Washington) device for blood self-collection for use in SARS-CoV-2 antibody testing in an ongoing COVID-19 prevalence and immunity research study. 100 participants were recruited between January and March 2021 from a previously identified sub-cohort of the Cabarrus County COVID-19 Prevalence and Immunity (C3PI) Study who were under-going bimonthly COVID-19 antibody testing. Participants were given a Tasso-SST kit and asked to self-collect blood during a scheduled visit where trained laboratory personnel performed routine phlebotomy. All participants completed an after-visit survey about their experience. Overall, 70.0% of participants were able to collect an adequate sample for testing using the device. Among those with an adequate sample, there was a high concordance in results between the Tasso-SST and phlebotomy blood collection methods (Cohen’s kappa coefficient = 0.88, Interclass correlation coefficient 0.98 [0.97, 0.99], p < 0.0001). The device received a high-level (90.0%) of acceptance among all participants. Overall, the Tasso-SST could prove to be a valuable tool for seroprevalence testing. However, future studies in larger, diverse populations over longer periods may provide a better understanding of device usability and acceptance among older participants and those with comorbidities in various use scenarios.
Background Distinguishing systemic metabolic disruptions in maple syrup urine disease (MSUD) beyond amino acid pathways is under-investigated, yet important to understanding disease pathology and treatment options. Methods An adolescent female (15 years) with MSUD without liver transplant, attended 2 study visits, 5 days apart. Medical diet adherence was determined based on her 3-day diet records and plasma branched-chain amino acid (BCAA) concentrations at both study visits. Plasma from a single age- and sex-matched control (MURDOCK Study, Duke University) and the case patient were analyzed with UPLC/MS/MS for intensity ( m / z ), annotated, and normalized against a median of 1 (Metabolon, Morrisville NC). Differences between case/control and 5-day comparisons were defined as ≥ ǀ 0.5 ǀ. Results 434 lipid metabolites were identified across samples; 90 (20.7%) were higher and 120 (27.6%) lower in the MSUD case at baseline compared with control. By study visit 2, plasma BCAA had declined, while 48 (53%) of elevated lipids and 14 (11.7%) of lower lipid values had moved to within ǀ 0.5 ǀ of control. Most shifts towards control by day 5 were seen in long-chain fatty acid intermediates (42%) and acylcarnitines (32%). Although androgenic (28%) and bile acid (23%) metabolites increased towards control, neither reached control level by day 5. Discussion This comparative metabolomics study in a single MSUD case and healthy control suggests intrinsic differences in MSUD lipid metabolism potentially influenced by therapeutic diet. Findings suggest influences on hormone regulation, fatty acid oxidation, and bile acid synthesis, but further studies are needed to confirm an association between MSUD and lipid dysregulation. Synopsis Within 5 days of improved dietary adherence, a single MSUD case experienced substantial changes in lipid markers potentially related to changes in plasma branched-chain amino acids.
Background Mitigation behaviors reduce the incidence of COVID-19 infection. Determining characteristics of groups defined by mitigation behaviors compliance may be useful to inform targeted public health policies and interventions. This study aimed to identify groups of individuals according to self-reported compliance with COVID-19 mitigation behaviors, define compliance class characteristics, and explore associations between compliance classes and important study and public health outcomes. Methods and findings We studied 1,410 participants in the Cabarrus County COVID-19 Prevalence and Immunity longitudinal cohort study (June 2020 to December 2021) who were asked 10 questions regarding compliance with recommended COVID-19 mitigation behaviors. By Latent Class Analysis, 1,381 participants were categorized into 3 classes (most [49.4%], moderately [45.0%], and least [5.6%] compliant). Compared with the most compliant class, the least and moderately compliant classes were younger (mean = 61.9 v. 59.0 v. 53.8 years), had fewer medical conditions per individual (1.37 v. 1.08 v. 0.77), and differed in Hispanic ethnicity (6.2% v. 2.8% v. 9.1%) and COVID-19 vaccine intention (65.8% v. 59.8% v. 35.1%). Compared to the most compliant class, the least compliant class had fewer women (54.6% v. 76.3%), fewer insured individuals (92.2% v. 97.4%), and more withdrew from study participation early (28.6% v. 16.0%). Relative to the most compliant class, the least compliant class had a higher likelihood of COVID-19 infection (OR = 2.08 [95% CI 1.13, 3.85]), lower rate of COVID-19 vaccination (72.6% v. 95.1%), and longer time to 50% COVID-19 vaccination following eligibility (8–9 vs 16 days). Conclusions Classes defined by mitigation behaviors compliance had distinct characteristics, including age, sex, medical history, and ethnicity, and were associated with important study and public health outcomes. Targeted public health policies and interventions according to the compliance group characteristics may be of value in current and future pandemic responses to increase compliance.
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