CONCLUSIONS: Clinical informatics tools represent a feasible approach to leverage discrete treatment-related data elements from PFC or the EHR to successfully implement previously validated late cardiovascular risk prediction models on a population health level. Concordance of CCSS, COG, and IGHG risk groups using real-world data informs current guidelines and identifies inequities in guideline-adherent care.

Cerebral small vessel disease (CSVD) is the leading cause of vascular cognitive impairment and is associated with COVID-19. However, contributing factors that often accompany CSVD pathology in COVID-19 patients may influence the incidence of cerebrovascular complications. Thus, a mechanism linking COVID-19 and CSVD has yet to be uncovered and differentiated from age-related comorbidities (i.e., hypertension), and medical interventions during acute infection. We aimed to evaluate CSVD in acute...

CONCLUSION: This article presents method developments to manipulate and resolve EHR encounter data issues in a generalizable way as a foundation for future research and analysis.

CONCLUSIONS: Fiji-assisted automatic quantitative volumetric analysis can be useful for accurate, precise, and efficient measurements of total areas of CNV.

The purpose of this study was to understand the perceptions of HPV vaccination barriers and factors among parents or guardians of American Indian adolescents in the Cherokee Nation. Fifty-four parents of American Indian adolescents in the Cherokee Nation participated in one of eleven focus group discussions from June to August 2019. Discussions were recorded, transcribed, coded, and analyzed for themes. Protection against cancer was the primary parent-reported reason for vaccinating their...

As the coronavirus disease 2019 (COVID-19) pandemic progresses to an endemic phase, a greater number of patients with a history of COVID-19 will undergo surgery. Major adverse cardiovascular and cerebrovascular events (MACE) are the primary contributors to postoperative morbidity and mortality; however, studies assessing the relationship between a previous severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and postoperative MACE outcomes are limited. Here, we analyzed...

CONCLUSIONS: This machine learning model by accurately predicting the mortality provides insights about the treatment combinations associated with clinical improvement in COVID-19 patients. Analysis of the model's components suggests benefit to treatment with combination of steroids, antivirals, and anticoagulant medication. The approach also provides a framework for simultaneously evaluating multiple real-world therapeutic combinations in future research studies.

CONCLUSIONS: The creation of large scale centralized multi-site EHR databases such as N3C enables a wide range of research aimed at better understanding treatments and health impacts of many conditions including COVID-19. As with all observational research, it is important that research teams engage with appropriate domain experts to understand the data in order to define research questions that are both clinically important and feasible to address using these real world data.

CONCLUSIONS: In this N3C study, breakthrough infection rates were similar among CLD patients with and without cirrhosis. Full vaccination was associated with a 66% reduction in risk of all-cause mortality for breakthrough infection among CLD patients with cirrhosis. These results provide an additional impetus for increasing vaccination uptake in CLD populations.