View as Webpage

Volume 66 | October 31, 2023

A program of NIH’s National Center for Advancing Translational Sciences

NCATS’ Sam Michael accepted the 2023 U.S. Department of Health and Human Services (HHS) Departmental Award on behalf of the NCATS National COVID Cohort Collaborative Data Enclave.

N3C has transformed how NIH and other federal agencies view big data, open science, and the power of cloud-based collaborative platforms. The award underscores the impact of NCATS’ translational science approaches to accelerate research on COVID-19. It’s great to see team science recognized in this way!

The Cardiovascular Diseases Domain Team (CVDT) is composed of individuals with a variety of backgrounds including clinicians, analysts, biostatisticians, and scientists from many institutions across the country, working collaboratively towards new discoveries of the impact of COVID-19 on cardiovascular diseases. Since the first meeting in February 2021, this group has been productive in researching COVID-19-related clinical cardiovascular health problems, learning about the relationship between COVID-19 and cardiovascular disease, and disseminating findings through manuscripts and abstract presentations at national meetings. In addition, CVDT members have been involved in supporting the N3C community in a number of activities including concept set creation and quality review of concept sets that have led to supporting the creation of N3C recommended concept sets and serving as beta-testers for the new publications intent platform.

Early efforts by the CVDT focused on investigating the impact of COVID-19 on patients with active cancers and measuring differences in major adverse cardiovascular events (MACE). This work resulted in three abstract presentations at the American College of Cardiology (ACC) 2022 Annual Meeting (Patel B, et al, Visaria A, et al, Visaria A, et al) and a recent publication in the journal Cardio-Oncology (Patel B, et al.). Additional work resulting in abstract presentations at ACC include an evaluation of outcomes and complications in patients with CVD infected with COVID-19 (Khodaverdi M, et al.) and the impact of health disparities in vaccinated CVD patients infected with COVID-19 (Khodaverdi M, et al).

More recent work has been related to exploring the impact of CVD-related comorbidities on MACE outcomes in COVID-19-infected patients with pre-existing heart failure and myocarditis/pericarditis diagnosis trends during the pre-COVID-19 era (Jan 2018-March 2020), the COVID-19/pre-vaccine era (April-December 2020), and COVID-19 and vaccine era (January 2021-March 2023). We have also explored the incidence of new cardiovascular complications between COVID-19 infection and receiving an mRNA vaccine.

Some recent CVDT research projects include:

• Outcomes of Patients with active cancers and pre-existing cardiovascular diseases infected with SARS-CoV-2

• COVID-19 Related Major Adverse Cardiovascular Events in Patients with Pre-Existing Heart Failure

• Myocarditis and Pericarditis Diagnosis Trends from 2018-2023 and the Influence of COVID-19 Infection and mRNA COVID-19 Vaccines

• Comparison of Cardiovascular Complications Associated with Myocarditis and Pericarditis Between COVID-19 Infection and mRNA COVID-19 Vaccines

• Methodological Quality Checks for OMOP Drug Concept Set Creation

The CVDT welcomes new team members and project ideas and has offered collaborative support for new projects. To learn more about the Cardiovascular Diseases Domain Team or to join our Domain Team, please visit https://covid.cd2h.org/cardiology or email n3c-dt-cardiology@googlegroups.com.

Meetings are held every other Thursday at 4 PM ET/1 PM PT

Next Meeting: November 2, 2023

Left to right: Anita Walden, Shawn O'Neil, Emily Marti

The N3C workshop, led by Anita Walden and Shawn O’Neil, of the University of Colorado Anschutz, introduced journalists to the National COVID Cohort Collaborative, which hosts hundreds of research projects using records representing over 20 million patients from around the US. Anita and Shawn discussed the team’s organization and how journalists can get involved, including data access requirements and finding collaborators with similar interests. A brief technical demonstration and hands-on activities showed participants the power and utility of large-scale health data analysis.

Releases and Updates Now Available in the Enclave

Machine learning (ML)-driven computable phenotypes are among the most challenging to share and reproduce. Despite this difficulty, the urgent public health considerations around Long COVID make it especially important to ensure the rigor and reproducibility of Long COVID phenotyping algorithms so they can be made available to a broad audience of researchers. As part of the NIH Researching COVID to Enhance Recovery (RECOVER) Initiative, researchers with the National COVID Cohort Collaborative (N3C) devised and trained an ML-based phenotype to identify patients highly probable to have Long COVID. Supported by RECOVER, N3C and NIH's All of Us study partnered to reproduce the output of N3C's trained model in the All of Us data enclave, demonstrating model extensibility in multiple environments. This case study in ML-based phenotype reuse illustrates how open-source software best practices and cross-site collaboration can de-black-box phenotyping algorithms, prevent unnecessary rework, and promote open science in informatics.

The White House Office of Science and Technology Policy (OSTP), in collaboration with federal agencies participating in a Year of Open Science, invites researchers, community scientists, educators, innovators, and members of the broader public to share stories of how they’ve advanced equitable open science.

Submissions Close on November 22, 2023.

The AMIA 2023 Annual Symposium centers on "Transforming Healthcare and Biomedicine for a Sustainable Future," tackling critical challenges in healthcare and biomedicine. The event emphasizes informatics' role in fostering sustainability and invites professionals worldwide to join in shaping a more equitable future. We are excited to share that many of our N3C collaborators will be presenting at the event.

• A Standard Operating Procedure for Concept Set Creation in the National COVID Cohort Collaborative

Speaker: Eileen Keck, BS, Stony Brook University  Author: Margaret Hall, MS, Emory University  Author: Adit Anand, BS, Stony Brook University  Author: Shreya Sinha, MS, Stony Brook University  Author: Tejas Patel, MD, Stony Brook University  Author: Dipika Rana, MD, FAAP, Stony Brook Medicine  

Author: Sigfried Gold, MFA MA, Johns Hopkins University  Author: Rachel Wong, MD MPH MBA, Stony Brook University, School of Medicine  Author: Harold Lehmann, MD PhD FACMI, Johns Hopkins University  Author: Richard Moffitt, PhD, Emory University

• Investigating COVID-19 outcomes for rare disease patients using semantic similarity and computational phenotyping

Speaker: Bryan Laraway, MS  Author: Justin Reese, PhD  Author: Katherina Cortes  Author: Andrew Williams, PhD  Author: Julie McMurry, MPH  Author: Tiffany Callahan, PhD, Columbia University Irving Medical Center  

Author: Peter Robinson, MD, MS  Author: Melissa Haendel, PhD, FACMI, University of Colorado Anschutz Medical Campus

• Value Set Curation in a Clinical Data Research Network: Certifying National COVID Cohort Collaborative (N3C) Recommended Concept Sets

Speaker: Johanna Loomba, ME, University of Virginia  Author: Stephanie Hong, BS, FAMIA, Johns Hopkins University School of Medicine  Author: Lisa Eskenazi, MHA, Johns Hopkins University School of Medicine  Author: Andrea Zhou, M.E., University of Virginia  Author: Xiaohan Zhang, MD, MS, Johns Hopkins University School of Medicine  

Author: Sigfried Gold, MFA MA, Johns Hopkins University  Author: Richard Moffitt, PhD, Emory University  Author: Richard Zhu, MD, Johns Hopkins University School of Medicine  Author: Amin Manna, ME, Palantir  Author: Saad Ljazouli, ME, Palantir  Author: Christopher Chute, MD, DrPH, Johns Hopkins University  Author: Harold Lehmann, MD PhD FACMI, Johns Hopkins University

• Harnessing Electronic Health Record data for Causal Inference through Target Trial Emulation: lessons from N3C-RECOVER

Speaker: Abhishek Bhatia, MS, University of North Carolina at Chapel Hill  Author: Alexander Preiss, MA, MS, RTI International  Author: Emily Pfaff, PhD, UNC Chapel Hill School of Medicine

• And many others!

Register for the AMIA 2023 Annual Symposium here

Save the Date!

AMIA 2024 Informatics Summit

March 18 - 21

Boston, MA

Anjali Sharathkumar

Professor of Pediatric

Director of Hemophilia Program,

Stead Family Department of Pediatrics

University of Iowa

To help our community with a positive and productive workload, N3C schedules several “No Meeting Weeks” throughout the year. The next N3C No Meeting Week will take place November 13 - November 17.

N3C support will continue with regular operations during these dates. Most meetings will be canceled. Impromptu meetings can still occur to push through action items as needed during no meeting week. Workgroups and Domain Teams should check with their Leads to determine meeting schedules for that week. 

Upcoming N3Community Forums

Register for the Forum

N3C In the News

Please report any questions, gaps, or errors to n3c.pubs@gmail.com

Gain Access to N3C Google Drive

Off-board from N3C

Report a Concern

Have something you'd like featured in the N3Connect Bulletin?

Submit it to taylor.dupree@cuanschutz.edu for consideration.

The National COVID Cohort Collaborative (N3C) is a complementary and synergistic partnership among the Clinical and Translational Science Awards (CTSA) Program hubs, the National Center for Data to Health (CD2H), distributed clinical data networks (PCORnet, OHDSI, ACT, TriNetX), and other partner organizations, with overall stewardship by NIH’s National Center for Advancing Translational Sciences (NCATS). The N3C aims to improve the efficiency and accessibility of analyses using a very large row-level (patient-level) COVID-19 clinical dataset, demonstrate a novel approach for collaborative pandemic data sharing, and speed understanding of and treatments for COVID-19.