4CE is an international consortium for electronic health record (EHR) data-driven studies of the COVID-19 pandemic. The goal of this effort—led by the i2b2 international academics users group—is to inform doctors, epidemiologists and the public about COVID-19 patients with data acquired through the health care process.

Temporal Analysis of COVID-19 Laboratory Value Improvement and Mortality Rates

In "Temporal trends analysis of stratified mortality rates and laboratory trajectories shows improved survival across time in COVID-19 patients", we found that clinical and pathophysiologic profiles of patients hospitalized with SARS-CoV-2 infection did not differ greatly between the first and second waves of the pandemic in 2020. We then identified significant differences in laboratory improvement rates during hospitalization. Mortality risks among patients stratified into with similar risk categories decreased over the course of the pandemic. The improvement in laboratory values and mortality risk was consistent across multiple countries.

Phase 1.2 Post-acute Sequelae Profiles of COVID-19 Patients

In "International post-acute sequelae profiles of COVID-19 patients" using a federated international network of healthcare systems, we systematically identified robust conditions associated with PASC compared to appropriate control groups, underscoring the multifaceted cardiovascular and neurological phenotype profiles of PASC.

Phase 2.1 Outcomes of Hospitalized COVID-19 Patients with Neurological Diagnosis

In "Neurological diagnoses in hospitalized COVID-19 patients associated with adverse outcomes: a multinational cohort study" based on the Phase 2.1 data, we reported that patients with diagnosis involving the central nervous system during COVID-19 hospitalization harbored a greater burden of pre-existing comorbidities and had greater risk for adverse outcomes than patients with diagnosis involving the peripheral nervous system or with no neurological condition.

Distinguishing Incidental COVID-19 Admissions

A chart-reviewed characterization of the frequency that SARS-CoV-2-positive hospital admissions were not COVID-19 related and application of an Apriori-like itemset-mining algorithm to find phenotypes of patients admitted for COVID has been published in JMIR, "Distinguishing Admissions Specifically for COVID-19 From Incidental SARS-CoV-2 Admissions: National Retrospective Electronic Health Record Study."

SurvMaximin

The SurvMaximin algorithm to estimate Cox model feature coefficients for multi-center heterogeneous Real-World Data (RWD) with time-to-event outcomes and high-dimensional features has been submitted to medRxiv as a preprint, "SurvMaximin: Robust Federated Approach to Transporting Survival Risk Prediction Models."

Phase 2.1 Multivariate PheWAS of the Post-acute Sequelae of COVID-19

Results from the multivariate Phenome-wide Association Study (PheWAS) in the post-acute sequelae of COVID-19 (PASC) using Phase 2.1 have been published in BMC Medicine, "Evolving Phenotypes of non-hospitalized Patients that Indicate Long Covid."

Phase 1.1 Temporal Analysis of COVID-19 Clinical Trajectories

Results on temporal changes in COVID-19 clinical trajectories have been published in JMIR, "International Changes in COVID-19 Clinical Trajectories Across 315 Hospitals and 6 Countries: a 4CE Consortium Study."

Pediatric National Hospitalization Trends

The pediatrics group has recently published a brief report on national trends in hospitalization rates, "National Trends in Disease Activity for COVID-19 Among Children in the US."

Pediatrics Results

A retrospective cohort study to explore international hospitalization trends and key epidemiological and clinical features of children and youth with COVID-19, "International Analysis of Electronic Health Records of Children and Youth Hospitalized With COVID-19 Infection in 6 Countries."

Considerations on Utilizing EHR Data

A viewpoint article on considerations that are crucial for appraising studies utilizing EHR data has been published in JMIR, "What Every Reader Should Know About Studies Using Electronic Health Record Data but May Be Afraid to Ask."

Phase 1.1 Neurological Phenotype Analysis Results

Results from neurological phenotype analysis during Phase 1.1 have been published in Scientific Reports, "Multinational Characterization of Neurological Phenotypes in Patients Hospitalized with COVID-19."

Phase 1.1 Main Results

Results from Phase 1.1 of data acquisition and analysis have been submitted to medRxiv as a preprint, "International Comparisons of Harmonized Laboratory Value Trajectories to Predict Severe COVID-19: Leveraging the 4CE Collaborative Across 342 Hospitals and 6 Countries: A Retrospective Cohort Study."

Phase 1.1 Severity Definition Results

Results from the severity definition process during Phase 1.1 have been published in JAMIA, "Validation of an internationally derived patient severity phenotype to support COVID-19 analytics from electronic health record data."

Phase 1 Results

Results from the first phase of data acquisition and analysis have been published in npj Digital Medicine, "International Electronic Health Record-Derived COVID-19 Clinical Course Profile: The 4CE Consortium."

Joining the Consortium

If you are interested in joining the 4CE project, please visit the join page.