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Leverage the opportunities afforded by the rapidly evolving field of data science.
Connect critical care clinicians with data scientists in a two-day event aimed at creating pragmatic, data-driven models applicable to the care of critically ill patients.
Build a foundation for critical care data science to enhance its role in clinical decision-making and research. Establish principles for data standardization, sharing, and developing common data elements, validated through a pilot study.
Create a Discovery Critical Care Datahub to strengthen current data automation collaborations and expand future collaborations.
Improving Outcomes in Mechanically Ventilated Adult ICU Patients Following Implementation of the ICU Liberation (ABCDEF) Bundle Across a Large Healthcare System
Association of Active Renin Content With Mortality in Critically Ill Patients: A Post Hoc Analysis of the Vitamin C, Thiamine, and Steroids in Sepsis Trial
Biomarker-Concordant Steroid Administration in Severe Coronavirus Disease-2019
Effects of Timing of Invasive Mechanical Ventilation in Patients With Shock. An Analysis of the Multicenter Prospective Observational VOLUME-CHASERS Cohort
The Association of Early Systemic Corticosteroids and Secondary Infection Amongst Hospitalized COVID-19 Patients: Results from the SCCM Discovery Virus COVID-19 Registry
Impact of Early Tracheostomy on Hospitalization Outcomes in Mechanically Ventilated COVID-19 Patients
Early Tracheostomy is Associated with Improved Mobility and Shorter Duration of Sedative-Analgesic Use in Critically Ill COVID-19 Patients
Incidence of Post-Intubation Complications in Early vs Late-Tracheostomy in Hospitalized COVID-19 Patients
Outcomes Associated with Early Initiation of Inhaled Nitric Oxide in Hospitalized COVID-19 Patients
Improvement of Oxygenation Status with Inhaled Nitric Oxide Therapy in Hospitalized COVID-19 Patients: A Retrospective Study