The Einstein-Montefiore Institute for Clinical and Translational Research (ICTR) proposes an Administrative Supplement pursuant to NOT-TR-20-011, CTSA Program Applications to Address 2019 Novel Coronavirus (Covid-19). Specifically, this application addresses the urgent need for research on the coronavirus pandemic with a project focusing on informatics and data science to preemptively identify patients with the life- threatening complications of SARS-CoV-2, using CTSA-supported core resources. Characterized by severe hypoxemia, tachypnea, and decreased lung compliance, the diagnosis of acute respiratory failure (ARF) is a bad prognostic sign, and in a subset, leads to development of acute respiratory distress syndrome (ARDS). The rates of Covid-19 infection and death in the Bronx have been higher than any other borough of NYC. As the major regional health system, our experience with Covid-19 provides guideposts that may prevent future victims of this pandemic. The bleak picture for ARDS in the 4,452 patients admitted showed that 78% of our intubated Covid-19 patients developed ARDS, with 42% mortality. The overall goal of this proposal is to leverage our novel informatics and analytics platforms enabled by the Einstein-Montefiore CTSA (NIH/NCATS 1ULTR002556), and extensive Artificial Intelligence and Deep Learning resources to implement a novel, situational awareness and clinical decision support system for ARF and ARDS (SA-ARDS). We will re-train our existing deep learning models with data collected from Covid-19 patients and contextualize its implementation with data from the Covid-19 response during the pandemic in NYC. The SA-ARDS data platform will provide longitudinally integrated clinical data for research and multi-institutional and national collaborations, with the following specific aims:
Aim 1 : To integrate, re-train, and validate our novel, near real-time, Electronic Risk Assessment System (ERAS 1.0) optimized for early recognition of ARF, ARDS, and inpatient mortality;
Aim 2 : To develop an evidence based, real-time, and context appropriate Situational Awareness clinical decision support system targeting ARF and ARDS response (SA-ARDS);
and Aim 3 : Through our partner CTSA organizations, to standardize and disseminate ERAS 1.0 and the SA-ARDS to other health systems, including the NYC consortium of CTSA hubs and the PCORI INSIGHT network. We will use the clinical data underlying the SA-ARDS to support research in local, regional, and national collaborations. All the methods and tools developed will be shared with the CTSA community via NCATS' National Center for Data to Health (CD2H).

Public Health Relevance

The US is in the midst of a public health crisis of the Covid-19 pandemic. We will create an artificial intelligence system to provide an early warning system optimized for recognition of ARF, ARDS, and inpatient mortality, and provide a base for application of artificial intelligence to detection of other debilitating and potentially fatal outcomes of Covid-19.

Agency
National Institute of Health (NIH)
Institute
National Center for Advancing Translational Sciences (NCATS)
Type
Linked Specialized Center Cooperative Agreement (UL1)
Project #
3UL1TR002556-04S2
Application #
10158737
Study Section
Program Officer
Talbot, Bernard
Project Start
2020-07-09
Project End
2021-02-28
Budget Start
2020-07-09
Budget End
2021-02-28
Support Year
4
Fiscal Year
2020
Total Cost
Indirect Cost
Name
Albert Einstein College of Medicine
Department
Type
DUNS #
081266487
City
Bronx
State
NY
Country
United States
Zip Code
10461
Isasi, Carmen R; Strizich, Garrett M; Kaplan, Robert et al. (2018) The association of cardiorespiratory fitness with cardiometabolic factors, markers of inflammation, and endothelial dysfunction in Latino youth: findings from the Hispanic Community Children's Health Study/Study of Latino Youth. Ann Epidemiol 28:583-589.e3
Lucan, Sean C; Maroko, Andrew R; Seitchik, Jason L et al. (2018) Sources of Foods That Are Ready-to-Consume ('Grazing Environments') Versus Requiring Additional Preparation ('Grocery Environments'): Implications for Food-Environment Research and Community Health. J Community Health 43:886-895
Taneva, Ekaterina; Sinclair, Shada; Mesquita, Pedro Mm et al. (2018) Vaginal microbiome modulates topical antiretroviral drug pharmacokinetics. JCI Insight 3:
Fox, Robert J; Coffey, Christopher S; Conwit, Robin et al. (2018) Phase 2 Trial of Ibudilast in Progressive Multiple Sclerosis. N Engl J Med 379:846-855
Abramowitz, Matthew K; Hall, Charles B; Amodu, Afolarin et al. (2018) Correction: Muscle mass, BMI, and mortality among adults in the United States: A population-based cohort study. PLoS One 13:e0198318
Gasic, Daniel; Rosenschöld, Per Munck Af; Vogelius, Ivan R et al. (2018) Retrospective estimation of heart and lung doses in pediatric patients treated with spinal irradiation. Radiother Oncol 128:209-213
Sohler, Nancy L; Starrels, Joanna L; Khalid, Laila et al. (2018) Cannabis Use is Associated with Lower Odds of Prescription Opioid Analgesic Use Among HIV-Infected Individuals with Chronic Pain. Subst Use Misuse 53:1602-1607
Holtzer, Roee; George, Claudene J; Izzetoglu, Meltem et al. (2018) The effect of diabetes on prefrontal cortex activation patterns during active walking in older adults. Brain Cogn 125:14-22
Tymon-Rosario, Joan R; Miller, Eirwen M; Gressel, Gregory M et al. (2018) Association between diabetes mellitus and progression free survival in women with ovarian granulosa cell tumors. Gynecol Oncol Rep 26:94-98
Rubin, Todd G; Catenaccio, Eva; Fleysher, Roman et al. (2018) MRI-defined White Matter Microstructural Alteration Associated with Soccer Heading Is More Extensive in Women than Men. Radiology 289:478-486

Showing the most recent 10 out of 33 publications