The mission of our laboratory is to translate multi-modal data driven insights into clinical care for complex diseases. The amount and velocity of data that has been generated in the past decade on the ‘human condition’ has been immense. This includes biological and molecular data, clinical data, and exposomic data. However, it is an ongoing challenge to integrate and understand these diverse datasets to further our knowledge and ultimately improve the care of our patients. Taking on this challenge, our lab has three major goals especially in kidney and cardio-metabolic diseases:
1 Understand the determinants of disease
2 Predict the incidence and progression of disease and
3 Improve clinical care through data-driven insights
New and Noteworthy
R56 (PI: Nadkarni) from the NIDDK to use artificial intelligence to predict outcomes in patients with acute kidney injury on continuous renal replacement therapy.
Machine-learning tool may help predict acute kidney injury in patients with COVID-19
Researchers from Icahn School of Medicine at Mount Sinai found a machine-learning model performed well in predicting risk for AKI and need for dialysis in patients hospitalized with COVID-19.
Published: November 16, 2020
R01 (PI: Nadkarni) on defining genetic and environmental modifiers in individuals with high genetic risk was funded by the NIDDK.
Deaths Sky High in Hospitalized COVID Patients With Kidney Injury
More evidence indicates that the development of acute kidney injury (AKI) in patients hospitalized with COVID-19 is associated not only with dramatically higher than usual mortality rates but also that a significant proportion of patients with AKI do not recover kidney function by the time they are discharged.
Published: September 7, 2020