Dascena Receives FDA Breakthrough Device Designation for Machine Learning Algorithm for Earlier Prediction of Acute Kidney Injury

This is the first Breakthrough Device Designation of a cloud-based machine learning algorithm developed for the early detection of AKI.

Metadata
Provider: 
Business Wire, Inc.Business Wire, Inc.
Retrieved on: 
Tuesday, July 7, 2020
Information
Tags: 
Software, Managed care, Health, FDA, Medical devices, Data management, Hospitals, Technology, Articles, Kidney diseases, Cybernetics, Medical specialties, Anatomy, Organ failure, Medical emergencies, Acute kidney injury, Machine learning, Artificial intelligence, Aki, Renal angina, Previse, Dascena
Geotags: 
United States, California
⚠ generated by AI ↴
Organisation: 
PREVISE, DASCENA
Summary
Key Points: 
  • This is the first Breakthrough Device Designation of a cloud-based machine learning algorithm developed for the early detection of AKI.
  • Acute kidney injury commonly affects hospitalized individuals, and if not caught early, can result in dangerous outcomes for patients, said Ritankar Das, chief executive officer of Dascena.
  • Our machine learning algorithm is able to analyze patient vital sign data and determine whether a patient is at risk of developing acute kidney injury.
  • Dascena is developing machine learning diagnostic algorithms to enable early disease intervention and improve care outcomes for patients.


Dascena, Inc., a machine learning diagnostic algorithm company that is targeting early disease intervention to improve patient care outcomes, today announced it has received Breakthrough Device Designation from the U.S. Food and Drug Administration (FDA) for Previse, the company’s algorithm designed to predict acute kidney injury (AKI) more than a full day before patients meet the clinical criteria for diagnosis. This is the first Breakthrough Device Designation of a cloud-based machine learning algorithm developed for the early detection of AKI.

“Acute kidney injury commonly affects hospitalized individuals, and if not caught early, can result in dangerous outcomes for patients,” said Ritankar Das, chief executive officer of Dascena. “Our machine learning algorithm is able to analyze patient vital sign data and determine whether a patient is at risk of developing acute kidney injury. With this technology, we believe we’ll be able to provide physicians with ample time to intervene and prevent long-term kidney injury in their patients.”

A major challenge in the treatment of AKI is that the clinical criteria for recognition are markers of established kidney damage or impaired function. By predicting whether a patient is likely to succumb to AKI before symptoms present, treatment outcomes could be improved. In validation studies, Previse demonstrated higher sensitivity and predictive value than a clinician’s assessment that relied on clinical criteria, and Previse only utilized patient data that were already routinely collected. In a 2018 paper published in the Canadian Journal of Kidney Health and Disease, Dascena reported that Previse predicted AKI 48 hours before onset with 84% percent accuracy and a diagnostic odds ratio of 5.8.

The FDA Breakthrough Device Program is intended to help patients receive more timely access to breakthrough technologies that have the potential to provide more effective treatment or diagnosis for life-threatening or irreversibly debilitating diseases or conditions.

About Previse

Previse is an algorithm that continuously monitors hospitalized patients and can predict acute kidney injury more than a full day before patients meet the clinical criteria for diagnosis, providing clinicians with ample time to intervene and prevent long-term injury.

About Dascena

Dascena is developing machine learning diagnostic algorithms to enable early disease intervention and improve care outcomes for patients. For more information, visit Dascena.com.

Copyright: 
Copyright Business Wire 2020