Dascena’s Previse is designed to predict AKI in patients a day before patients meet the clinical criteria for diagnosis. Credit: Patho / Wiki Commons.

Machine learning diagnostic algorithm company Dascena has received breakthrough device designation from the US Food and Drug Administration (FDA) for Previse, an algorithm for the early detection of acute kidney injury (AKI).

The algorithm is designed to predict AKI in patients a day before patients meet the clinical criteria for diagnosis, the company noted.

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A major challenge in the treatment of AKI is that the clinical criteria for diagnosis are markers of established kidney damage or impaired function.

Previse is expected to improve the treatment outcome by predicting whether a patient is likely to suffer from AKI before symptoms are present.

Dascena said that its algorithm has demonstrated higher sensitivity and predictive value in validation studies compared to clinician’s assessment that relied on clinical criteria.

In a 2018 paper published in the Canadian Journal of Kidney Health and Disease, the company said that Previse predicted AKI 48 hours before onset with 84% accuracy and a diagnostic odds ratio of 5.8.

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Dascena CEO Ritankar Das said: “Acute kidney injury commonly affects hospitalised individuals, and if not caught early, can result in dangerous outcomes for patients.

“Our machine learning algorithm is able to analyse patient vital sign data and determine whether a patient is at risk of developing acute kidney injury. With this technology, we believe we will be able to provide physicians with ample time to intervene and prevent long-term kidney injury in their patients.”

Dascena noted that it is the first time a cloud-based machine learning algorithm developed for the early detection of AKI is granted breakthrough device designation by the FDA.

The agency’s breakthrough device programme is intended to help patients receive more timely access to technologies that have the potential to provide more effective treatment or diagnosis.