New algorithm predicts likelihood of acute kidney injury

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A new artificial-intelligence-based tool can help clinicians predict which hospitalised patients face a high risk of developing acute kidney injury (AKI), say researchers, including one of Indian-origin. AKI is common among hospitalized patients and has a significant impact on morbidity and mortality.

Unfortunately, it's difficult to predict which patients are most likely to develop AKI and could benefit from preventative treatments.

To address this, the research team at Dascena Inc. in the US developed and evaluated a prediction algorithm based on machine learning, a type of artificial intelligence.

The algorithm analysed 7,122 patient encounters and was compared with the standard of care, the Sequential Organ Failure Assessment (SOFA) scoring system.

The Dascena algorithm outperformed SOFA, demonstrating superior performance in predicting acute kidney injury 72 hours prior to onset.

"Through earlier detection, physicians can proactively treat their patients, potentially resulting in better outcomes and limiting the severity of AKI symptoms," said Ritankar Das, president and chief executive officer of Dascena.

This presentation highlights our algorithm's ability to provide this earlier detection over traditional systems, which could profoundly impact AKI management in the hospital setting in the future.

The research is scheduled to be presented online during ASN Kidney Week 2020 Reimagined October 19-25.