Washington, October 25: A new artificial-intelligence-based algorithm may help clinicians predict which patients with COVID-19 face a high risk of developing acute kidney injury (AKI) requiring dialysis.

The research was presented online during ASN Kidney Week 2020 Reimagined October 19-October 25. Also Read | Foods For Cyclists: From Quinoa to Dates, Here Are Five Foods to Have Regularly For Cycling Exercises to Avoid Nutritional Deficiency.

Preliminary reports indicate that acute AKI is common in patients with COVID-19. Using data from more than 3,000 hospitalized patients with COVID-19, investigators at the Icahn School of Medicine at Mount Sinai trained a model based on machine learning, a type of artificial intelligence, to predict AKI that requires dialysis. Only information gathered within the first 48 hours of admission was included, so predictions could be made when patients were admitted. Also Read | Cause of Alzheimer’s Disease Traced to Mutation in Common Enzyme, Says Study.

The model demonstrated high accuracy (AUC of 0.79), and features that were important for prediction included blood levels of creatinine and potassium, age, and vital signs of heart rate and oxygen saturation.

"A machine learning model using admission features had a good performance for prediction of dialysis need. Models like this are potentially useful for resource allocation and planning during future COVID-19 surges," said co-author Lili Chan, MD, MS. "We are in the process of deploying this model into our healthcare systems to help clinicians better care for their patients."

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