Cover Kidney News
Volume/Issue:
Volume 11: Issue 2
Page:
22
Publication Date:
01 Feb 2019
Online Publication Date:
07 Feb 2019
  • 1.

    Ravizza S, et al. Predicting the early risk of chronic kidney disease in patients with diabetes using real-world data. Nature Medicine 2019; 25:57–59.

    • Crossref
    • Search Google Scholar
    • Export Citation
Editorial Type:
Industry Spotlight

Diabetic Kidney Disease Prediction

Volume/Issue:
Volume 11: Issue 2
Publication Date:
01 Feb 2019
Page:
22
Restricted access

Roche and IBM have teamed up to parse half a million electronic health records (EHRs) to create a predictive algorithm for patients with early risk of chronic kidney disease (CKD) related to diabetes. The industry duo developed the algorithm based on real-world data.

Age, body mass index, and glomerular filtration rate as well as concentrations of creatinine, albumin, glucose, and hemoglobin (HbA1c) were selected as important predictors on the basis of “a data-driven and medical selection for the study,” according to the paper, published in Nature Medicine (1). CKD was defined as a microvascular long-term complication
Save