{
  "abstract": "With novel treatment strategies available to delay or prevent kidney failure, early identification of individuals at the highest risk is a key priority to improve health outcomes and reduce healthcare costs.1 The kidney failure risk equation, calculated using age, sex, estimated glomerular filtration rate, and urine albumin to creatinine ratio (uACR), is the most extensively validated and widely used kidney failure prognostic model in patients with chronic kidney disease2 3; however, suboptimal uACR testing limits its implementation.4 5 In a large observational cohort study published in BMJ Medicine (doi:10.1136/bmjmed-2025-001950), Cleary and colleagues developed a risk prediction model for kidney failure at five years, in individuals with chronic kidney disease that uses routinely collected data and does not require uACR testing.6",
  "authors": [
    {
      "affiliations": [
        "Population Health and Genomics, University of Dundee, Dundee, UK"
      ],
      "name": "Heather Y Walker"
    },
    {
      "affiliations": [
        "School of Cardiovascular and Metabolic Health, University of Glasgow, Glasgow, UK",
        "Glasgow Renal and Transplant Unit, NHS Greater Glasgow and Clyde, Glasgow, UK"
      ],
      "name": "Jennifer S Lees"
    }
  ],
  "title": "Predicting kidney failure risk without albuminuria: implications in chronic kidney disease",
  "uid": "efa187b4-cd23-5b50-b016-b1e04417e26c"
}