{
  "abstract": "Background Early identification of patients at risk of heart failure (HF) provides opportunities for preventative management. Though models have been developed to predict HF incidence, their validation remains unclear. Our objective was to summarise the performance, as observed in validation studies, of risk prediction models for incident HF.Methods In addition to articles from three previous systematic reviews, a search in Medline and Embase from 2014 to 2025 identified derivation or validation studies for incident HF prediction models. Performance was assessed in models validated in ≥1 cohort, with random-effects meta-analyses used to pool discrimination measures, and calibration descriptively summarised. We used the Prediction Model Risk Of Bias Assessment Tool to assess risk of bias in individual studies and the Grading of Recommendations, Assessment, Development and Evaluation approach to assess certainty in inferences drawn from the evidence.Results From 24 531 publications identified, 76 studies representing 238 models were included. Risk of bias was high in 82.9% of assessments. With moderate to high certainty, among 64 models validated in at least one cohort, four models had moderate and eight models had high discrimination. In patients with low predicted risk, calibration may have been adequate. The Predicting Risk of CVD EVENTs (PREVENT), Atherosclerosis Risk in Communities (ARIC), and Multi-Ethnic Study of Atherosclerosis (MESA) models were most promising for further validation and impact studies. Among externally validated models, 14 were derived using machine learning, six incorporated novel biomarkers such as proteomics and polygenic risk scores, and nine included measures of social determinants of health as predictors.Conclusions The PREVENT, ARIC and MESA risk scores demonstrate promising performance and should be prioritised for further validation and progression to impact studies.PROSPERO registration number CRD42021266756.",
  "authors": [
    {
      "affiliations": [
        "Ted Rogers Centre for Heart Research, University Health Network, Toronto, Ontario, Canada",
        "School of Medicine, Queen’s University, Kingston, Ontario, Canada"
      ],
      "name": "Jose Miguel Navarro"
    },
    {
      "affiliations": [
        "Schulich Heart Program, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada"
      ],
      "name": "Barbara Stella Doumouras"
    },
    {
      "affiliations": [
        "Ted Rogers Centre for Heart Research, University Health Network, Toronto, Ontario, Canada"
      ],
      "name": "William Douglas"
    },
    {
      "affiliations": [
        "Ted Rogers Centre for Heart Research, University Health Network, Toronto, Ontario, Canada"
      ],
      "name": "Paul Tieu"
    },
    {
      "affiliations": [
        "Ted Rogers Centre for Heart Research, University Health Network, Toronto, Ontario, Canada"
      ],
      "name": "Veronica Chan"
    },
    {
      "affiliations": [
        "Ted Rogers Centre for Heart Research, University Health Network, Toronto, Ontario, Canada"
      ],
      "name": "Tsz Hin Alexander Lau"
    },
    {
      "affiliations": [
        "Ted Rogers Centre for Heart Research, University Health Network, Toronto, Ontario, Canada"
      ],
      "name": "David Bobrowski"
    },
    {
      "affiliations": [
        "Ted Rogers Centre for Heart Research, University Health Network, Toronto, Ontario, Canada"
      ],
      "name": "Clarissa Yu"
    },
    {
      "affiliations": [
        "Ted Rogers Centre for Heart Research, University Health Network, Toronto, Ontario, Canada",
        "Division of Cardiology, Western University, London, Ontario, Canada"
      ],
      "name": "Chang (Nancy) Wang"
    },
    {
      "affiliations": [
        "Ted Rogers Centre for Heart Research, University Health Network, Toronto, Ontario, Canada"
      ],
      "name": "Mohamed Adam"
    },
    {
      "affiliations": [
        "Ted Rogers Centre for Heart Research, University Health Network, Toronto, Ontario, Canada"
      ],
      "name": "Joshua G Lee"
    },
    {
      "affiliations": [
        "Department of Medicine, Harvard Medical School, Boston, Massachusetts, USA",
        "Division of Cardiology, Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA"
      ],
      "name": "Jennifer E Ho"
    },
    {
      "affiliations": [
        "National Heart Lung and Blood Institute Framingham Heart Study, Framingham, Massachusetts, USA"
      ],
      "name": "Daniel Levy"
    },
    {
      "affiliations": [
        "Division of Cardiology, Women’s College Hospital, Toronto, Ontario, Canada",
        "Department of Medicine, University of Toronto, Toronto, Ontario, Canada"
      ],
      "name": "Husam Abdel-Qadir"
    },
    {
      "affiliations": [
        "Department of Medicine, University of Toronto, Toronto, Ontario, Canada",
        "Peter Munk Cardiac Centre, Toronto General Hospital, Toronto, Ontario, Canada"
      ],
      "name": "Heather Ross"
    },
    {
      "affiliations": [
        "Ted Rogers Centre for Heart Research, University Health Network, Toronto, Ontario, Canada",
        "Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, Ontario, Canada"
      ],
      "name": "Farid Foroutan"
    }
  ],
  "title": "Risk prediction models for incident heart failure: a systematic review and meta-analysis",
  "uid": "5c3e2a70-9fa4-5168-877f-04619278c2fd"
}