{
  "abstract": "Purpose: Cardiovascular disease remains a leading cause of morbidity and mortality in women. Cardiovascular risk prediction models are widely used to guide preventative management, although many do not incorporate female-specific risk factors. The aim of this review is to identify published cardiovascular risk prediction models for women or those which include female-specific predictors and to summarize the predictors and model performance. Methods: The protocol was developed following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA-P) guidelines. The protocol has been registered in PROSPERO (CRD420261420766). An update of the systematic review by Baart et al. will be performed by searching MEDLINE and EMBASE from July 27 2017 to May 2026 to identify primary articles reporting on the development and/or validation of models predicting incident cardiovascular disease in women. Data on model predictors, performance, validation and clinical usability will be extracted. Risk of bias will be assessed using PROBAST+AI. Findings will be synthesized descriptively although quantitative synthesis will be considered when sufficiently comparable studies are available. Conclusions: This systematic review will provide an updated synthesis of cardiovascular risk prediction models in women and summarize how female-specific risk factors are incorporated into contemporary risk assessment.",
  "abstract_shown": true,
  "affiliations": [
    "Department of Medicine, The Ottawa Hospital, Ottawa, Ontario, Canada",
    "The University of Ottawa, Ottawa, Ontario, Canada",
    "Library Services, The Ottawa Hospital, Ottawa, Ontario, Canada",
    "Bruyere Research Institute, Ottawa, Ontario, Canada"
  ],
  "article_type": "Study Protocol",
  "arxiv": null,
  "author_total": 8,
  "authors": [
    {
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        0
      ],
      "name": "Cairina Frank"
    },
    {
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        1
      ],
      "name": "Hadi Tehfe"
    },
    {
      "affs": [
        2
      ],
      "name": "Charles Ghanem"
    },
    {
      "affs": [
        3
      ],
      "name": "Jade Choo-Foo"
    },
    {
      "name": "Ramtin Hakimjavadi"
    },
    {
      "name": "Hawre Jalal"
    },
    {
      "name": "Risa Shorr"
    },
    {
      "name": "Daniel Kobewka"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/e8f8p5e9hevd9.bib",
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  "doi": "10.1371/journal.pone.0360860",
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    "1932-6203"
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  "licence": "CC-BY-4.0",
  "licence_label": "CC BY 4.0",
  "licence_source": "journal",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
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  "native_subjects": [
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      "openalex",
      "2739|Health Promotion and Cardiovascular Prevention"
    ],
    [
      "plos",
      "/Medicine and health sciences/Cardiology/Cardiovascular medicine/Cardiovascular diseases"
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      "/Medicine and health sciences/Cardiology/Cardiovascular medicine/Cardiovascular diseases/Cardiovascular disease risk"
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      "plos",
      "/Medicine and health sciences/Cardiology/Cardiovascular medicine/Cardiovascular diseases/Cardiovascular diseases in women"
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    [
      "plos",
      "/Medicine and health sciences/Medical conditions/Cardiovascular diseases/Cardiovascular disease risk"
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    [
      "plos",
      "/Medicine and health sciences/Medical conditions/Cardiovascular diseases/Cardiovascular diseases in women"
    ],
    [
      "plos",
      "/Medicine and health sciences/Vascular medicine/Blood pressure/Hypertension/Hypertensive disorders in pregnancy"
    ],
    [
      "plos",
      "/Medicine and health sciences/Women's health/Cardiovascular diseases in women"
    ],
    [
      "plos",
      "/Medicine and health sciences/Women's health/Maternal health/Pregnancy/Hypertensive disorders in pregnancy"
    ],
    [
      "plos",
      "/Medicine and health sciences/Women's health/Obstetrics and gynecology/Pregnancy/Hypertensive disorders in pregnancy"
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      "plos",
      "/Physical sciences/Mathematics/Statistics/Statistical methods/Forecasting"
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      "plos",
      "/Physical sciences/Mathematics/Statistics/Statistical methods/Metaanalysis"
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      "/Research and analysis methods/Mathematical and statistical techniques/Statistical methods/Forecasting"
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      "plos",
      "/Research and analysis methods/Mathematical and statistical techniques/Statistical methods/Metaanalysis"
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      "/Research and analysis methods/Research assessment/Systematic reviews"
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  "pdf_url": "https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0360860&type=printable",
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-15",
  "publisher": "Public Library of Science",
  "ris": "https://research.draconitic.com/paper/e8f8p5e9hevd9.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:17:23Z",
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      "url": "https://doi.org/10.1371/journal.pone.0360860"
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  "subjects": [
    {
      "field": "mathematics",
      "origin": "plos:statistical methods",
      "subfield": "statistics"
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    {
      "field": "medicine",
      "origin": "plos:cardiovascular diseases",
      "subfield": "cardiovascular"
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    {
      "field": "medicine",
      "origin": "plos:women's health",
      "subfield": "reproductive-child"
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  "title": "Cardiovascular risk prediction models for women: A systematic review protocol",
  "title_text": "Cardiovascular risk prediction models for women: A systematic review protocol",
  "type": "peer-reviewed",
  "updated_at": "2026-10-30T12:17:23Z",
  "url": "https://research.draconitic.com/paper/e8f8p5e9hevd9",
  "venue": "PLOS One",
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