Evidence map›Paper›PMID 35175849›Full record

ReviewCirculation research2022

Cardiovascular Disease Screening in Women: Leveraging Artificial Intelligence and Digital Tools.

Demilade A Adedinsewo, Amy W Pollak, Sabrina D Phillips, Taryn L Smith, Anna Svatikova, Sharonne N Hayes, Sharon L Mulvagh, Colleen Norris, Veronique L Roger, Peter A Noseworthy and 2 more

Abstract readReview
In one paragraph

Review in Circulation research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 41 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
41citing papers in PubMed, 2 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

41 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Article
  4. Article
  5. Review
  6. Article
  7. Gender disparities in coronary artery disease: a review of factors influencing clinical outcomes.Netherlands heart journal : monthly journal of the Netherlands Society of Cardiology and the Netherlands Heart Foundation · 2025
    Review
  8. Sensitivity, specificity and prevalencesJournal of oral & facial pain and headache · 2025
    Article
  9. Review
  10. Review
  11. Article
  12. Review
  13. Tailoring cardiovascular risk prediction to females.The Journal of endocrinology · 2025
    Review
  14. Article
  15. Review
  16. Review
  17. Article
  18. Review
  19. Article
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors.

Demilade A AdedinsewoDepartment of Cardiovascular Medicine (D.A.A., A.W.P., S.D.P.), Mayo Clinic, Jacksonville, FL.ORCID 0000-0002-8629-2029
Amy W PollakDepartment of Cardiovascular Medicine (D.A.A., A.W.P., S.D.P.), Mayo Clinic, Jacksonville, FL.
Sabrina D PhillipsDepartment of Cardiovascular Medicine (D.A.A., A.W.P., S.D.P.), Mayo Clinic, Jacksonville, FL.
Taryn L SmithDivision of General Internal Medicine (T.L.S.), Mayo Clinic, Jacksonville, FL.
Anna SvatikovaDepartment of Cardiovascular Diseases (A.S.), Mayo Clinic, Phoenix, AZ.
Sharonne N HayesDepartment of Cardiovascular Medicine (S.N.H., S.L.M., V.L.R., P.A.N.), Mayo Clinic, Rochester, MN.ORCID 0000-0003-3129-362X
Sharon L MulvaghDepartment of Cardiovascular Medicine (S.N.H., S.L.M., V.L.R., P.A.N.), Mayo Clinic, Rochester, MN.
Colleen NorrisCardiovascular Health and Stroke Strategic Clinical Network, Edmonton, Canada (C.N.).ORCID 0000-0002-6793-9333
Veronique L RogerDepartment of Cardiovascular Medicine (S.N.H., S.L.M., V.L.R., P.A.N.), Mayo Clinic, Rochester, MN.ORCID 0000-0002-9347-7865
Peter A NoseworthyDepartment of Cardiovascular Medicine (S.N.H., S.L.M., V.L.R., P.A.N.), Mayo Clinic, Rochester, MN.ORCID 0000-0002-4308-0456
Xiaoxi YaoRobert D. and Patricia E. Kern Center for the Science of Health Care Delivery (X.Y.), Mayo Clinic, Rochester, MN.ORCID 0000-0001-9906-7106
Rickey E CarterDepartment of Quantitative Health Sciences (R.E.C.), Mayo Clinic, Jacksonville, FL.ORCID 0000-0002-0818-273X

Funding

Mayo Clinic Interdisciplinary Women's Health Research ProgramK12HD065987 · NICHD · MAYO CLINIC ROCHESTER · PI KANTARCI, KEJAL · 2010 to 2023
$6.7M
NICHD NIH HHS K12 HD065987
6 · The paper itself

Abstract

Cardiovascular disease remains the leading cause of death in women. Given accumulating evidence on sex- and gender-based differences in cardiovascular disease development and outcomes, the need for more effective approaches to screening for risk factors and phenotypes in women is ever urgent. Public health surveillance and health care delivery systems now continuously generate massive amounts of data that could be leveraged to enable both screening of cardiovascular risk and implementation of tailored preventive interventions across a woman's life span. However, health care providers, clinical guidelines committees, and health policy experts are not yet sufficiently equipped to optimize the collection of data on women, use or interpret these data, or develop approaches to targeting interventions. Therefore, we provide a broad overview of the key opportunities for cardiovascular screening in women while highlighting the potential applications of artificial intelligence along with digital technologies and tools.

Indexed as

Artificial IntelligenceCardiovascular DiseasesDigital TechnologyFemaleHumansLongevityMass ScreeningMenopausePregnancyPregnancy Complications, Cardiovascularartificial intelligencecardiovascular diseasesdeep learningfemalehumanssexwomen's health

Identifiers

PMID35175849
PMCPMC8889564

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.