Cardiovascular Risk Prediction Models: A Scoping Review

Research output: Contribution to conferencePaperpeer-review

4 Citations (Scopus)


Background: The prevention of cardiovascular disease is a public health priority as it is associated with increasing morbidity and mortality worldwide.

Objective: A scoping review of the existing cardiovascular risk prediction models, to provide a basis for suggesting future research directions.

Methods: PubMed and Scopus were searched from 2008 to 2018 for review papers investigating the formulation and effectiveness of risk prediction models for cardiovascular disease.

Results: 229 references were screened of which 4 articles were included in the review, describing development of 436 prediction models. Most of the work reported was from USA and Europe.

Conclusions: Availability of larger datasets from Electronic Health Records for more comprehensive and targeted risk prediction, and advancement in data analysis and modeling methods like machine learning to enable cohort directed approaches, has prompted researchers and clinicians to rethink risk modeling.

Original languageEnglish
Number of pages5
Publication statusPublished - 29 Jan 2019
Event2019 Australasian Computer Science Week Multiconference - Sydney , Australia
Duration: 29 Jan 2019 → …


Conference2019 Australasian Computer Science Week Multiconference
Abbreviated titleACSW 2019
Period29/01/19 → …


  • Cardiovascular Risk
  • public health
  • scoping review
  • cardiovascular disease
  • risk factors
  • data analysis
  • modeling


Dive into the research topics of 'Cardiovascular Risk Prediction Models: A Scoping Review'. Together they form a unique fingerprint.

Cite this