Literature DB >> 30310997

The Evolving Cardiovascular Disease Risk Scores for Persons with Diabetes Mellitus.

Yanglu Zhao1,2, Nathan D Wong3,4.   

Abstract

PURPOSE OF REVIEW: We briefly introduce the concept and use of cardiovascular disease (CVD) risk scores and review the methodology for CVD risk score development and validation in patients with diabetes. We also discuss CVD risk scores for diabetic patients that have been developed in different countries. RECENT
FINDINGS: Patients with diabetes have a gradient of CVD risk that needs to be accurately assessed. Numerous CVD risk scores for diabetic patients have been created in various settings. The methods to develop risk scores are highly diverse and each choice has its own pros and cons. A well-constructed risk score for diabetic patients may be advocated by guidelines and adopted by healthcare providers to help determine preventive strategies. New risk factors are being investigated in order to improve the predictive accuracy of current risk scores. A suitable CVD risk score for the diabetes population should be accurate, low-cost, and beneficial to outcome. While the performance (accuracy) has all been internally validated, validation on external populations is still needed. Cost-effectiveness and clinical trials demonstrating improvement in outcomes are limited and should be the target of future research.

Entities:  

Keywords:  Cardiovascular disease; Diabetes; Disease risk score

Mesh:

Year:  2018        PMID: 30310997     DOI: 10.1007/s11886-018-1069-5

Source DB:  PubMed          Journal:  Curr Cardiol Rep        ISSN: 1523-3782            Impact factor:   2.931


  48 in total

1.  Development of a new diabetes risk prediction tool for incident coronary heart disease events: the Multi-Ethnic Study of Atherosclerosis and the Heinz Nixdorf Recall Study.

Authors:  Joseph Yeboah; Raimund Erbel; Joseph Chris Delaney; Robin Nance; Mengye Guo; Alain G Bertoni; Matthew Budoff; Susanne Moebus; Karl-Heinz Jöckel; Gregory L Burke; Nathan D Wong; Nils Lehmann; David M Herrington; Stefan Möhlenkamp; Philip Greenland
Journal:  Atherosclerosis       Date:  2014-08-14       Impact factor: 5.162

2.  Risk prediction of major complications in individuals with diabetes: the Atherosclerosis Risk in Communities Study.

Authors:  C M Parrinello; K Matsushita; M Woodward; L E Wagenknecht; J Coresh; E Selvin
Journal:  Diabetes Obes Metab       Date:  2016-06-14       Impact factor: 6.577

3.  Testing for improvement in prediction model performance.

Authors:  Margaret Sullivan Pepe; Kathleen F Kerr; Gary Longton; Zheyu Wang
Journal:  Stat Med       Date:  2013-01-07       Impact factor: 2.373

4.  UKPDS outcomes model 2: a new version of a model to simulate lifetime health outcomes of patients with type 2 diabetes mellitus using data from the 30 year United Kingdom Prospective Diabetes Study: UKPDS 82.

Authors:  A J Hayes; J Leal; A M Gray; R R Holman; P M Clarke
Journal:  Diabetologia       Date:  2013-06-22       Impact factor: 10.122

5.  Prediction of coronary heart disease in middle-aged adults with diabetes.

Authors:  Aaron R Folsom; Lloyd E Chambless; Bruce B Duncan; Adam C Gilbert; James S Pankow
Journal:  Diabetes Care       Date:  2003-10       Impact factor: 19.112

6.  General cardiovascular risk profile for use in primary care: the Framingham Heart Study.

Authors:  Ralph B D'Agostino; Ramachandran S Vasan; Michael J Pencina; Philip A Wolf; Mark Cobain; Joseph M Massaro; William B Kannel
Journal:  Circulation       Date:  2008-01-22       Impact factor: 29.690

Review 7.  Comparative performance of diabetes-specific and general population-based cardiovascular risk assessment models in people with diabetes mellitus.

Authors:  J-B Echouffo-Tcheugui; A P Kengne
Journal:  Diabetes Metab       Date:  2013-09-27       Impact factor: 6.041

8.  Developing and validating a cardiovascular risk score for patients in the community with prior cardiovascular disease.

Authors:  Katrina K Poppe; Rob N Doughty; Sue Wells; Dudley Gentles; Harry Hemingway; Rod Jackson; Andrew J Kerr
Journal:  Heart       Date:  2017-02-23       Impact factor: 5.994

9.  Development and validation of risk prediction equations to estimate future risk of heart failure in patients with diabetes: a prospective cohort study.

Authors:  Julia Hippisley-Cox; Carol Coupland
Journal:  BMJ Open       Date:  2015-09-09       Impact factor: 2.692

10.  Cardiovascular disease: The rise of the genetic risk score.

Authors:  Joshua W Knowles; Euan A Ashley
Journal:  PLoS Med       Date:  2018-03-30       Impact factor: 11.069

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