Literature DB >> 25267049

Predicted 10-year risk of cardiovascular disease is influenced by the risk equation adopted: a cross-sectional analysis.

Benjamin J Gray1, Richard M Bracken1, Daniel Turner1, Kerry Morgan2, Stephen D Mellalieu3, Michael Thomas4, Sally P Williams5, Meurig Williams2, Sam Rice2, Jeffrey W Stephens6.   

Abstract

BACKGROUND: Validated risk equations are currently recommended to assess individuals to determine those at 'high risk' of cardiovascular disease (CVD). However, there is no longer a risk 'equation of choice'. AIM: This study examined the differences between four commonly-used CVD risk equations. DESIGN AND
SETTING: Cross-sectional analysis of individuals who participated in a workplace-based risk assessment in Carmarthenshire, south Wales.
METHOD: Analysis of 790 individuals (474 females, 316 males) with no prior diagnosis of CVD or diabetes. Ten-year CVD risk was predicted by entering the relevant variables into the QRISK2, Framingham Lipids, Framingham BMI, and JBS2 risk equations.
RESULTS: The Framingham BMI and JBS2 risk equations predicted a higher absolute risk than the QRISK2 and Framingham Lipids equations, and CVD risk increased concomitantly with age irrespective of which risk equation was adopted. Only a small proportion of females (0-2.1%) were predicted to be at high risk of developing CVD using any of the risk algorithms. The proportion of males predicted at high risk ranged from 5.4% (QRISK2) to 20.3% (JBS2). After age stratification, few differences between isolated risk factors were observed in males, although a greater proportion of males aged ≥50 years were predicted to be at 'high risk' independent of risk equation used.
CONCLUSIONS: Different risk equations can influence the predicted 10-year CVD risk of individuals. More males were predicted at 'high risk' using the JBS2 or Framingham BMI equations. Consideration should also be given to the number of isolated risk factors, especially in younger adults when evaluating CVD risk. © British Journal of General Practice 2014.

Entities:  

Keywords:  cardiovascular diseases; decision support techniques; prevention and control; primary care; risk

Mesh:

Substances:

Year:  2014        PMID: 25267049      PMCID: PMC4173726          DOI: 10.3399/bjgp14X681805

Source DB:  PubMed          Journal:  Br J Gen Pract        ISSN: 0960-1643            Impact factor:   5.386


  18 in total

1.  Re-assessing the contribution of serum total cholesterol, blood pressure and cigarette smoking to the aetiology of coronary heart disease: impact of regression dilution bias.

Authors:  Jonathan R Emberson; Peter H Whincup; Richard W Morris; Mary Walker
Journal:  Eur Heart J       Date:  2003-10       Impact factor: 29.983

2.  JBS 2: Joint British Societies' guidelines on prevention of cardiovascular disease in clinical practice.

Authors: 
Journal:  Heart       Date:  2005-12       Impact factor: 5.994

3.  Cardiovascular risk and diabetes. Are the methods of risk prediction satisfactory?

Authors:  Jeffrey W Stephens; Gareth Ambler; Patrick Vallance; D John Betteridge; Steve E Humphries; Steven J Hurel
Journal:  Eur J Cardiovasc Prev Rehabil       Date:  2004-12

4.  Adding social deprivation and family history to cardiovascular risk assessment: the ASSIGN score from the Scottish Heart Health Extended Cohort (SHHEC).

Authors:  Mark Woodward; Peter Brindle; Hugh Tunstall-Pedoe
Journal:  Heart       Date:  2006-11-07       Impact factor: 5.994

5.  The diabetes risk score: a practical tool to predict type 2 diabetes risk.

Authors:  Jaana Lindström; Jaakko Tuomilehto
Journal:  Diabetes Care       Date:  2003-03       Impact factor: 19.112

6.  Estimation of ten-year risk of fatal cardiovascular disease in Europe: the SCORE project.

Authors:  R M Conroy; K Pyörälä; A P Fitzgerald; S Sans; A Menotti; G De Backer; D De Bacquer; P Ducimetière; P Jousilahti; U Keil; I Njølstad; R G Oganov; T Thomsen; H Tunstall-Pedoe; A Tverdal; H Wedel; P Whincup; L Wilhelmsen; I M Graham
Journal:  Eur Heart J       Date:  2003-06       Impact factor: 29.983

7.  Lipid modification: cardiovascular risk assessment and the modification of blood lipids for the primary and secondary prevention of cardiovascular disease.

Authors:  J Robson
Journal:  Heart       Date:  2008-08-13       Impact factor: 5.994

8.  Predicting cardiovascular risk in England and Wales: prospective derivation and validation of QRISK2.

Authors:  Julia Hippisley-Cox; Carol Coupland; Yana Vinogradova; John Robson; Rubin Minhas; Aziz Sheikh; Peter Brindle
Journal:  BMJ       Date:  2008-06-23

9.  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

10.  Effect of a multifactorial intervention on mortality in type 2 diabetes.

Authors:  Peter Gaede; Henrik Lund-Andersen; Hans-Henrik Parving; Oluf Pedersen
Journal:  N Engl J Med       Date:  2008-02-07       Impact factor: 91.245

View more
  5 in total

1.  Cardiovascular risk prediction: balancing complexity against simple practicality.

Authors:  Mikhail S Dzeshka; Paramjit S Gill; Gregory Y H Lip
Journal:  Br J Gen Pract       Date:  2015-01       Impact factor: 5.386

2.  Agreement between laboratory-based and non-laboratory-based Framingham risk score in Southern Iran.

Authors:  Fatemeh Rezaei; Mozhgan Seif; Abdullah Gandomkar; Mohammad Reza Fattahi; Jafar Hasanzadeh
Journal:  Sci Rep       Date:  2021-05-24       Impact factor: 4.379

3.  10-Year Cardiovascular Disease Risk Estimation Based on Lipid Profile-Based and BMI-Based Framingham Risk Scores across Multiple Sociodemographic Characteristics: The Malaysian Cohort Project.

Authors:  Boekhtiar Borhanuddin; Azmawati Mohd Nawi; Shamsul Azhar Shah; Noraidatulakma Abdullah; Syed Zulkifli Syed Zakaria; Mohd Arman Kamaruddin; Chandralekah S Velu; Norliza Ismail; Mohd Shaharom Abdullah; Salywana Ahmad Kamat; Afifah Awang; Mariatul Akma Hamid; Rahman Jamal
Journal:  ScientificWorldJournal       Date:  2018-07-17

4.  Estimating the burden of cardiovascular risk in community dwellers over 40 years old in South Africa, Kenya, Burkina Faso and Ghana.

Authors:  Ryan G Wagner; Nigel J Crowther; Lisa K Micklesfield; Palwende Romauld Boua; Engelbert A Nonterah; Felistas Mashinya; Shukri F Mohamed; Gershim Asiki; Stephen Tollman; Michèle Ramsay; Justine I Davies
Journal:  BMJ Glob Health       Date:  2021-01

5.  Response bias to a randomised controlled trial of a lifestyle intervention in people at high risk of cardiovascular disease: a cross-sectional analysis.

Authors:  Adam Bayley; Daniel Stahl; Mark Ashworth; Derek G Cook; Peter H Whincup; Janet Treasure; Anne Greenough; Katie Ridge; Kirsty Winkley; Khalida Ismail
Journal:  BMC Public Health       Date:  2018-09-04       Impact factor: 3.295

  5 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.