Standard cardiovascular disease risk algorithms underestimate the risk of cardiovascular disease in schizophrenia: evidence from a national primary care database

McLean, G., Langan-Martin, J. , Martin, D. J., Guthrie, B., Mercer, S. W. and Smith, D. J. (2014) Standard cardiovascular disease risk algorithms underestimate the risk of cardiovascular disease in schizophrenia: evidence from a national primary care database. Schizophrenia Research, 159(1), pp. 176-181. (doi: 10.1016/j.schres.2014.07.022)

Abstract

Background: Schizophrenia is associated with increased cardiovascular mortality. Although cardiovascular disease (CVD) risk prediction algorithms are widely in the general population, their utility for patients with schizophrenia is unknown.<p></p> Methods: A primary care dataset was used to compare CVD risk scores (Joint British Societies (JBS) score), cardiovascular risk factors, rates of pre-existing CVD and age of first diagnosis of CVD for schizophrenia (n=1,997) relative to population controls (n=215,165).<p></p> Results: Pre-existing rates of CVD and the recording of risk factors for those without CVD were higher in the schizophrenia cohort in the younger age groups, for both genders. Those with schizophrenia were more likely to have a first diagnosis of CVD at a younger age, with nearly half of men with schizophrenia plus CVD diagnosed under the age of 55 (schizophrenia men 46.1% vs. control men 34.8%, p<0.001; schizophrenia women 28.9% vs. control women 23.8%, p<0.001). However, despite high rates of CVD risk factors within the schizophrenia group, only a very small percentage (3.2% of men and 7.5% of women) of those with schizophrenia under age 55 were correctly identified as high risk for CVD according to the JBS risk algorithm.<p></p> Conclusion: The JBS2 risk score identified only a small proportion of individuals with schizophrenia under the age of 55 as being at high risk of CVD, despite high rates of risk factors and high rates of first diagnosis of CVD within this age group. The validity of CVD risk prediction algorithms for schizophrenia needs further research.

• Item Type: Articles
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Martin, Dr Daniel and Smith, Professor Daniel and Mercer, Professor Stewart and Langan-Martin, Dr Julie and Guthrie, Prof Bruce and McLean, Dr Gary
• Authors: McLean, G., Langan-Martin, J., Martin, D. J., Guthrie, B., Mercer, S. W., and Smith, D. J.
• College/School: College of Medical Veterinary and Life Sciences > School of Health & Wellbeing > Mental Health and Wellbeing; College of Medical Veterinary and Life Sciences > School of Health & Wellbeing > General Practice and Primary Care
• Journal Name: Schizophrenia Research
• Publisher: Elsevier
• ISSN: 0920-9964
• ISSN (Online): 1573-2509