AUTHOR=Berry Alexandra , Drake Richard J. , Webb Roger T. , Ashcroft Darren M. , Carr Matthew J. , Yung Alison R.
TITLE=Investigating the Agreement Between Cardiovascular Disease Risk Calculators Among People Diagnosed With Schizophrenia
JOURNAL=Frontiers in Psychiatry
VOLUME=9
YEAR=2018
URL=https://www.frontiersin.org/journals/psychiatry/articles/10.3389/fpsyt.2018.00685
DOI=10.3389/fpsyt.2018.00685
ISSN=1664-0640
ABSTRACT=Background: People diagnosed with schizophrenia have a much reduced life expectancy compared to the general population, and a more than doubled risk of dying from cardiovascular disease (CVD). Existing CVD risk calculators can be used to detect people with an elevated predicted risk of CVD to inform interventions to reduce risk.
Aims: This study aimed to compare four different risk calculators for 10-year predicted CVD risk in a sample of people with schizophrenia.
Methods: Thirty participants with a diagnosis of schizophrenia spectrum disorders living within Greater Manchester, United Kingdom took part. Ten-year predicted cardiovascular risk scores were calculated using four different models: QRISK3, Framingham, PRIMROSE BMI, and PRIMROSE lipid. Risk estimates and classified risk categories were compared.
Results: QRISK3 identified 11 (39%) as having >10% risk of a CV event within 10 years, 4 (14%) of whom exceeded 20%. The Framingham model identified 4 (14%) as exceeding 10%, none of whom exceeded 20%. PRIMROSE risk calculators identified no participants as having >10% risk of a CV event within 10 years. Pairwise concordance correlation coefficients between types of model ranged 0.22–0.77. Mean (± SD) age was 40 (± 10) years but QRISK3's mean “Heart age” was 58 (± 14) years.
Conclusion: Risk calculators generate differing predicted CVD risk scores for patients with schizophrenia. Using one risk calculator might yield different recommended monitoring and treatment plans compared to another. Clinicians should therefore take into account other patient-related factors, such as patients' preferences and other underlying physical conditions when making treatment decisions.