Prediction of cardiovascular disease risk among people with severe mental illness: A cohort study


Autoři: Ruth Cunningham aff001;  Katrina Poppe aff002;  Debbie Peterson aff001;  Susanna Every-Palmer aff003;  Ian Soosay aff004;  Rod Jackson aff002
Působiště autorů: Department of Public Health, University of Otago Wellington, Wellington, New Zealand aff001;  Section of Epidemiology and Biostatistics, School of Population Health, University of Auckland, Auckland, New Zealand aff002;  Department of Psychological Medicine, University of Otago Wellington, Wellington, New Zealand aff003;  School of Medical and Health Sciences, University of Auckland, Auckland, New Zealand aff004
Vyšlo v časopise: PLoS ONE 14(9)
Kategorie: Research Article
doi: 10.1371/journal.pone.0221521

Souhrn

Objective

To determine whether contemporary sex-specific cardiovascular disease (CVD) risk prediction equations underestimate CVD risk in people with severe mental illness from the cohort in which the equations were derived.

Methods

We identified people with severe mental illness using information on prior specialist mental health treatment. This group were identified from the PREDICT study, a prospective cohort study of 495,388 primary care patients aged 30 to 74 years without prior CVD that was recently used to derive new CVD risk prediction equations. CVD risk was calculated in participants with and without severe mental illness using the new equations and the predicted CVD risk was compared with observed risk in the two participant groups using survival methods.

Results

28,734 people with a history of recent contact with specialist mental health services, including those without a diagnosis of a psychotic disorder, were identified in the PREDICT cohort. They had a higher observed rate of CVD events compared to those without such a history. The PREDICT equations underestimated the risk for this group, with a mean observed:predicted risk ratio of 1.29 in men and 1.64 in women. In contrast the PREDICT algorithm performed well for those without mental illness.

Conclusions

Clinicians using CVD risk assessment tools that do not include severe mental illness as a predictor could by underestimating CVD risk by about one-third in men and two-thirds in women in this patient group. All CVD risk prediction equations should be updated to include mental illness indicators.

Klíčová slova:

Medicine and health sciences – Cardiovascular medicine – Cardiovascular diseases – Cardiovascular diseases in women – Mental health and psychiatry – Mood disorders – Bipolar disorder – Schizophrenia – Psychoses – Epidemiology – Medical risk factors – Women's health – Health care – Primary care


Zdroje

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PLOS One


2019 Číslo 9

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