TY - JOUR
T1 - Cardiovascular risk indicators among depressed persons
T2 - A special case?
AU - van Zutphen, Elisabeth M.
AU - Kok, Almar A.L.
AU - Muller, Majon
AU - Oude Voshaar, Richard C.
AU - Rhebergen, Didi
AU - Huisman, Martijn
AU - Beekman, Aartjan T.F.
N1 - Funding Information:
The infrastructure for the NESDA study ( www.nesda.nl ) has been funded through the Geestkracht program of the Netherlands Organization for Health Research and Development (ZonMw, grant number 10-000-1002 ) and by participating universities and mental health care organizations (Amsterdam University Medical Center location VUmc, GGZ inGeest, Leiden University Medical Center, University Medical Center Groningen, University of Groningen, Lentis, GGZ Friesland, GGZ Drenthe, Rob Giel Onderzoekcentrum). The infrastructure for NESDO ( www.nesdo.onderzoek.io ) has been funded through the Fonds NutsOhra (project 0701-065 ), Stichting tot Steun VCVGZ, NARSAD The Brain and Behavior Research Fund (Grand Id 41080 ), and the participating universities and mental healthcare organizations (VU University Medical Center, Leiden University Medical Center, University Medical Center Groningen, Radboud University Nijmegen Medical Center, GGZ Ingeest, GGNet, GGZ Nijmegen, GGZ Rivierduinen, Lentis and Parnassia). The authors received no specific grant from any funding agency, commercial or not-for-profit sectors.
Publisher Copyright:
© 2023
PY - 2023/5/15
Y1 - 2023/5/15
N2 - Background: Traditional cardiovascular risk indicators only partially explain cardiovascular risks in depressed persons. Depressed persons may exhibit a profile of cardiovascular risk indicators that goes beyond traditional cardiovascular risk indicators, such as symptom severity, insomnia, loneliness and neuroticism, yet research on the added value of these depression-related characteristics in predicting cardiovascular risks of depressed persons is scarce. Methods: Data from N = 1028 depressed Dutch adults without prevalent CVD were derived from two longitudinal depression cohort studies. The outcome was medication-confirmed self-reported CVD. Fifteen depression-related clinical and psychological characteristics were included and tested against traditional cardiovascular risk indicators. Data were analysed using Cox regression models. Incremental values of these characteristics were calculated using c-statistics. Results: After a median follow-up of 65.3 months, 12.7% of the participants developed CVD. Only anxiety and depressive symptom severity were associated with incident CVD beyond traditional cardiovascular risk indicators. The c-statistic of the model with traditional cardiovascular risk indicators was 85.47%. This increased with 0.56 or 0.33 percentage points after inclusion of anxiety or depression severity, respectively. Limitations: Other relevant depression-related characteristics were not available in the datasets used. Conclusion: Anxiety and depressive symptom severity were indicative of an increased cardiovascular risk. Including these as additional risk indicators barely improved the ability to assess cardiovascular risks in depressed persons. Although traditional cardiovascular risk indicators performed well in depressed persons, existing risk prediction algorithms need to be validated in depressed persons.
AB - Background: Traditional cardiovascular risk indicators only partially explain cardiovascular risks in depressed persons. Depressed persons may exhibit a profile of cardiovascular risk indicators that goes beyond traditional cardiovascular risk indicators, such as symptom severity, insomnia, loneliness and neuroticism, yet research on the added value of these depression-related characteristics in predicting cardiovascular risks of depressed persons is scarce. Methods: Data from N = 1028 depressed Dutch adults without prevalent CVD were derived from two longitudinal depression cohort studies. The outcome was medication-confirmed self-reported CVD. Fifteen depression-related clinical and psychological characteristics were included and tested against traditional cardiovascular risk indicators. Data were analysed using Cox regression models. Incremental values of these characteristics were calculated using c-statistics. Results: After a median follow-up of 65.3 months, 12.7% of the participants developed CVD. Only anxiety and depressive symptom severity were associated with incident CVD beyond traditional cardiovascular risk indicators. The c-statistic of the model with traditional cardiovascular risk indicators was 85.47%. This increased with 0.56 or 0.33 percentage points after inclusion of anxiety or depression severity, respectively. Limitations: Other relevant depression-related characteristics were not available in the datasets used. Conclusion: Anxiety and depressive symptom severity were indicative of an increased cardiovascular risk. Including these as additional risk indicators barely improved the ability to assess cardiovascular risks in depressed persons. Although traditional cardiovascular risk indicators performed well in depressed persons, existing risk prediction algorithms need to be validated in depressed persons.
KW - Cardiovascular disease
KW - Depression
KW - Risk prediction
U2 - 10.1016/j.jad.2023.02.092
DO - 10.1016/j.jad.2023.02.092
M3 - Article
C2 - 36842656
AN - SCOPUS:85149292070
SN - 0165-0327
VL - 329
SP - 335
EP - 342
JO - Journal of Affective Disorders
JF - Journal of Affective Disorders
ER -