Investigating the Added Value of Beck’s Depression Inventory in Atherosclerosis Prediction: Lessons from Paracelsus 10,000

Author:

Dienhart Christiane1,Aigner Elmar1,Iglseder Bernhard2ORCID,Frey Vanessa3,Gostner Isabella3,Langthaler Patrick345,Paulweber Bernhard16,Trinka Eugen378,Wernly Bernhard910ORCID

Affiliation:

1. Department of Internal Medicine I, Paracelsus Medical University, 5020 Salzburg, Austria

2. Department of Geriatric Medicine, Christian Doppler University Hospital, Paracelsus Medical University, 5020 Salzburg, Austria

3. Department of Neurology, Christian Doppler University Hospital, Paracelsus Medical University and Centre for Cognitive Neuroscience, Affiliated Member of the European Reference Network EpiCARE, 5020 Salzburg, Austria

4. Department of Artificial Intelligence and Human Interfaces, Paris Lodron University of Salzburg, 5020 Salzburg, Austria

5. Team Biostatistics and Big Medical Data, IDA Lab Salzburg, Paracelsus Medical University Salzburg, 5020 Salzburg, Austria

6. Obesity Research Unit, Paracelsus Medical University, 5020 Salzburg, Austria

7. Neuroscience Institute, Christian Doppler University Hospital, Paracelsus Medical University and Centre for Cognitive Neuroscience, Affiliated Member of the European Reference Network EpiCARE, 5020 Salzburg, Austria

8. Department of Public Health, Health Services Research and Health Technology Assessment, UMIT—University for Health Sciences, Medical Informatics and Technology, 6060 Hall in Tirol, Austria

9. Department of Internal Medicine I, Oberndorf Hospital, 5110 Salzburg, Austria

10. Institute for General and Preventive Medicine, Paracelsus Medical University, 5020 Salzburg, Austria

Abstract

Background: Depression is the most common mental illness worldwide and generates an enormous health and economic burden. Furthermore, it is known to be associated with an elevated risk of arteriosclerotic cardiovascular diseases (ASCVD), particularly stroke. However, it is not a factor reflected in many ASCVD risk models, including SCORE2. Thus, we analysed the relationship between depression, ASCVD and SCORE2 in our cohort. Methods: We analysed 9350 subjects from the Paracelsus 10,000 cohort, who underwent both a carotid artery ultrasound and completed a Beck Depression Inventory (BDI) screening. Patients were categorised binomially based on the BDI score. Atherosclerotic carotid plaque or absence was dichotomised for logistic regression modelling. Odds ratios and adjusted relative risks were calculated using Stata. Results: Subjects with an elevated BDI (≥14) had higher odds for carotid plaques compared to subjects with normal BDI, especially after adjusting for classical risk factors included in SCORE2 (1.21; 95%CI 1.03–1.43, p = 0.023). The adjusted relative risk for plaques was also increased (1.09; 95%CI 1.01–1.18, p = 0.021). Subgroup analysis showed an increased odds of plaques with increases in depressive symptoms, particularly in women and patients ≤55 yrs. Conclusions: In our cohort, the BDI score is associated with subclinical atherosclerosis beyond classical risk factors. Thus, depression might be an independent risk factor which may improve risk stratification if considered in ASCVD risk prediction models, such as SCORE2. Furthermore, reminding clinicians to take mental health into consideration to identify individuals at increased atherosclerosis risk may provide added opportunities to address measures which can reduce the risk of ASCVD.

Funder

Land Salzburg, the Salzburger Landeskliniken

Paracelsus Medical University Salzburg

Austrian health insurance

Bayer

AstraZeneca

Sanofi-Aventis

Boehringer-Ingelheim

Publisher

MDPI AG

Reference66 articles.

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