Journal Article Ahead of print 1 citation
PubMed: 42684053 DOI: 10.1161/JAHA.126.049492
Post-traumatic Psychopathology and Cardiovascular Risk: A Danish Case-Control Study of Sex-Specific Associations.
J Am Heart Assoc
Authors: Jennifer A Sumner, Anthony J Rosellini, Péter Szentkúti, Erzsébet Horváth-Puhó, Hans Erik Bøtker, Timothy L Lash, Paula P Schnurr, Sandro Galea, Henrik Toft Sørensen, Jaimie L Gradus
Affiliations
- Department of Psychology University of California, Los Angeles Los Angeles CA USA.
- Department of Epidemiology Boston University School of Public Health Boston MA USA.
- Department of Clinical Epidemiology and Center for Population Medicine Aarhus University Hospital and Aarhus University Aarhus Denmark.
- Department of Clinical Medicine Aarhus University Hospital and Aarhus University Aarhus Denmark.
- Department of Epidemiology, Rollins School of Public Health Emory University Atlanta GA USA.
- National Center for PTSD Executive Division White River Junction VT USA.
- Department of Psychiatry Geisel School of Medicine at Dartmouth Hanover NH USA.
- Washington University School of Public Health Saint Louis MO USA.
- Department of Epidemiology Boston University School of Public Health Boston MA USA. Department of Clinical Epidemiology and Center for Population Medicine Aarhus University Hospital and Aarhus University Aarhus Denmark.
- Department of Psychiatry Boston University School of Medicine Boston MA USA.
Abstract
BACKGROUND
There is increasing recognition that trauma exposure and related psychiatric consequences predict cardiovascular disease risk. However, most research has specifically examined post-traumatic stress disorder-despite evidence that a range of psychiatric disorders may follow trauma. We applied machine learning to identify key post-traumatic psychiatric predictors of incident major adverse cardiac and cerebrovascular events (MACCE) in a population-based cohort.
METHODS
We conducted a case-control study of adults aged ≥18 years, nested within a trauma-exposed cohort of all Denmark residents from 1995 to 2018. Cases (n=43 994) experienced MACCE (non-fatal myocardial infarction, non-fatal stroke, coronary revascularization, cardiovascular death) between 1995 and 2019. Controls (n=175 872) were matched 4:1 on MACCE date, sex, year of trauma, and age at trauma. Machine learning model predictors included a range of psychiatric disorders diagnosed ≤3 years following trauma. Sex-stratified machine learning models were trained using extreme gradient boosting (men: n=91 111; women: n=84 781) and tested in hold-out datasets (men: n=22 777; women: n=21 197). We identified the 15 most important psychiatric disorder predictors of MACCE using Shapley Additive Explanations values.
RESULTS
For men and women, the most important psychiatric predictor of MACCE was alcohol use disorders. Other important psychiatric predictors included depressive disorders, post-traumatic stress disorder/stress-related disorders, brain-related/physiological conditions, and non-substance-induced delirium. Some sex-specific findings also emerged (eg, depressive episodes more important for women than men). Overall, odds ratios in training and testing sets indicated that odds of MACCE were greater among those with (versus without) psychiatric disorders.
CONCLUSIONS
Results emphasize the importance of considering a range of psychiatric disorders when assessing cardiovascular risk following trauma.
MeSH
Psychopathology, Heart Diseases, Stress Disorders, Post-Traumatic, Stroke, Myocardial Infarction, Alcoholism, Mental Disorders, Case-Control Studies, Stress, Physiological, Machine Learning, Depressive Disorder, Stress Disorders, Traumatic, Sex, Learning, Wounds And Injuries