Association of substance use with stroke in heart failure by community socioeconomic distress
Year: 2025
Type: article
Study design: Observational Study
Abstract: INTRODUCTION: Substance use is common among individuals with heart failure (HF) and is linked to cardiotoxic effects and adverse outcomes. Given the increased vulnerability of HF patients to ischemic stroke, understanding how substance use and community distress contribute to this risk is vital for optimizing clinical prevention strategies. This study examined whether substance use increases stroke risk among HF patients and whether this association differs by community distress level. METHODS: We conducted a multicenter study using data from HF patients treated at WVU Medicine and Charleston Area Medical Center (CAMC) in West Virginia between 2017 and 2023. Multivariable logistic regression assessed the association between substance use and ischemic stroke, stratified by community distress level and adjusted for demographics and comorbidities. RESULTS: Among 33,663 individuals with HF in the WVU Medicine cohort, 2651 (7.88 %) experienced a stroke. Among 8050 in the CAMC cohort, 900 (11.18 %) experienced a stroke. Overall, among both cohorts, patients with substance use disorder diagnoses had greater odds of stroke. WVU (aOR, 1.36; 95 % CI, 1.14-1.63) and CAMC (aOR, 3.50; 95 % CI, 2.85-4.55). In distressed communities, the association was stronger: WVU (aOR, 1.68; 95 % CI, 1.34-2.09) and CAMC (aOR, 3.70; 95 % CI, 3.03-4.52). In non-distressed communities, only the CAMC cohort showed a significant association (aOR, 1.80; 95 % CI, 1.63-2.09). CONCLUSIONS AND RELEVANCE: Substance use is linked to higher stroke risk among HF patients, especially in socioeconomically distressed communities. Addressing both clinical and structural factors is essential for effective stroke prevention in this population.
Source: Drug and Alcohol Dependence
Authors: Brian Witrick, Frank Annie, Timothy Dotson, Wes Kimble, George Sokos, Christopher Bianco, Sarah Rinehart, Megan Pate, Evonne Richards, Brian Hendricks
Language: English
Subfield: Cardiology and Cardiovascular Medicine
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
Estimated APC paid: $4,380
Awards: G1424939314, Identifying COVID-19 vaccine deserts using Machine Learning and Geospatial Analyses to target Community -engaged testing for vulnerable rural populations to prevent localized outbreaks, G8708076294, West Virginia Clinical and Translational Science Institute: A Statewide Organization Building Research Excellence and Engaging Communities to Improve Health
OpenAlex ID: W4414413985
