Abstract WP160: Mechanisms of Brain Hemorrhage in Chronic Kidney Disease

Abstract

Introduction: Chronic kidney disease (CKD) is a risk factor for intracerebral hemorrhage (ICH) and for worse outcomes following ICH. In this study, we examined the relationship between ICH and CKD, as well as intracranial arterial calcification (IAC) as an intermediate biomarker. We hypothesized that CKD is an independent risk factor for IAC burden, and that high IAC burden is an independent risk factor for ICH. Methods: A retrospective cohort of spontaneous ICH and non-ICH patients with non-contrast head CT imaging was identified. For each patient, eGFR (estimated glomerular filtration rate) along with age, sex, race, ethnicity, hypertension (HTN), diabetes (DM), heart disease, and hyperlipidemia were abstracted. A convolutional neural network was developed to automate quantification of IAC burden within the anterior and posterior circulation, and all results were visually verified for accuracy by an expert neuroradiologist. The relationship between eGFR and IAC was assessed with Pearson correlation and one-way ANOVA. Univariate analysis of ICH risk factors was evaluated using t-test and Chi-square, while multivariate models were analyzed using logistic regression. Results: Among the 717 patients in this study, 98 were ICH patients. In all patients, mean IAC burden increased significantly with CKD stage (p < 0.01). Univariate analysis for IAC risk factors yielded statistically significant associations for eGFR (p < 0.01) as well as age (p < 0.01), HTN (p = 0.01), and African-American race (p = 0.02). In multivariate analysis, eGFR remained a significant independent predictor of IAC (p < 0.01) along with HTN (p < 0.01), DM (p < 0.01), and race (p < 0.01). Furthermore, IAC burden was significantly higher in ICH patients (15.4 mL vs. 8.7 mL, p = 0.02). In multivariate analysis, IAC remained a significant independent predictor of ICH (p < 0.01) along with HTN (p < 0.01), DM (p = 0.03), sex (p < 0.01), and race (p < 0.01). Conclusion: This is the first demonstration that eGFR predicts strictly quantified IAC, which then predicts ICH. These findings offer novel insights into determinants of IAC and mechanisms underlying the CKD-ICH relationship.