Association of Left Ventricular Hypertrophy and Atrial Fibrillation with Hemorrhagic Evolution of Small Vessel Disease

Differential risk factor profile and neuroimaging markers of small vessel disease between lacunar ischemic stroke and deep intracerebral hemorrhage

Background

Lacunar ischemic stroke (LIS) and deep intracerebral hemorrhage (dICH) are two stroke phenotypes of deep perforator arteriopathy. It is unclear what factors predispose individuals with deep perforator arteriopathy to either ischemic or hemorrhagic events.

Objectives

We aimed to investigate risk factors and neuroimaging features of small vessel disease (SVD) associated with LIS versus dICH in a cross-sectional study.

Methods

We included patients with clinically presenting, magnetic resonance imaging-confirmed LIS or dICH from two tertiary hospitals between 2010 and 2021. We recorded vascular risk factors and SVD markers, including lacunes, white matter hyperintensities (WMH), perivascular spaces (PVS), and cerebral microbleeds (CMB). Logistic regression modeling was used to determine the association between vascular risk factors, SVD markers, and stroke phenotype. We further created WMH probability maps to compare WMH distribution between LIS and dICH.

Results

A total of 834 patients with LIS (mean age 61.7 ± 12.1 years) and 405 with dICH (57.7 ± 13.2 years) were included. Hypertension was equally frequent between LIS and dICH (72.3% versus 74.8%, p = 0.349). Diabetes mellitus, hyperlipidemia, smoking, and prior ischemic stroke were more associated with LIS [odds ratio (OR) (95% confidence interval (CI)), 0.35 (0.25-0.48), 0.32 (0.22-0.44), 0.31 (0.22-0.44), and 0.38 (0.18-0.75)]. Alcohol intake and prior ICH were more associated with dICH [OR (95% CI), 2.34 (1.68-3.28), 2.53 (1.31-4.92)]. Lacunes were more prevalent in LIS [OR (95% CI) 0.23 (0.11-0.43)], while moderate-to-severe basal-ganglia PVS and CMB were more prevalent in dICH [OR (95% CI) 2.63 (1.35-5.27), 4.95 (2.71-9.42)]. WMH burden and spatial distribution did not differ between groups.

Conclusion

The microangiopathy underlying LIS and dICH reflects distinct risk profiles and SVD features, hence possibly SVD subtype susceptibility. Prospective studies with careful phenotyping and genetics are needed to clarify the mechanisms underlying this difference.

Hemorrhagic Coagulation Disorders and Ischemic Stroke: How to Reconcile Both?

Coagulation and fibrinolytic system disorders are conditions in which the blood's ability to clot is impaired, resulting in an increased risk of thrombosis or bleeding. Although these disorders are the expression of two opposing tendencies, they can often be associated with or be a consequence of each other, contributing to making the prognosis of acute cerebrovascular events more difficult. It is important to recognize those conditions that are characterized by dual alterations in the coagulation and fibrinolytic systems to reduce the prognostic impact of clinical conditions with difficult treatment and often unfortunate outcomes. Management of these individuals can be challenging, as clinicians must balance the need to prevent bleeding episodes with the potential risk of clot formation. Treatment decisions should be made on an individual basis, considering the specific bleeding disorder, its severity, and the patient's general medical condition. This review aims to deal with all those forms in which coagulation and fibrinolysis represent two sides of the same media in the correct management of patients with acute neurological syndrome. Precision medicine, personalized treatment, advanced anticoagulant strategies, and innovations in bleeding control represent future directions in the management of these complex pathologies in which stroke can be the evolution of two different acute events or be the first manifestation of an occult or unknown underlying pathology.

Early Prediction of Cerebral Computed Tomography under Intelligent Segmentation Algorithm Combined with Serological Indexes for Hematoma Enlargement after Intracerebral Hemorrhage

The aim of this study was to explore the application value of brain computed tomography (CT) images under intelligent segmentation algorithm and serological indexes in the early prediction of hematoma enlargement in patients with intracerebral hemorrhage (ICH). Fuzzy C-means (FCM) intelligence segmentation algorithm was introduced, and 150 patients with early ICH were selected as the research objects. Patient cerebral CT images were intelligently segmented to assess the diagnostic value of this algorithm. According to different hematoma volumes during CT examination, patients were divided into observation group (hematoma enlargement occurred, n = 48) and control group (no hematoma enlargement occurred, n = 102). The predicative value of hematoma enlargement after ICH was investigated by assessing CT image quality and measuring intracerebral edema, hematoma volume, and serological indicators of the patients of the two groups. The results demonstrated that the sensitivity, specificity, and accuracy of CT images processed by intelligence segmentation algorithm amounted to 0.894, 0.898, and 0.930, respectively. Besides, early edema enlargement and hematoma of patients in the observation group were more significant than those of patients in the control group. Relative edema volume was 0.912, which was apparently lower than that in the control group (1.017) (P < 0.05). In terms of CT signs of ICH patients, the incidence of blend sign, low density sign, and stroke of the observation group was evidently higher than those of the control group (P < 0.05). Besides, absolute lymphocyte count (ALC) and hemoglobin (HGB) concentration of the patients in the observation group were 6.23 × 109/L and 6.29 × 109/L, respectively, both of which were higher than those of the control group (6.08 × 109/L and 4.25 × 109/L). Neutrophil to lymphocyte ratio (NLR) was 0.99 × 109/L, which was apparently lower than that in the control group (1.43 × 109/L) (P < 0.05). To sum up, cerebral CT images processed by FCM algorithm showed good diagnostic effect on ICH and high clinical values in the early prediction of hematoma among ICH patients.