A Simple Review of Small Vessel Disease Manifestation in the Brain, Retina, and Kidneys.

Small blood vessels express specific phenotypical and functional characteristics throughout the body. Alterations in the microcirculation contribute to many correlated physiological and pathological events in related organs. Factors such as comorbidities and genetics contribute to the complexity of this topic. Small vessel disease primarily affects end organs that receive significant cardiac output, such as the brain, kidney, and retina. Despite the differences in location, concurrent changes are seen in the micro-vasculature of the brain, retina, and kidneys under pathological conditions due to their common histological, functional, and embryological characteristics. While the cardiovascular basis of pathology in association with the brain, retina, or kidneys has been well documented, this is a simple review that uniquely considers the relationship between all three organs and highlights the prevalence of coexisting end organ injuries in an attempt to elucidate connections between the brain, retina, and kidneys, which has the potential to transform diagnostic and therapeutic approaches.

Long-term mortality in ischemic stroke patients with concomitant chronic obstructive pulmonary disease.

BACKGROUND: Long-term mortality in ischemic stroke patients with concomitant COPD has been largely unexplored. This study aimed to compare long-term all-cause mortality in ischemic stroke patients with and without COPD. METHODS: This was a retrospective cohort study of ischemic stroke patients with and without COPD in the Geisinger Neuroscience Ischemic Stroke database to examine all-cause mortality up to 3 years using Kaplan-Meier estimator and Cox proportional hazards model. RESULTS: Of the 6,589 ischemic stroke patients included in this study, 5,525 (83.9%) did not have COPD (group A). Group B (n=1,006) consisted of patients with COPD diagnosis by ICD-9/10-CM codes. COPD patients in Group C (n=233) were diagnosed by spirometry, and in Group D (n=175) by both ICD-9/10-CM codes and spirometry confirmation. The survival probabilities at three years in Group B, C, and D were significantly lower than in Group A. Group B (HR=1.262, 95% CI 1.122-1.42, p<0.001) and group C (HR=1.251, 95% CI 1.01-1.55, p=0.041) had significantly lower hazard of mortality compared to group A. There was no significant difference in survival between COPD subtypes of chronic bronchitis and emphysema. Patients in Global Initiative for Chronic Obstructive Lung Disease (GOLD) 2 stage had an increased mortality hazard compared to the GOLD 1 stage. CONCLUSIONS: While ischemic stroke patients with preexisting COPD have worse long-term survival than those without COPD, the results largely depended on the definition of COPD used. These results suggest that ischemic stroke patients with COPD need more personalized medical care to decrease long-term mortality.

Comparison of Long-Term Outcomes and Associated Factors between Younger and Older Rural Ischemic Stroke Patients.

Introduction: The rise of ischemic stroke among young adults has stressed the need to understand their risk profiles and outcomes better. This study aimed to examine the five-year ischemic stroke recurrence and survival probability among young patients in rural Pennsylvania. Methods: This retrospective cohort study included first-time ischemic stroke patients from the Geisinger Health System between September 2003 and May 2014. The outcomes included all-cause mortality and ischemic stroke recurrence at five years. Kaplan-Meier estimator, cumulative incidence function, Cox proportional hazards model, and Cause-specific hazard model were used to examine the association of independent variables with the outcomes. Results: A total of 4459 first-time ischemic stroke patients were included in the study, with 664 (14.9%) patients in the 18−55 age group and 3795 (85.1%) patients in the >55 age group. In the 18−55 age group, the five-year survival probability was 87.2%, and the cumulative incidence of recurrence was 8%. Patients in the 18−55 age group had significantly lower hazard for all-cause mortality (HR = 0.37, 95% CI 0.29−0.46, p < 0.001), and non-significant hazard for five-year recurrence (HR = 0.81, 95% CI 0.58−1.12, p = 0.193) compared to the >55 age group. Chronic kidney disease was found to be associated with increased mortality in the 18−55 age group. Conclusion: In our rural population, younger ischemic stroke patients were at the same risk of long-term ischemic stroke recurrence as the older ischemic stroke patients. Identifying the factors and optimizing adequate long-term secondary prevention may reduce the risk of poor outcomes among younger ischemic stroke patients.

Predicting short and long-term mortality after acute ischemic stroke using EHR.

OBJECTIVE: Despite improvements in treatment, stroke remains a leading cause of mortality and long-term disability. In this study, we leveraged administrative data to build predictive models of short- and long-term post-stroke all-cause-mortality. METHODS: The study was conducted and reported according to the Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) guideline. We used patient-level data from electronic health records, three algorithms, and six prediction windows to develop models for post-stroke mortality. RESULTS: We included 7144 patients from which 5347 had survived their ischemic stroke after two years. The proportion of mortality was between 8%(605/7144) within 1-month, to 25%(1797/7144) for the 2-years window. The three most common comorbidities were hypertension, dyslipidemia, and diabetes. The best Area Under the ROC curve(AUROC) was reached with the Random Forest model at 0.82 for the 1-month prediction window. The negative predictive value (NPV) was highest for the shorter prediction windows - 0.91 for the 1-month - and the best positive predictive value (PPV) was reached for the 6-months prediction window at 0.92. Age, hemoglobin levels, and body mass index were the top associated factors. Laboratory variables had higher importance when compared to past medical history and comorbidities. Hypercoagulation state, smoking, and end-stage renal disease were more strongly associated with long-term mortality. CONCLUSION: All the selected algorithms could be trained to predict the short and long-term mortality after stroke. The factors associated with mortality differed depending on the prediction window. Our classifier highlighted the importance of controlling risk factors, as indicated by laboratory measures.