Neurology of rheumatologic disorders

Rheumatologic diseases encompass autoimmune and inflammatory disorders of the joints and soft tissues that often involve multiple organ systems, including the central and peripheral nervous systems. Common features include constitutional symptoms, arthralgia and arthritis, myalgia, and sicca symptoms. Neurological manifestations may present in patients with preexisting rheumatologic diagnoses, occur concurrently with systemic signs and symptoms, or precede systemic manifestations by months to years. Rheumatic disorders presenting as neurological syndromes may pose diagnostic challenges. Advances in immunosuppressive treatment of rheumatologic disease have expanded the treatment armamentarium. However, serious neurotoxic effects have been reported with both old and newer agents. Familiarity with neurological manifestations of rheumatologic diseases, diagnosis, and potential nervous system consequences of treatment is important for rapid diagnosis and appropriate intervention. This article briefly reviews the diverse neurological manifestations and key clinical features of rheumatic disorders and the potential neurological complications of agents commonly used for treatment

Ischemic Posterior Circulation Stroke: A Review of Anatomy, Clinical Presentations, Diagnosis, and Current Management

Posterior circulation (PC) strokes represent approximately 20% of all ischemic strokes. In contrast to the anterior circulation (AC) several differences in presenting symptoms, clinical evaluation, diagnostic testing and management strategy exist which may present a challenge to the treating physician. This review will discuss the anatomical, etiological and clinical classification of PC strokes, identify diagnostic pitfalls and overview current therapeutic regimens

Embolic Strokes of Unknown Source and Cryptogenic Stroke: Implications in Clinical Practice

Up to a third of strokes are rendered cryptogenic or of undetermined etiology. This number is specifically higher in younger patients. At times, inadequate diagnostic workups, multiple cause or an under-recognized etiology contributes to this statistic. Embolic stroke of undetermined source, a new clinical entity particularly refers to patients with embolic stroke for whom the etiology of embolism remains unidentified despite through investigations ruling out established cardiac and vascular sources. In this article, we review current classification and discuss important clinical considerations in these patients; highlighting cardiac arrhythmias and structural abnormalities, patent foramen ovale, paradoxical sources, and potentially under-recognized, vascular, inflammatory, autoimmune and hematologic sources in relation to clinical practice

Amyloid-Beta Related Angiitis of the Central Nervous System: Case Report and Topic Review

Amyloid-beta related angiitis (ABRA) of the central nervous system (CNS) is a rare disorder with overlapping features of primary angiits of the CNS (PACNS) and cerebral amyloid angiopathy (CAA). We evaluated a 74-year-old man with intermittent left sided weakness and MRI findings of leptomeningeal enhancement, vasogenic edema and subcortical white matter disease proven to have ABRA. We discuss clinicopathological features and review the topic of ABRA. <br/

High Mortality among 30-Day Readmission after Stroke: Predictors and Etiologies of Readmission

BackgroundAlthough some risk factors for stroke readmission have been reported, the mortality risk is unclear. We sought to evaluate etiologies and predictors of 30-day readmissions and determine the associated mortality risk.MethodsThis is a retrospective case–control study evaluating 1,544 patients admitted for stroke (hemorrhagic, ischemic, or TIA) from January 2013 to December 2014. Of these, 134 patients readmitted within 30 days were identified as cases; 1,418 other patients, with no readmissions were identified as controls. Patients readmitted for hospice or elective surgery were excluded. An additional 248 patients deceased on index admission were included for only a comparison of mortality rates. Factors explored included socio-demographic characteristics, clinical comorbidities, stroke characteristics, and length of stay. Chi-square test of proportions and multivariable logistic regression were used to identify independent predictors of 30-day stroke readmissions. Mortality rates were compared for index admission and readmission and among readmission diagnoses.ResultsAmong the 1,544 patients in the main analysis, 67% of index stroke admissions were ischemic, 22% hemorrhagic, and 11% TIA. The 30-day readmission rate was 8.7%. The most common etiologies for readmission were infection (30%), recurrent stroke and TIA (20%), and cardiac complications (14%). Significantly higher proportion of those readmitted for recurrent strokes and TIAs presented within the first week (p = 0.039) and had a shorter index admission length of stay (p = 0.027). Risk factors for 30-day readmission included age &gt;75 (p = 0.02), living in a facility prior to index stroke (p = 0.01), history of prior stroke (p = 0.03), diabetes (p = 0.03), chronic heart failure (p ≤ 0.001), atrial fibrillation (p = 0.03), index admission to non-neurology service (p &lt; 0.01), and discharge to other than home (p &lt; 0.01). On multivariate analysis, index admission to a non-neurology service was an independent predictor of 30-day readmission (p ≤ 0.01). The mortality after a within 30-day readmission after stroke was higher than index admission (36.6 vs. 13.8% p ≤ 0.001) (OR 3.6 95% CI 2.5–5.3). Among those readmitted, mortality was significantly higher for those admitted for a recurrent stroke (p = 0.006).ConclusionApproximately one-third of 30-day readmissions were infection related and one-fifth returned with recurrent stroke or TIA. Index admission to non-neurology service was an independent risk factor of 30-day readmissions. The mortality rate for 30-day readmission after stroke is more than 2.5 times greater than index admissions and highest among those readmitted for recurrent stroke. Identifying high-risk patients for readmission, ensuring appropriate level of service, and early outpatient follow-up may help reduce 30-day readmission and the high associated risk of mortality

Machine learning provides evidence that stroke risk is not linear: The non-linear Framingham stroke risk score.

Current stroke risk assessment tools presume the impact of risk factors is linear and cumulative. However, both novel risk factors and their interplay influencing stroke incidence are difficult to reveal using traditional additive models. The goal of this study was to improve upon the established Revised Framingham Stroke Risk Score and design an interactive Non-Linear Stroke Risk Score. Leveraging machine learning algorithms, our work aimed at increasing the accuracy of event prediction and uncovering new relationships in an interpretable fashion. A two-phase approach was used to create our stroke risk prediction score. First, clinical examinations of the Framingham offspring cohort were utilized as the training dataset for the predictive model. Optimal Classification Trees were used to develop a tree-based model to predict 10-year risk of stroke. Unlike classical methods, this algorithm adaptively changes the splits on the independent variables, introducing non-linear interactions among them. Second, the model was validated with a multi-ethnicity cohort from the Boston Medical Center. Our stroke risk score suggests a key dichotomy between patients with history of cardiovascular disease and the rest of the population. While it agrees with known findings, it also identified 23 unique stroke risk profiles and highlighted new non-linear relationships; such as the role of T-wave abnormality on electrocardiography and hematocrit levels in a patient's risk profile. Our results suggested that the non-linear approach significantly improves upon the baseline in the c-statistic (training 87.43% (CI 0.85-0.90) vs. 73.74% (CI 0.70-0.76); validation 75.29% (CI 0.74-0.76) vs 65.93% (CI 0.64-0.67), even in multi-ethnicity populations. The clinical implications of the new risk score include prioritization of risk factor modification and personalized care at the patient level with improved targeting of interventions for stroke prevention

Early ischaemic and haemorrhagic complications after atrial fibrillation-related ischaemic stroke: analysis of the IAC study.

INTRODUCTION: Predictors of long-term ischemic and hemorrhagic complications in atrial fibrillation (AF) have been studied, but there is limited data on predictors of early ischemic and hemorrhagic complications after AF associated ischemic stroke. We sought to determine these predictors. METHODS: The Initiation of Anticoagulation after Cardioembolic stroke (IAC) study is a multicenter retrospective study across that pooled data from consecutive patients with ischemic stroke in the setting of AF from stroke registries across 8 comprehensive stroke centers in the United States. The co-primary outcomes were recurrent ischemic event (stroke/TIA/systemic arterial embolism) and delayed symptomatic intracranial hemorrhage (d-sICH) within 90 days. We performed univariate analyses and cox regression analyses including important predictors on univariate analyses to determine independent predictors of early ischemic events (stroke/TIA/systemic embolism) and d-sICH. RESULTS: Out of 2084 patients, 1520 patients qualified; 104 patients (6.8%) had recurrent ischemic events and 23 patients (1.5%) had d-sICH within 90 days from the index event. In cox-regression models, factors associated with a trend for recurrent ischemic events were prior stroke or TIA (HR 1.42, 0.96 – 2.10) and ipsilateral arterial stenosis with 50–99% narrowing (HR 1.54, 0.98 – 2.43). Those associated with sICH were female sex (HR 2.68, 1.06– 6.83), history of hyperlipidemia (HR 2.91, 1.08 – 7.84), and early hemorrhagic transformation (HR 5.35, 2.22 – 12.92). CONCLUSION: In patients with ischemic stroke and AF, predictors of d-sICH are different than those of recurrent ischemic events therefore recognizing these predictors may help inform early stroke versus d-sICH prevention strategies

Anticoagulation Timing in Cardioembolic Stroke and Recurrent Event Risk.

OBJECTIVES: Guidelines recommend to initiate anticoagulation within 4-14 days after cardioembolic stroke. Data supporting this did not account for key factors potentially affecting the decision to initiate anticoagulation such as infarct size, hemorrhagic transformation, or high risk features on echocardiography. METHODS: We pooled data from stroke registries of 8 comprehensive stroke centers across the United States. We included consecutive patients admitted with ischemic stroke and atrial fibrillation. The primary predictor was timing of initiating anticoagulation (0-3 days, 4-14 days, or >14 days) and outcomes were recurrent stroke/TIA/systemic embolism, symptomatic intracerebral hemorrhage (sICH), and major extracranial hemorrhage (ECH) within 90 days. RESULTS: Among 2084 patients, 1289 met the inclusion criteria. The combined endpoint occurred in 10.1% (n = 130) subjects (87 ischemic events, 20 sICH, and 29 ECH). Overall, there was no significant difference in the composite endpoint between the three groups: 0-3 days [10.3% (64/617)], 4-14 days [(9.7%) 52/535)], >14 days [10.2% (14/137), p=0.933]. In adjusted models, patients started on anticoagulation between 4-14 days did not have a lower rate of sICH (vs. 0-3 days) (OR 1.49 95% CI 0.50 – 4.43) neither did they have a lower rate of recurrent ischemic events (vs. > 14 days) (OR 0.76 95% CI 0.36 – 1.62, p = 0.482). INTERPRETATION: In this multicenter real world cohort, the recommended (4-14 days) time frame to start oral anticoagulation was not associated with reduced ischemic and hemorrhagic outcomes. Randomized trials are required to determine the optimal timing of anticoagulation initiation