Cerebral Venous Sinus Thrombosis - Diagnostic Strategies and Prognostic Models: A Review

In 1825, Ribes described a case of a 45-year old man who died after a 6-month history of epilepsy, seizures and delirium. The autopsy examination revealed thrombosis of the superior sagittal sinus, the left lateral sinus and a cortical vein in the parietal region. This was probably the first detailed description of extensive cerebral venous sinus thrombosis (CVST). Since then, the literature describing this disease has comprised of case reports, series and some newer prospective studies, including recent reviews and guidelines (statement) on the diagnosis and management of CVST (Siddiqui \u26 Kamal, 2006; Stam, 2005; Saposnik et al, 2011; Brown \u26 Thore, 2011). The cerebral venous sinus thrombosis is a challenging condition and it is most common than previously thought. CVST accounts for 0.5% to 1.0% of all strokes and usually affects young individuals. Important advances have been made in the understanding of the pathophysiology of this vascular disorder. The diagnosis of CVST is still frequently overlooked or delayed as a result of the wide spectrum of clinical symptoms and the often sub-acute or lingering onset. Patients with CVST commonly present with headache, although some develop a focal neurological deficit, decreased level of consciousness, seizures, or intracranial hypertension without focal neurological signs. Uncommonly, an insidious onset may create a diagnostic challenge. The main problem of this disorder is that it is very often unrecognised at initial presentation. In particular, a prothrombotic factor or a direct cause is identified in approximately 66% of the CVST patients (a list of most important causal and risk factors are listed in Table 1). Cerebral venous thrombosis is more common in women than men, with a female to male ratio of 3:1 (cited in Ferro \u26 Canhao, 2011). The imbalance may be due to the increased risk of CVST associated with pregnancy and puerperium and with oral contraceptives. The female predominance in CVST is found in young adults, but not in children or older adults

Metabolic syndrome severity score: range and associations with cardiovascular risk factors

Introduction: Metabolic Syndrome Severity Score (MSSS) is a new clinical prediction rule (CPR) for diagnostic and therapeutic decisions and employs available components (sex, age, race, systolic blood pressure, waistline circumference, high-density lipoprotein, triglycerides and fasting blood glucose). The aim of our work was to perform cross-sectional pilot trial on middle-aged healthy volunteers and patients with metabolic syndrome (MetS) with and without type 2 diabetes mellitus (T2DM) for studying feasibility and implementation of MSSS and its associations with cardiovascular risk factors.Material and methods: We approached 64 eligible participants from Bulgaria. The MSSS values, together with demographic, anthropometric, medical history, laboratory findings, CVD risk factors, QRISK2 score for 10-year cardiovascular risk and predicted heart age, were analysed. Descriptive statistics with tests for comparison (e.g., t-test, c2) between groups as well as ANOVA and logistic regression were applied. Results: We analysed data from 56 participants (aged 50.11 ±3.43 years). The MSSS was higher in MetS patients (including 6 T2DM patients) than in controls (n = 29; 51.8%) presented as percentiles (69.97% and 34.41%, respectively) and z-scores (0.60 and –0.45, respectively) (p < 0.05). The logistic regression model of MSSS indicated a positive association with MetS/T2DM cases (correctness > 85%, p < 0.01). For further validation purposes, positive correlations of MSSS with CVDrisk factor as diastolic blood pressure (Rho = 0.399; p < 0.003) and QRISK2 score (Rho = 0.524; p < 0.001) or predicted heart age (Rho = 0.368; p < 0.007) were also found.Conclusions: The pilot study of MSSS in Bulgaria indicated feasibility and consistency of its implementation among patients with metabolic syndrome and/or T2DM and healthy volunteers

Early neurological and cognitive impairments in subclinical cerebrovascular disease

Background: The subclinical cerebrovascular disease (SCVD) is an important public health problem with demonstrated prognostic significance for stroke, future cognitive decline, and progression to dementia. The earliest possible detection of the silent presence of SCVD in adults at age at risk with normal functioning is very important for both clinical doctors and scientists.Materials and Methods: Seventy-seven adult volunteers, recruited during the years 2005–2007, with mean age 58.7 (standard deviation 5.9) years, were assessed by four subtests from the Cambridge Neuropsychological Test Automated Battery (CANTAB)-Eclipse cognitive assessment system. We used a questionnaire survey for the presence of cerebrovascular risk factors (CVRFs) such as arterial hypertension, smoking and dyslipidemia, among others, as well as instrumental (Doppler examination) and neurological magnetic resonance imaging (MRI) procedures. Descriptive statistics, comparison (t-test, Chi-square) and univariate methods were used as followed by multifactor logistic regression and receiver operating characteristics analyses.Results: The risk factor questionnaire revealed nonspecific symptoms in 44 (67.7%) of the subjects. In 42 (64.6%) of all 65 subjects, we found at least one of the conventional CVRFs. Abnormal findings from the extra- and trans-cranial Doppler examination were established in 38 (58.5%) of all studied volunteers. Thirty-four subjects had brain MRI (52.3%), and abnormal findings were found in 12 (35.3%) of them. Two of the four subtests of CANTAB tool appeared to be potentially promising predictors of the outcome, as found at the univariate analysis (spatial working memory 1 [SWM1] total errors; intra-extra dimensional set 1 [IED1] total errors [adjusted]; IED2 total trials [adjusted]). We established that the best accuracy of 82.5% was achieved by a multifactor interaction logistic regression model, with the role CVRF and combined CANTAB predictor “IED total ratio (errors/trials) × SWM1 total errors” (P = 0.006).Conclusions: Our results have contributed to the hypothesis that it is possible to identify, by noninvasive methods, subjects at age at risk who have mild degree of cognitive impairment and to establish the significant relationship of this impairment with existing CVRFs, nonspecific symptoms and subclinical abnormal brain Doppler/MRI findings. We created a combined neuropsychological predictor that was able to clearly distinguish between the presence and absence of abnormal Doppler/MRI findings. This pilot prognostic model showed a relatively high accuracy of >80%; therefore, the predictors may serve as biomarkers for SCVD in subjects at age at risk (51–65 years)