Data science of stroke imaging and enlightenment of the penumbra.

Imaging protocols of acute ischemic stroke continue to hold significant uncertainties regarding patient selection for reperfusion therapy with thrombolysis and mechanical thrombectomy. Given that patient inclusion criteria can easily introduce biases that may be unaccounted for, the reproducibility and reliability of the patient screening method is of utmost importance in clinical trial design. The optimal imaging screening protocol for selection in targeted populations remains uncertain. Acute neuroimaging provides a snapshot in time of the brain parenchyma and vasculature. By identifying the at-risk but still viable penumbral tissue, imaging can help estimate the potential benefit of a reperfusion therapy in these patients. This paper provides a perspective about the assessment of the penumbral tissue in the context of acute stroke and reviews several neuroimaging models that have recently been developed to assess the penumbra in a more reliable fashion. The complexity and variability of imaging features and techniques used in stroke will ultimately require advanced data driven software tools to provide quantitative measures of risk/benefit of recanalization therapy and help aid in making the most favorable clinical decisions

The relationship between glycaemic variability and cardiovascular autonomic dysfunction in patients with type 1 diabetes : a systematic review

Rigorous glycaemic control-reflected by low HbA1c goals-is of the utmost importance in the prevention and management of complications in patients with type 1 diabetes mellitus (T1DM). However, previous studies suggested that short-term glycaemic variability (GV) is also important to consider as excessive glucose fluctuations may have an additional impact on the development of diabetic complications. The potential relationship between GV and the risk of cardiovascular autonomic neuropathy (CAN), a clinical expression of cardiovascular autonomic dysfunction, is of increasing interest. This systematic review aimed to summarize existing evidence concerning the relationship between GV and cardiovascular autonomic dysfunction in T1DM. An electronic database search of Medline (PubMed), Web of Science and Embase was performed up to October 2019. There were no limits concerning year of publication. Methodological quality was evaluated using the Newcastle Ottawa Scale for observational studies. Six studies (four cross-sectional and two prospective cohorts) were included. Methodological quality of the studies varied from level C to A2. Two studies examined the association between GV and heart rate variability (HRV), and both found significant negative correlations. Regarding cardiovascular autonomic reflex tests (CARTs), two studies did not, while two other studies did find significant associations between GV parameters and CART scores. However, associations were attenuated after adjusting for covariates such as HbA1c, age and disease duration. In conclusion, this systematic review found some preliminary evidence supporting an association between GV and cardiovascular autonomic dysfunction in T1DM. Hence, uncertainty remains whether high GV can independently contribute to the onset or progression of CAN. The heterogeneity in the methodological approach made it difficult to compare different studies. Future studies should therefore use uniformly evaluated continuous glucose monitoring-derived parameters of GV, while standardized assessment of HRV, CARTs and other potential cardiac autonomic function parameters is needed for an unambiguous definition of CAN

Forecasting temporal dynamics of cutaneous leishmaniasis in Northeast Brazil.

IntroductionCutaneous leishmaniasis (CL) is a vector-borne disease of increasing importance in northeastern Brazil. It is known that sandflies, which spread the causative parasites, have weather-dependent population dynamics. Routinely-gathered weather data may be useful for anticipating disease risk and planning interventions.Methodology/principal findingsWe fit time series models using meteorological covariates to predict CL cases in a rural region of Bahía, Brazil from 1994 to 2004. We used the models to forecast CL cases for the period 2005 to 2008. Models accounting for meteorological predictors reduced mean squared error in one, two, and three month-ahead forecasts by up to 16% relative to forecasts from a null model accounting only for temporal autocorrelation.SignificanceThese outcomes suggest CL risk in northeastern Brazil might be partially dependent on weather. Responses to forecasted CL epidemics may include bolstering clinical capacity and disease surveillance in at-risk areas. Ecological mechanisms by which weather influences CL risk merit future research attention as public health intervention targets

Stroke following percutaneous coronary intervention : type-specific incidence, outcomes and determinants seen by the British Cardiovascular Intervention Society 2007-12

Published on behalf of the European Society of Cardiology. All rights reserved. © The Author 2015. For permissions please email: [email protected] reviewedPostprin