Development and psychometric properties of ECPICID-AVC to measure informal caregivers’ skills when caring for older stroke survivors at home

Introduction: Informal caregivers provide a significant part of the total care needed by dependent older people poststroke. Although informal care is often the preferred option of those who provide and those who receive informal care, informal caregivers often report lack of preparation to take care of older dependent people. This article outlines the development and psychometric testing of informal caregivers’ skills when providing care to older people after a stroke – ECPICID-AVC. Design: Prospective psychometric instrument validation study. Methods: Eleven experts participated in a focus group in order to delineate, develop and validate the instrument. Data were gathered among adult informal caregivers (n = 186) living in the community in Northern Portugal from August 2013 to January 2014. Results: The 32-item scale describes several aspects of informal caregiver’s skills. The scale has eight factors: skill to feed/hydrate by nasogastric feeding, skill to assist the person in personal hygiene, skill to assist the person for transferring, skill to assist the person for positioning, skill to provide technical aids, skill to assist the person to use the toilet, skill to feed/hydrate and skill to provide technical aids for dressing/undressing. Analysis demonstrated adequate internal consistency (Cronbach’s alpha = 0.83) and good temporal stability 0.988 (0.984–0.991). Conclusion: The psychometric properties of the measurement tool showed acceptable results allowing its implementation in clinical practice by the nursing community staff for evaluating practical skills in informal caregivers when providing care to older stroke survivors living at home.

Evaluating balance, stability and gait symmetry of stroke patients using kinematic and dynamic gait lab data

Dissertação de mestrado integrado em Engenharia Biomédica

Metabolic profiling and classification of propolis samples from Southern Brazil: an NMR-based platform coupled with machine learning

The chemical composition of propolis is affected by environmental factors and harvest season, making it difficult to standardize its extracts for medicinal usage. By detecting a typical chemical profile associated with propolis from a specific production region or season, certain types of propolis may be used to obtain a specific pharmacological activity. In this study, propolis from three agroecological regions (plain, plateau, and highlands) from southern Brazil, collected over the four seasons of 2010, were investigated through a novel NMR-based metabolomics data analysis workflow. Chemometrics and machine learning algorithms (PLS-DA and RF), including methods to estimate variable importance in classification, were used in this study. The machine learning and feature selection methods permitted construction of models for propolis sample classification with high accuracy (>75%, reaching 90% in the best case), better discriminating samples regarding their collection seasons comparatively to the harvest regions. PLS-DA and RF allowed the identification of biomarkers for sample discrimination, expanding the set of discriminating features and adding relevant information for the identification of the class-determining metabolites. The NMR-based metabolomics analytical platform, coupled to bioinformatic tools, allowed characterization and classification of Brazilian propolis samples regarding the metabolite signature of important compounds, i.e., chemical fingerprint, harvest seasons, and production regions.

Monovarietal extra-virgin olive oil classification: a fusion of human sensory attributes and an electronic tongue

Olive oil quality grading is traditionally assessed by human sensory evaluation of positive and negative attributes (olfactory, gustatory, and final olfactorygustatory sensations). However, it is not guaranteed that trained panelist can correctly classify monovarietal extra-virgin olive oils according to olive cultivar. In this work, the potential application of human (sensory panelists) and artificial (electronic tongue) sensory evaluation of olive oils was studied aiming to discriminate eight single-cultivar extra-virgin olive oils. Linear discriminant, partial least square discriminant, and sparse partial least square discriminant analyses were evaluated. The best predictive classification was obtained using linear discriminant analysis with simulated annealing selection algorithm. A low-level data fusion approach (18 electronic tongue signals and nine sensory attributes) enabled 100 % leave-one-out cross-validation correct classification, improving the discrimination capability of the individual use of sensor profiles or sensory attributes (70 and 57 % leave-one-out correct classifications, respectively). So, human sensory evaluation and electronic tongue analysis may be used as complementary tools allowing successful monovarietal olive oil discrimination.

Land cover classification of Lago Grande de Curuai floodplain (Amazon, Brazil) using multi-sensor and image fusion techniques

Given the limitations of different types of remote sensing images, automated land-cover classifications of the Amazon várzea may yield poor accuracy indexes. One way to improve accuracy is through the combination of images from different sensors, by either image fusion or multi-sensor classifications. Therefore, the objective of this study was to determine which classification method is more efficient in improving land cover classification accuracies for the Amazon várzea and similar wetland environments - (a) synthetically fused optical and SAR images or (b) multi-sensor classification of paired SAR and optical images. Land cover classifications based on images from a single sensor (Landsat TM or Radarsat-2) are compared with multi-sensor and image fusion classifications. Object-based image analyses (OBIA) and the J.48 data-mining algorithm were used for automated classification, and classification accuracies were assessed using the kappa index of agreement and the recently proposed allocation and quantity disagreement measures. Overall, optical-based classifications had better accuracy than SAR-based classifications. Once both datasets were combined using the multi-sensor approach, there was a 2% decrease in allocation disagreement, as the method was able to overcome part of the limitations present in both images. Accuracy decreased when image fusion methods were used, however. We therefore concluded that the multi-sensor classification method is more appropriate for classifying land cover in the Amazon várzea.

Supercritical fluid and pharmaceutical applications. Part I: Process classification

The supercritical fluid technology has been target of many pharmaceuticals investigations in particles production for almost 35 years. This is due to the great advantages it offers over others technologies currently used for the same purpose. A brief history is presented, as well the classification of supercritical technology based on the role that the supercritical fluid (carbon dioxide) performs in the process.

Ontological representation of tumor-node-metastasis classification and an ontology-driven classifier: a study on colorectal cancer

Dissertação de mestrado integrado em Engenharia Biomédica (área de especialização em Informática Médica)

Clinical impact of transesophageal echocardiography in patients with stroke without clinical evidence of cardiovascular sources of emboli

OBJECTIVE: The purpose of this study is to evaluate the impact of transeophageal echocardiography on management of patients at low-risk for cardiogenic embolism to prevent new potential cardiovascular sources of emboli. METHODS: We studied 69 patients with ischemic stroke at low-risk for cardiogenic embolism. Transeophageal echocardiography was performed to access: left atrium enlargement; communication or aneurysm of the interatrial septum; patent foramen ovale; spontaneous echo contrast or intracavitary thrombi; the presence of intraaortic atherosclerotic plaques or thrombi; significant valvar morphologic alteration or dysfunction; left ventricle enlargement, hypertrophy, or contractile abnormality. Transesophageal echocardiography altered clinical management, and we adopted anticoagulant therapy or another procedure apart from the use of acetylsalicylic acid. RESULTS: Transeophageal echocardiography detected at least one abnormality in 40 cases (58%). Clinical conduct was adjusted after the performance of transesophageal echocardiography in 11 patients (15.9%); anticoagulation was added in 10 cases and surgical correction in one patient. CONCLUSION: Transeophageal echocardiography was a very useful tool in the secondary prevention for stroke in patients at low risk for cardiogenic embolism.

Fibroelastoma of the mitral valve as a cause of transient ischemic stroke

A 44-year-old woman had a transient ischemic stroke, fibroelastoma of the mitral valve being the source of the embolus. The patient evolved with neutropenia induced by ticlopidine after 10 days of treatment. We report the major clinical features, therapeutical options, and medicamentous toxicity resulting from the use of antiplatelet drugs.

Les diatomées. Histoire naturelle, préparation, classification & description des principales espèces, par J. Pelletan, avec une introduction à l'étude des diatomées par m. J. Deby, et un exposé de la classification des diatomées par m. Paul Petit.

pt. 1

Les diatomées. Histoire naturelle, préparation, classification & description des principales espèces, par J. Pelletan, avec une introduction à l'étude des diatomées par m. J. Deby, et un exposé de la classification des diatomées par m. Paul Petit.

pt. 2