Reliability of maximal grip strength measurements and grip strength recovery following a stroke.

STUDY DESIGN: Clinical measurement. PURPOSE: The test-retest reliability of maximal grip strength measurements (MGSM) is examined in subjects for 12 weeks post-stroke together with maximal grip strength recovery and the maximal-grip and upper-extremity strength measurements' relationship with capacity and performance test scores. METHODS: A Jamar dynamometer and the Motricity Index (MI) were used for strength measurements. The Chedoke Arm and Hand Activity Inventory and ABILHAND questionnaire for evaluating capacities and performances. RESULTS: MGSM were reliable (Intraclass Correlation Coefficients = 0.97-0.99, Minimal Detectable Differences = 2.73-4.68 kg). Among the 34 participants, 47% did not have a measurable grip strength one week post-stroke but 50% of these recovered some strength within the first eight weeks. The MGSM and MI scores were correlated with scores of tests of capacity and performance (Spearman's Rank Correlation Coefficients = 0.69-0.94). CONCLUSIONS: MGSM are reliable in the first weeks after a stroke. LEVEL OF EVIDENCE: N/A.

Risk factors, aetiology and outcome of ischaemic stroke in young adults: the Swiss Young Stroke Study (SYSS).

Ischaemic stroke (IS) in young adults has been increasingly recognized as a serious health condition. Stroke aetiology is different in young adults than in the older population. This study aimed to investigate aetiology and risk factors, and to search for predictors of outcome and recurrence in young IS patients. We conducted a prospective multicentre study of consecutive IS patients aged 16-55 years. Baseline demographic data, risk factors, stroke aetiology including systematic genetic screening for Fabry disease and severity were assessed and related to functional neurological outcome (modified Rankin Scale, mRS), case fatality, employment status, place of residence, and recurrent cerebrovascular events at 3 months. In 624 IS patients (60 % men), median age was 46 (IQR 39-51) years and median NIHSS on admission 3 (IQR 1-8). Modifiable vascular risk factors were found in 73 %. Stroke aetiology was mostly cardioembolism (32 %) and of other defined origin (24 %), including cervicocerebral artery dissection (17 %). Fabry disease was diagnosed in 2 patients (0.3 %). Aetiology remained unknown in 20 %. Outcome at 3 months was favourable (mRS 0-1) in 61 % and fatal in 2.9 %. Stroke severity (p < 0.001) and diabetes mellitus (p = 0.023) predicted unfavourable outcome. Stroke recurrence rate at 3 months was 2.7 %. Previous stroke or TIA predicted recurrent cerebrovascular events (p = 0.012). In conclusion, most young adults with IS had modifiable vascular risk factors, emphasizing the importance of prevention strategies. Outcome was unfavourable in more than a third of patients and was associated with initial stroke severity and diabetes mellitus. Previous cerebrovascular events predicted recurrent ones.

Classification and inventory management of abnormal demand items

The main objective of the study is to form a framework that provides tools to recognise and classify items whose demand is not smooth but varies highly on size and/or frequency. The framework will then be combined with two other classification methods in order to form a three-dimensional classification model. Forecasting and inventory control of these abnormal demand items is difficult. Therefore another object of this study is to find out which statistical forecasting method is most suitable for forecasting of abnormal demand items. The accuracy of different methods is measured by comparing the forecast to the actual demand. Moreover, the study also aims at finding proper alternatives to the inventory control of abnormal demand items. The study is quantitative and the methodology is a case study. The research methods consist of theory, numerical data, current state analysis and testing of the framework in case company. The results of the study show that the framework makes it possible to recognise and classify the abnormal demand items. It is also noticed that the inventory performance of abnormal demand items differs significantly from the performance of smoothly demanded items. This makes the recognition of abnormal demand items very important.

The fossil crown wasp Electrostephanus petiolatus Brues in Baltic Amber (Hymenoptera, Stephanidae): designation of a neotype, revised classification,and a key to amber Stephanidae.

The fossil crown wasp Electrostephanus petiolatus Brues comb. rev.(Stephanidae, Electrostephaninae) is re-described from a single male preserved in middle Eocene Baltic Amber. The holotype was lost or destroyed around the time of World War II and subsequent interpretations of its identity have been based solely on the brief descriptive comments provided by Brues in his original account. The new specimen matches the original description and illustration provided by Brues in every detail and we hereby consider them to be conspecific, selecting the specimen as a neotype for the purpose of stabilizing the nomenclature for this fossil species. This neotype exhibits a free first metasomal tergum and sternum, contrary to the assertion of previous workers who indicated these to be fused. Accordingly, this species does indeed belong to the genus Electrostephanus Brues rather than to Denaeostephanus Engel & Grimaldi (Stephaninae). Electrostephanus petiolatus is transferred to a new subgenus, Electrostephanodes n. subgen. , based on its elongate pseudo- petiole and slender gaster, but may eventually warrant generic status as the phylogenetic placement of these fossil lineages continues to be clarifi ed. A revised key to the Baltic amber crown wasps is provided.

Bayesian Networks for the Age Classification of Living Individuals: a Study on Transition Analysis

Over the past few decades, age estimation of living persons has represented a challenging task for many forensic services worldwide. In general, the process for age estimation includes the observation of the degree of maturity reached by some physical attributes, such as dentition or several ossification centers. The estimated chronological age or the probability that an individual belongs to a meaningful class of ages is then obtained from the observed degree of maturity by means of various statistical methods. Among these methods, those developed in a Bayesian framework offer to users the possibility of coherently dealing with the uncertainty associated with age estimation and of assessing in a transparent and logical way the probability that an examined individual is younger or older than a given age threshold. Recently, a Bayesian network for age estimation has been presented in scientific literature; this kind of probabilistic graphical tool may facilitate the use of the probabilistic approach. Probabilities of interest in the network are assigned by means of transition analysis, a statistical parametric model, which links the chronological age and the degree of maturity by means of specific regression models, such as logit or probit models. Since different regression models can be employed in transition analysis, the aim of this paper is to study the influence of the model in the classification of individuals. The analysis was performed using a dataset related to the ossifications status of the medial clavicular epiphysis and results support that the classification of individuals is not dependent on the choice of the regression model.

Probabilistic age classification with Bayesian networks: a study on the ossification status of the medial clavicular epiphysis

In the past few decades, the rise of criminal, civil and asylum cases involving young people lacking valid identification documents has generated an increase in the demand of age estimation. The chronological age or the probability that an individual is older or younger than a given age threshold are generally estimated by means of some statistical methods based on observations performed on specific physical attributes. Among these statistical methods, those developed in the Bayesian framework allow users to provide coherent and transparent assignments which fulfill forensic and medico-legal purposes. The application of the Bayesian approach is facilitated by using probabilistic graphical tools, such as Bayesian networks. The aim of this work is to test the performances of the Bayesian network for age estimation recently presented in scientific literature in classifying individuals as older or younger than 18 years of age. For these exploratory analyses, a sample related to the ossification status of the medial clavicular epiphysis available in scientific literature was used. Results obtained in the classification are promising: in the criminal context, the Bayesian network achieved, on the average, a rate of correct classifications of approximatively 97%, whilst in the civil context, the rate is, on the average, close to the 88%. These results encourage the continuation of the development and the testing of the method in order to support its practical application in casework.

Classification supervisée multi-étiquette en actes de dialogue: analyse discriminante et transformations de Schoenberg

Abstract This work studies the multi-label classification of turns in simple English Wikipedia talk pages into dialog acts. The treated dataset was created and multi-labeled by (Ferschke et al., 2012). The first part analyses dependences between labels, in order to examine the annotation coherence and to determine a classification method. Then, a multi-label classification is computed, after transforming the problem into binary relevance. Regarding features, whereas (Ferschke et al., 2012) use features such as uni-, bi-, and trigrams, time distance between turns or the indentation level of the turn, other features are considered here: lemmas, part-of-speech tags and the meaning of verbs (according to WordNet). The dataset authors applied approaches such as Naive Bayes or Support Vector Machines. The present paper proposes, as an alternative, to use Schoenberg transformations which, following the example of kernel methods, transform original Euclidean distances into other Euclidean distances, in a space of high dimensionality. Résumé Ce travail étudie la classification supervisée multi-étiquette en actes de dialogue des tours de parole des contributeurs aux pages de discussion de Simple English Wikipedia (Wikipédia en anglais simple). Le jeu de données considéré a été créé et multi-étiqueté par (Ferschke et al., 2012). Une première partie analyse les relations entre les étiquettes pour examiner la cohérence des annotations et pour déterminer une méthode de classification. Ensuite, une classification supervisée multi-étiquette est effectuée, après recodage binaire des étiquettes. Concernant les variables, alors que (Ferschke et al., 2012) utilisent des caractéristiques telles que les uni-, bi- et trigrammes, le temps entre les tours de parole ou l'indentation d'un tour de parole, d'autres descripteurs sont considérés ici : les lemmes, les catégories morphosyntaxiques et le sens des verbes (selon WordNet). Les auteurs du jeu de données ont employé des approches telles que le Naive Bayes ou les Séparateurs à Vastes Marges (SVM) pour la classification. Cet article propose, de façon alternative, d'utiliser et d'étendre l'analyse discriminante linéaire aux transformations de Schoenberg qui, à l'instar des méthodes à noyau, transforment les distances euclidiennes originales en d'autres distances euclidiennes, dans un espace de haute dimensionnalité.

External Validation of the Prestroke Independence, Sex, Age, National Institutes of Health Stroke Scale (ISAN) Score for Predicting Stroke-Associated Pneumonia in the Athens Stroke Registry.

BACKGROUND AND PURPOSE: The Prestroke Independence, Sex, Age, National Institutes of Health Stroke Scale (ISAN) score was developed recently for predicting stroke-associated pneumonia (SAP), one of the most common complications after stroke. The aim of the present study was to externally validate the ISAN score. METHODS: Data included in the Athens Stroke Registry between June 1992 and December 2011 were used for this analysis. Inclusion criteria were the availability of all ISAN score variables (prestroke independence, sex, age, National Institutes of Health Stroke Scale score). Receiver operating characteristic curves and linear regression analyses were used to determine the discriminatory power of the score and to assess the correlation between actual and predicted pneumonia in the study population. Separate analyses were performed for patients with acute ischemic stroke (AIS) and intracerebral hemorrhage (ICH). RESULTS: The analysis included 3204 patients (AIS: 2732, ICH: 472). The ISAN score demonstrated excellent discrimination in patients with AIS (area under the curve [AUC]: .83 [95% confidence interval {CI}: .81-.85]). In the ICH group, the score was less effective (AUC: .69 [95% CI: .63-.74]). Higher-risk groups of ISAN score were associated with an increased relative risk of SAP; risk increase was more prominent in the AIS population. Predicted pneumonia correlated very well with actual pneumonia (AIS group: R(2) = .885; β-coefficient = .941, P < .001; ICH group: R(2) = .880, β-coefficient = .938, P < .001). CONCLUSIONS: In our external validation in the Athens Stroke Registry cohort, the ISAN score predicted SAP very accurately in AIS patients and demonstrated good discriminatory power in the ICH group. Further validation and assessment of clinical usefulness would strengthen the score's utility further.

Classification models for neurocognitive impairment in HIV infection based on demographic and clinical variables

Objective: We used demographic and clinical data to design practical classification models for prediction of neurocognitive impairment (NCI) in people with HIV infection. Methods: The study population comprised 331 HIV-infected patients with available demographic, clinical, and neurocognitive data collected using a comprehensive battery of neuropsychological tests. Classification and regression trees (CART) were developed to btain detailed and reliable models to predict NCI. Following a practical clinical approach, NCI was considered the main variable for study outcomes, and analyses were performed separately in treatment-naïve and treatment-experienced patients. Results: The study sample comprised 52 treatment-naïve and 279 experienced patients. In the first group, the variables identified as better predictors of NCI were CD4 cell count and age (correct classification [CC]: 79.6%, 3 final nodes). In treatment-experienced patients, the variables most closely related to NCI were years of education, nadir CD4 cell count, central nervous system penetration-effectiveness score, age, employment status, and confounding comorbidities (CC: 82.1%, 7 final nodes). In patients with an undetectable viral load and no comorbidities, we obtained a fairly accurate model in which the main variables were nadir CD4 cell count, current CD4 cell count, time on current treatment, and past highest viral load (CC: 88%, 6 final nodes). Conclusion: Practical classification models to predict NCI in HIV infection can be obtained using demographic and clinical variables. An approach based on CART analyses may facilitate screening for HIV-associated neurocognitive disorders and complement clinical information about risk and protective factors for NCI in HIV-infected patients.

Identification of imaging selection patterns in acute ischemic stroke patients and the influence on treatment and clinical trial enrollment decision making.

BACKGROUND AND PURPOSE: For the STroke Imaging Research (STIR) and VISTA-Imaging Investigators The purpose of this study was to collect precise information on the typical imaging decisions given specific clinical acute stroke scenarios. Stroke centers worldwide were surveyed regarding typical imaging used to work up representative acute stroke patients, make treatment decisions, and willingness to enroll in clinical trials. METHODS: STroke Imaging Research and Virtual International Stroke Trials Archive-Imaging circulated an online survey of clinical case vignettes through its website, the websites of national professional societies from multiple countries as well as through email distribution lists from STroke Imaging Research and participating societies. Survey responders were asked to select the typical imaging work-up for each clinical vignette presented. Actual images were not presented to the survey responders. Instead, the survey then displayed several types of imaging findings offered by the imaging strategy, and the responders selected the appropriate therapy and whether to enroll into a clinical trial considering time from onset, clinical presentation, and imaging findings. A follow-up survey focusing on 6 h from onset was conducted after the release of the positive endovascular trials. RESULTS: We received 548 responses from 35 countries including 282 individual centers; 78% of the centers originating from Australia, Brazil, France, Germany, Spain, United Kingdom, and United States. The specific onset windows presented influenced the type of imaging work-up selected more than the clinical scenario. Magnetic Resonance Imaging usage (27-28%) was substantial, in particular for wake-up stroke. Following the release of the positive trials, selection of perfusion imaging significantly increased for imaging strategy. CONCLUSIONS: Usage of vascular or perfusion imaging by Computed Tomography or Magnetic Resonance Imaging beyond just parenchymal imaging was the primary work-up (62-87%) across all clinical vignettes and time windows. Perfusion imaging with Computed Tomography or Magnetic Resonance Imaging was associated with increased probability of enrollment into clinical trials for 0-3 h. Following the release of the positive endovascular trials, selection of endovascular only treatment for 6 h increased across all clinical vignettes.

Genetically-defined deficiency of mannose-binding lectin is associated with protection after experimental stroke in mice and outcome in human stroke

The complement system is a major effector of innate immunity that has been involved in stroke brain damage. Complement activation occurs through the classical, alternative and lectin pathways. The latter is initiated by mannose-binding lectin (MBL) and MBL-associated serine proteases (MASPs). Here we investigated whether the lectin pathway contributes to stroke outcome in mice and humans.