Utilidad del Cálculo del Índice tobillo-brazo en pacientes no diabéticos con factores de riesgo cardiovascular en la identificación de pacientes de alto riesgo; Concordancia con tablas de riesgo cardiovascular (REGICOR y SCORE)

L’objectiu de l’estudi va ser la determinació de la prevalença de malaltia arterial perifèrica mitjançant el càlcul de l'Índex turmell-braç (ITB) en pacients sense malaltia vascular associada, no diabètics, amb 2 o més factors de risc cardiovascular (RCV); Determinant la seva concordança amb les taules de RCV de REGICOR i SCORE i veure quina d’elles classifica millor a aquests pacients. Es va seleccionar una mostra aleatòria de pacients entre 50 i 65 anys. El resultat de l’estudi demostra que la prevalença és baixa i no s’estableix concordança entre les taules de RCV de REGICOR i SCORE i el càlcul del ITB.

Scores de mesure fonctionnelle articulaire pour le praticien [Joint functional outcome score for the clinician].

The sports clinician faces multiple treatment options when dealing with overload injuries, and it is important to evaluate their outcomes. Multiple scores exist, some clincian rated (CRO), others patient rated (PRO), the latter being currently favoured. This review presents some of these scores and we selected the ones we feel are the most appropriate for a sports clinician. We considered these common problems: tennis elbow, rotator cuff issues, groin pain, patellofemoral pain syndrome, achilles tendinopathy and ankle instability. In addition, an activity level score is useful to weigh the result in the context of return to performance. These scores help to create a common language between therapists and to evaluate treatments objectively.

Visual search in spatial neglect studied with a preview paradigm.

Impaired visual search is a hallmark of spatial neglect. When searching for an unique feature (e.g., color) neglect patients often show only slight visual field asymmetries. In contrast, when the target is defined by a combination of features (e.g., color and form) they exhibit a severe deficit of contralesional search. This finding suggests a selective impairment of the serial deployment of spatial attention. Here, we examined this deficit with a preview paradigm. Neglect patients searched for a target defined by the conjunction of shape and color, presented together with varying numbers of distracters. The presentation time was varied such that on some trials participants previewed the target together with same-shape/different-color distracters, for 300 or 600 ms prior to the appearance of additional different-shape/same-color distracters. On the remaining trials the target and all distracters were shown simultaneously. Healthy participants exhibited a serial search strategy only when all items were presented simultaneously, whereas in both preview conditions a pop-out effect was observed. Neglect patients showed a similar pattern when the target was presented in the right hemifield. In contrast, when searching for a target in the left hemifield they showed serial search in the no-preview condition, as well as with a preview of 300 ms, and partly even at 600 ms. A control experiment suggested that the failure to fully benefit from item preview was probably independent of accurate perception of time. Our results, when viewed in the context of existing literature, lead us to conclude that the visual search deficit in neglect reflects two additive factors: a biased representation of attentional priority in favor of ipsilesional information and exaggerated capture of attention by ipsilesional abrupt onsets.

Optimization of spatial resolution for peripheral magnetic resonance angiography.

RATIONALE AND OBJECTIVES: To determine optimum spatial resolution when imaging peripheral arteries with magnetic resonance angiography (MRA). MATERIALS AND METHODS: Eight vessel diameters ranging from 1.0 to 8.0 mm were simulated in a vascular phantom. A total of 40 three-dimensional flash MRA sequences were acquired with incremental variations of fields of view, matrix size, and slice thickness. The accurately known eight diameters were combined pairwise to generate 22 "exact" degrees of stenosis ranging from 42% to 87%. Then, the diameters were measured in the MRA images by three independent observers and with quantitative angiography (QA) software and used to compute the degrees of stenosis corresponding to the 22 "exact" ones. The accuracy and reproducibility of vessel diameter measurements and stenosis calculations were assessed for vessel size ranging from 6 to 8 mm (iliac artery), 4 to 5 mm (femoro-popliteal arteries), and 1 to 3 mm (infrapopliteal arteries). Maximum pixel dimension and slice thickness to obtain a mean error in stenosis evaluation of less than 10% were determined by linear regression analysis. RESULTS: Mean errors on stenosis quantification were 8.8% +/- 6.3% for 6- to 8-mm vessels, 15.5% +/- 8.2% for 4- to 5-mm vessels, and 18.9% +/- 7.5% for 1- to 3-mm vessels. Mean errors on stenosis calculation were 12.3% +/- 8.2% for observers and 11.4% +/- 15.1% for QA software (P = .0342). To evaluate stenosis with a mean error of less than 10%, maximum pixel surface, the pixel size in the phase direction, and the slice thickness should be less than 1.56 mm2, 1.34 mm, 1.70 mm, respectively (voxel size 2.65 mm3) for 6- to 8-mm vessels; 1.31 mm2, 1.10 mm, 1.34 mm (voxel size 1.76 mm3), for 4- to 5-mm vessels; and 1.17 mm2, 0.90 mm, 0.9 mm (voxel size 1.05 mm3) for 1- to 3-mm vessels. CONCLUSION: Higher spatial resolution than currently used should be selected for imaging peripheral vessels.

Aplicación de un score semiquantitativo de tac-ar para el control y evaluación del pronóstico de pacientes con fibrosis pulmonar idiopática

Estudi prospectiu amb 36 pacients, on definírem un score semiquantitatiu per a diferents patrons de FPI a la TCAR, i la suma resultant (Score Total). Estudiàrem la relació amb paràmetres funcionals i cel.lularitat del RBA, analitzant-se’n les diferències amb els pacients morts. Trobàrem correlació entre el score de bresca (honeycomb) i total amb alguns paràmetres funcionals, prova de marxa de 6 minuts i la gasometria arterial. Els morts hi tenien major score total i tendència a la neutrofília. Concluírem que un score semiquantitatiu de TCAR és útil per a valorar la gravetat inicial i preveure l’evolució de la FPI. Paraules clau: TCAR, FPI, Score semiquantitatiu, gravetat, evolució.

Hierarchical conditional random fields for parts based models matching

A parts based model is a parametrization of an object class using a collection of landmarks following the object structure. The matching of parts based models is one of the problems where pairwise Conditional Random Fields have been successfully applied. The main reason of their effectiveness is tractable inference and learning due to the simplicity of involved graphs, usually trees. However, these models do not consider possible patterns of statistics among sets of landmarks, and thus they sufffer from using too myopic information. To overcome this limitation, we propoese a novel structure based on a hierarchical Conditional Random Fields, which we explain in the first part of this memory. We build a hierarchy of combinations of landmarks, where matching is performed taking into account the whole hierarchy. To preserve tractable inference we effectively sample the label set. We test our method on facial feature selection and human pose estimation on two challenging datasets: Buffy and MultiPIE. In the second part of this memory, we present a novel approach to multiple kernel combination that relies on stacked classification. This method can be used to evaluate the landmarks of the parts-based model approach. Our method is based on combining responses of a set of independent classifiers for each individual kernel. Unlike earlier approaches that linearly combine kernel responses, our approach uses them as inputs to another set of classifiers. We will show that we outperform state-of-the-art methods on most of the standard benchmark datasets.

Imaging Properties of MS Lesions Correlate with Attention Deficits in Early Multiple Sclerosis

Introduction: Cognitive impairment affects 40-65% of multiple sclerosis (MS) patients, often since early stages of the disease (relapsing remitting MS, RRMS). Frequently affected functions are memory, attention or executive abilities but the most sensitive measure of cognitive deficits in early MS is the information processing speed (Amato, 2008). MRI has been extensively exploited to investigate the substrate of cognitive dysfunction in MS but the underlying physiopathological mechanisms remain unclear. White matter lesion load, whole-brain atrophy and cortical lesions' number play a role but correlations are in some cases modest (Rovaris, 2006; Calabrese, 2009). In this study, we aimed at characterizing and correlating the T1 relaxation times of cortical and sub-cortical lesions with cognitive deficits detected by neuropsychological tests in a group of very early RR MS patients. Methods: Ten female patients with very early RRMS (age: 31.6 ±4.7y; disease duration: 3.8 ±1.9y; EDSS disability score: 1.8 ±0.4) and 10 age- and gender-matched healthy volunteers (mean age: 31.2 ±5.8y) were included in the study. All participants underwent the following neuropsychological tests: Rao's Brief Repeatable Battery of Neuropsychological tests (BRB-N), Stockings of Cambridge, Trail Making Test (TMT, part A and B), Boston Naming Test, Hooper Visual Organization Test and copy of the Rey-Osterrieth Complex Figure. Within 2 weeks from neuropsychological assessment, participants underwent brain MRI at 3T (Magnetom Trio a Tim System, Siemens, Germany) using a 32-channel head coil. The imaging protocol included 3D sequences with 1x1x1.2 mm3 resolution and 256x256x160 matrix, except for axial 2D-FLAIR: -DIR (T2-weighted, suppressing both WM and CSF; Pouwels, 2006) -MPRAGE (T1-weighted; Mugler, 1991) -MP2RAGE (T1-weighted with T1 maps; Marques, 2010) -FLAIR SPACE (only for patient 4-10, T2-weighted; Mugler, 2001) -2D Axial FLAIR (0.9x0.9x2.5 mm3, 256x256x44 matrix). Lesions were identified by one experienced neurologist and radiologist using all contrasts, manually contoured and assigned to regional locations (cortical or sub-cortical). Lesion number, volume and T1 relaxation time were calculated for lesions in each contrast and in a merged mask representing the union of the lesions from all contrasts. T1 relaxation times of lesions were normalized with the mean T1 value in corresponding control regions of the healthy subjects. Statistical analysis was performed using GraphPad InStat software. Cognitive scores were compared between patients and controls with paired t-tests; p values ≤ 0.05 were considered significant. Spearmann correlation tests were performed between the cognitive tests, which differed significantly between patients and controls, and lesions' i) number ii) volume iii) T1 relaxation time iv) disease duration and v) years of study. Results: Cortical and sub-cortical lesions count, T1 values and volume are reported in Table 1 (A and B). All early RRMS patients showed cortical lesions (CLs) and the majority consisted of CLs type I (lesions with a cortical component extending to the sub-cortical tissue). The rest of cortical lesions were characterized as type II (intra-cortical lesions). No type III/IV lesions (large sub-pial lesions) were detected. RRMS patients were slightly less educated (13.5±2.5y vs. 16.3±1.8y of study, p=0.02) than the controls. Signs of cortical dysfunction (i.e. impaired learning, language, visuo-spatial skills or gnosis) were rare in all patients. However, patients showed on average lower scores on measures of visual attention and information processing speed (TMT-part A: p=0.01; TMT-part B: p=0.006; PASAT-included in the BRB-N: p=0.04). The T1 relaxation values of CLs type I negatively correlated with the TMT-part A score (r=0.78, p<0.01). The correlations of TMT-part B score and PASAT score with T1 relaxation time of lesions as well and the correlation between TMT-part A, TMT-part B and PASAT score with lesions' i) number ii) volume iii) disease duration and iv) years of study did not reach significance. In order to preclude possible influences from partial volume effects on the T1 values, the correlation between lesion volume and T1 value of CLs type I was calculated; no correlation was found, suggesting that partial volume effects did not affect the statistics. Conclusions: The present pilot study reports for the first time the presence and the T1 characteristics at 3 T of cortical lesions in very early RRMS (< 6 y disease duration). It also shows that CLS type I represents the most frequent cortical lesion type in this cohort of RRMS patients. In addition, it reveals a negative correlation between the attentional test TMT-part A and the T1 properties of cortical lesions type I. In other words, lower attention deficits are concomitant with longer T1-relaxation time in cortical lesions. In respect to this last finding, it could be speculated that long relaxation time correspond to a certain degree of tissue loss that is enough to stimulate compensatory mechanisms. This hypothesis is in line with previous fMRI studies showing functional compensatory mechanisms to help maintaining normal or sub-normal attention performances in RR MS patients (Penner, 2003).

Temporal and spatial distribution of Leishmania mexicana infections in a population of Neotoma micropus

A 19-month mark-release-recapture study of Neotoma micropus with sequential screening for Leishmania mexicana was conducted in Bexar County, Texas, USA. The overall prevalence rate was 14.7% and the seasonal prevalence rates ranged from 3.8 to 26.7%. Nine incident cases were detected, giving an incidence rate of 15.5/100 rats/year. Follow-up of 101 individuals captured two or more times ranged from 14 to 462 days. Persistence of L. mexicana infections averaged 190 days and ranged from 104 to 379 days. Data on dispersal, density, dispersion, and weight are presented, and the role of N. micropus as a reservoir host for L. mexicana is discussed.

Machine learning algorithms for spatial data. Case studies: Environmental pollution, natural hazards, renewable resources

This paper presents general problems and approaches for the spatial data analysis using machine learning algorithms. Machine learning is a very powerful approach to adaptive data analysis, modelling and visualisation. The key feature of the machine learning algorithms is that they learn from empirical data and can be used in cases when the modelled environmental phenomena are hidden, nonlinear, noisy and highly variable in space and in time. Most of the machines learning algorithms are universal and adaptive modelling tools developed to solve basic problems of learning from data: classification/pattern recognition, regression/mapping and probability density modelling. In the present report some of the widely used machine learning algorithms, namely artificial neural networks (ANN) of different architectures and Support Vector Machines (SVM), are adapted to the problems of the analysis and modelling of geo-spatial data. Machine learning algorithms have an important advantage over traditional models of spatial statistics when problems are considered in a high dimensional geo-feature spaces, when the dimension of space exceeds 5. Such features are usually generated, for example, from digital elevation models, remote sensing images, etc. An important extension of models concerns considering of real space constrains like geomorphology, networks, and other natural structures. Recent developments in semi-supervised learning can improve modelling of environmental phenomena taking into account on geo-manifolds. An important part of the study deals with the analysis of relevant variables and models' inputs. This problem is approached by using different feature selection/feature extraction nonlinear tools. To demonstrate the application of machine learning algorithms several interesting case studies are considered: digital soil mapping using SVM, automatic mapping of soil and water system pollution using ANN; natural hazards risk analysis (avalanches, landslides), assessments of renewable resources (wind fields) with SVM and ANN models, etc. The dimensionality of spaces considered varies from 2 to more than 30. Figures 1, 2, 3 demonstrate some results of the studies and their outputs. Finally, the results of environmental mapping are discussed and compared with traditional models of geostatistics.

Ruling out coronary heart disease in primary care patients with chest pain : a clinical prediction score

ABSTRACT: BACKGROUND: Chest pain raises concern for the possibility of coronary heart disease. Scoring methods have been developed to identify coronary heart disease in emergency settings, but not in primary care. METHODS: Data were collected from a multicenter Swiss clinical cohort study including 672 consecutive patients with chest pain, who had visited one of 59 family practitioners' offices. Using delayed diagnosis we derived a prediction rule to rule out coronary heart disease by means of a logistic regression model. Known cardiovascular risk factors, pain characteristics, and physical signs associated with coronary heart disease were explored to develop a clinical score. Patients diagnosed with angina or acute myocardial infarction within the year following their initial visit comprised the coronary heart disease group. RESULTS: The coronary heart disease score was derived from eight variables: age, gender, duration of chest pain from 1 to 60 minutes, substernal chest pain location, pain increases with exertion, absence of tenderness point at palpation, cardiovascular risks factors, and personal history of cardiovascular disease. Area under the receiver operating characteristics curve was of 0.95 with a 95% confidence interval of 0.92; 0.97. From this score, 413 patients were considered as low risk for values of percentile 5 of the coronary heart disease patients. Internal validity was confirmed by bootstrapping. External validation using data from a German cohort (Marburg, n = 774) revealed a receiver operating characteristics curve of 0.75 (95% confidence interval, 0.72; 0.81) with a sensitivity of 85.6% and a specificity of 47.2%. CONCLUSIONS: This score, based only on history and physical examination, is a complementary tool for ruling out coronary heart disease in primary care patients complaining of chest pain.