Use of patients’ classification instruments: analysis of the brazilian production of knowledge

Objective To analyze the production of scientific knowledge about the use of patients’ classification instruments in care and management practice in Brazil. Method Integrative literature review with databases search in: Latin American and Caribbean Literature on Health Sciences (LILACS), Medical Literature Analysis and Retrieval System on-line (MEDLINE), Cumulative Index to Nursing and Allied Health Literature (CINAHL) and SCOPUS, between January 2002 through December 2013. Results 1,194 studies were found, 31 met the inclusion criteria. We observed a higher number of studies in the category care plans and workload (n=15), followed by the category evaluation of psychometric properties (n=14). Conclusion Brazilian knowledge production has not yet investigated some purposes of using instruments for classifying patients in professional nursing practice. The identification of unexplored areas can guide future research on the topic.


Terms of international classification for Nursing Practice in motor and physical rehabilitation

OBJECTIVE To validate terms of nursing language especially for physical-motor rehabilitation and map them to the terms of ICNP® 2.0. METHOD A methodology research based on document analysis, with collection and analysis of terms from 1,425 records. RESULTS 825 terms were obtained after the methodological procedure, of which 226 had still not been included in the ICNP® 2.0. These terms were distributed as follows: 47 on the Focus axis; 15 on the Judgment axis; 31 on the Action axis; 25 on the Location axis; 102 on the Means axis; three on the Time axis; and three on the Client axis. All non-constant terms in ICNP® have been validated by experts, having reached an agreement index ≥0.80. CONCLUSION The ICNP® is applicable and used in nursing care for physical-motor rehabilitation.

Incidence of local complications and risk factors associated with peripheral intravenous catheter in neonates

Abstract OBJECTIVE To evaluate the incidence of complications related to the use of peripheral intravenous catheter in neonates and identify the associated risk factors. METHOD Prospective cohort study conducted in a Neonatal Intensive Care Unit. Participants were the hospitalized neonates undergoing peripheral intravenous puncture in the period from February to June 2013. RESULTS The incidence of complications was 63.15%, being infiltration/extravasation (69.89%), phlebitis (17.84%) and obstruction (12.27%). The risk factors were the presence of infection (p = 0.0192) and weight at the puncture day (p = 0.0093), type of intermittent infusion associated with continuous infusion (p <0.0001), endotracheal intubation (p = 0.0008), infusion of basic plan (p = 0.0027), total parenteral nutrition (P = 0.0002), blood transfusion associated with other infusions (p = 0.0003) and other drugs (p = 0.0004). Higher risk of developing complications in the first 48 hours after puncture. CONCLUSION A high rate of complications related to the use of peripheral intravenous catheter, and risk factors associated with infection, weight, drugs and infused solutions, and type of infusion.

Local volatility changes in the black-scholes model

In this paper we address a problem arising in risk management; namely the study of price variations of different contingent claims in the Black-Scholes model due to anticipating future events. The method we propose to use is an extension of the classical Vega index, i.e. the price derivative with respect to the constant volatility, in thesense that we perturb the volatility in different directions. Thisdirectional derivative, which we denote the local Vega index, will serve as the main object in the paper and one of the purposes is to relate it to the classical Vega index. We show that for all contingent claims studied in this paper the local Vega index can be expressed as a weighted average of the perturbation in volatility. In the particular case where the interest rate and the volatility are constant and the perturbation is deterministic, the local Vega index is an average of this perturbation multiplied by the classical Vega index. We also study the well-known goal problem of maximizing the probability of a perfect hedge and show that the speed of convergence is in fact dependent of the local Vega index.

Interactive local bandwidth choice

A tool for user choice of the local bandwidth function for a kernel density estimate is developed using KDE, a graphical object-oriented package for interactive kernel density estimation written in LISP-STAT. The bandwidth function is a cubic spline, whose knots are manipulated by the user in one window, while the resulting estimate appears in another window. A real data illustration of this method raises concerns, because an extremely large family of estimates is available.

Automatic classification of MR scans in Alzheimer's disease.

To be diagnostically useful, structural MRI must reliably distinguish Alzheimer's disease (AD) from normal aging in individual scans. Recent advances in statistical learning theory have led to the application of support vector machines to MRI for detection of a variety of disease states. The aims of this study were to assess how successfully support vector machines assigned individual diagnoses and to determine whether data-sets combined from multiple scanners and different centres could be used to obtain effective classification of scans. We used linear support vector machines to classify the grey matter segment of T1-weighted MR scans from pathologically proven AD patients and cognitively normal elderly individuals obtained from two centres with different scanning equipment. Because the clinical diagnosis of mild AD is difficult we also tested the ability of support vector machines to differentiate control scans from patients without post-mortem confirmation. Finally we sought to use these methods to differentiate scans between patients suffering from AD from those with frontotemporal lobar degeneration. Up to 96% of pathologically verified AD patients were correctly classified using whole brain images. Data from different centres were successfully combined achieving comparable results from the separate analyses. Importantly, data from one centre could be used to train a support vector machine to accurately differentiate AD and normal ageing scans obtained from another centre with different subjects and different scanner equipment. Patients with mild, clinically probable AD and age/sex matched controls were correctly separated in 89% of cases which is compatible with published diagnosis rates in the best clinical centres. This method correctly assigned 89% of patients with post-mortem confirmed diagnosis of either AD or frontotemporal lobar degeneration to their respective group. Our study leads to three conclusions: Firstly, support vector machines successfully separate patients with AD from healthy aging subjects. Secondly, they perform well in the differential diagnosis of two different forms of dementia. Thirdly, the method is robust and can be generalized across different centres. This suggests an important role for computer based diagnostic image analysis for clinical practice.

A data-dependent skeleton estimate and a scale-sensitive dimension for classification

The classical binary classification problem is investigatedwhen it is known in advance that the posterior probability function(or regression function) belongs to some class of functions. We introduceand analyze a method which effectively exploits this knowledge. The methodis based on minimizing the empirical risk over a carefully selected``skeleton'' of the class of regression functions. The skeleton is acovering of the class based on a data--dependent metric, especiallyfitted for classification. A new scale--sensitive dimension isintroduced which is more useful for the studied classification problemthan other, previously defined, dimension measures. This fact isdemonstrated by performance bounds for the skeleton estimate in termsof the new dimension.

Active learning methods for remote sensing image classification

In this paper, we propose two active learning algorithms for semiautomatic definition of training samples in remote sensing image classification. Based on predefined heuristics, the classifier ranks the unlabeled pixels and automatically chooses those that are considered the most valuable for its improvement. Once the pixels have been selected, the analyst labels them manually and the process is iterated. Starting with a small and nonoptimal training set, the model itself builds the optimal set of samples which minimizes the classification error. We have applied the proposed algorithms to a variety of remote sensing data, including very high resolution and hyperspectral images, using support vector machines. Experimental results confirm the consistency of the methods. The required number of training samples can be reduced to 10% using the methods proposed, reaching the same level of accuracy as larger data sets. A comparison with a state-of-the-art active learning method, margin sampling, is provided, highlighting advantages of the methods proposed. The effect of spatial resolution and separability of the classes on the quality of the selection of pixels is also discussed.

Cartographier les géomorphosites : objectifs, publics et propositions méthodologiques

Related to the raise of the awareness of the importance of the Earth heritage, geomorphosites receive increasing attention from the scientific community. Assessment methods, classification and conservation strategies have been developed to safeguard the geomorphological heritage for present and future generations. On the other hand, Earth heritage offers opportunities to develop educational and recreational programs as well as tourism projects. Various interpretive supports and local development projects have been engendered in the past few years to promote geoheritage.¦Be it for the assessment, conservation or promotion of geomorphosites, maps are valuable from many standpoints. They can provide fundamental data for detailed geomorphosite description, serve as visual communication tools helping to guide the selection process in defining protection priority or supporting Earth heritage promotion and interpretàtion.¦This study reviews the main achievements and the objectives yet to be accomplished in the field of geomorphosite mapping and proposes a general framework for the mapping of geomorphosites that takes into account the different aims and publics. The main focus is on mapping geomorphosites for non-specialists in the field of Earth heritage promotion (Geotourism). In this context, maps are often employed to show itineraries or points of interest. Like a scheme or a diagram, a map can also be used as a method for visualising geoscientific information. This function is particularly important since some processes, which contributed to the formation of a geomorphosite or a geomorphological landscape are no longer or not always clearly visible in the landscape. In this case, maps become interpretive media that serve popularisation purposes.¦Mapping for non-specialists holds the challenging task to ensure the information transfer between the cartographer and the user. We therefore focus on both the implementation of the map by the cartographer (which information? which visualisation?) and the interpretation of the map by the user (effectiveness of the knowledge transfer). The research is based on empirical studies carried out in the Maderan valley (Canton of Uri) and in classes of the Cantons of Uri and Tessin that aim to gain knowledge about the familiarity and interests of non- specialists for geoheritage as well as about their map reading skills. The final objective is to formulate methodological proposals for geomorphosite mapping for interpretive purpose.

A surface-based approach to quantify local cortical gyrification.

The high complexity of cortical convolutions in humans is very challenging both for engineers to measure and compare it, and for biologists and physicians to understand it. In this paper, we propose a surface-based method for the quantification of cortical gyrification. Our method uses accurate 3-D cortical reconstruction and computes local measurements of gyrification at thousands of points over the whole cortical surface. The potential of our method to identify and localize precisely gyral abnormalities is illustrated by a clinical study on a group of children affected by 22q11 Deletion Syndrome, compared to control individuals.

Staphylococcus aureus clfB and spa alleles of the repeat regions are segregated into major phylogenetic lineages.

To reliably differentiate among Staphylococcus aureus isolates we recently developed the Double Locus Sequence Typing (DLST) based on the analysis of partial sequences of clfB and spa genes. This method is highly discriminatory and gives unambiguous definition of types. The highly clonal population structure of S. aureus suggests that isolates with identical clfB or spa alleles belong to the same clonal complex (CC) defined by Multi-Locus Sequence Typing (MLST). To test this hypothesis as well as to investigate putative intra-CC genetic structure, we analyzed a total of 289 isolates (186 MSSA and 103 MRSA) with DLST-, spa- and MLST-typing. Among the 289 strains, 242 were clustered into 7 major MLST CCs, 40 into minor CCs and 7 were not grouped into CCs. A total of 205 DLST- and 129 spa-types were observed. With one exception, all DLST-clfB, DLST-spa and spa-type alleles were segregated into CCs. DLST-types sharing an identical allele (clfB or spa) were clustered using eBURST. Except for one strain, all isolates from each DLST cluster belonged to the same CC. However, using both DLST- and spa-typing we were not able to disclose a clear intra-CC structure. Nevertheless, the high diversity of these loci confirmed that they are good markers for local epidemiological investigations.

Period-Luminosity-Colour distribution and classification of Galactic oxygen-rich LPVs I. Luminosity calibrations

The absolute K magnitudes and kinematic parameters of about 350 oxygen-rich Long-Period Variable stars are calibrated, by means of an up-to-date maximum-likelihood method, using HIPPARCOS parallaxes and proper motions together with radial velocities and, as additional data, periods and V-K colour indices. Four groups, differing by their kinematics and mean magnitudes, are found. For each of them, we also obtain the distributions of magnitude, period and de-reddened colour of the base population, as well as de-biased period-luminosity-colour relations and their two-dimensional projections. The SRa semiregulars do not seem to constitute a separate class of LPVs. The SRb appear to belong to two populations of different ages. In a PL diagram, they constitute two evolutionary sequences towards the Mira stage. The Miras of the disk appear to pulsate on a lower-order mode. The slopes of their de-biased PL and PC relations are found to be very different from the ones of the Oxygen Miras of the LMC. This suggests that a significant number of so-called Miras of the LMC are misclassified. This also suggests that the Miras of the LMC do not constitute a homogeneous group, but include a significant proportion of metal-deficient stars, suggesting a relatively smooth star formation history. As a consequence, one may not trivially transpose the LMC period-luminosity relation from one galaxy to the other.

Utility scores associated with the world health organisation drinking risk-level classification in alcohol dependence

BACKGROUND: Extensive research exists estimating the effect hazardous alcohol¦use on morbidity and mortality, but little research quantifies the association between¦alcohol consumption and utility scores in patients with alcohol dependence.¦In the context of comparative research, the World Health Organisation (WHO)¦proposed to categorise the risk for alcohol-related acute and chronic harm according¦to patients' average daily alcohol consumption. OBJECTIVES: To estimate utility¦scores associated with each category of the WHO drinking risk-level classification¦in patients with alcohol dependence (AD). METHODS: We used data from¦CONTROL, an observational cohort study including 143 AD patients from the Alcohol¦Treatment Center at Lausanne University Hospital, followed for 12 months.¦Average daily alcohol consumption was assessed monthly using the Timeline Follow-¦back method and patients were categorised according to the WHO drinking¦risk-level classification: abstinent, low, medium, high and very high. Other measures¦as sociodemographic characteristics and utility scores derived from the EuroQoL¦5-Dimensions questionnaire (EQ-5D) were collected every three months.¦Mixed models for repeated measures were used to estimate mean utility scores¦associated with WHO drinking risk-level categories. RESULTS: A total of 143 patients¦were included and the 12-month follow-up permitting the assessment of¦1318 person-months. At baseline the mean age of the patients was 44.6 (SD 11.8)¦and the majority of patients was male (63.6%). Using repeated measures analysis,¦utility scores decreased with increasing drinking levels, ranging from 0.80 in abstinent¦patients to 0.62 in patients with very high risk drinking level (p_0.0001).¦CONCLUSIONS: In this sample of patients with alcohol dependence undergoing¦specialized care, utility scores estimated from the EQ-5D appeared to substantially¦and consistently vary according to patients' WHO drinking level.

Local ocular immunomodulation resulting from electrotransfer of plasmid encoding soluble TNF receptors in the ciliary muscle.

PURPOSE: Plasmid electrotransfer in the ciliary muscle allows the sustained release of therapeutic proteins within the eye. The aim of this study was to evaluate whether the ocular production of TNF-alpha soluble receptor, using this nonviral gene therapy method, could have a beneficial local effect in a model of experimental autoimmune uveoretinitis (EAU). METHODS: Injection of a plasmid encoding a TNF-alpha p55 receptor (30 microg) in the ciliary muscle, combined with electrotransfer (200 V/cm), was carried out in Lewis rat eyes 4 days before the induction of EAU by S-antigen. Control eyes received naked plasmid electrotransfer or simple injection of the therapeutic plasmid. The disease was evaluated clinically and histologically. Cytokines and chemokines were analyzed in the ocular media by multiplex assay performed 15 and 21 days after immunization. RESULTS: Ocular TNF-alpha blockade, resulting from the local secretion of soluble receptors, was associated with delayed and significantly less severe uveitis, together with a reduction of the retinal damages. Compared with the controls, treated eyes showed significantly lower levels of IL-1beta and MCP1, higher levels of IL-13 and IL-4, and reduced NOS-2 expression in infiltrating cells. Treatment did not influence TNF-alpha levels in inguinal lymph nodes. CONCLUSIONS: Taken together, these results indicate that local immunomodulation was achieved and that no systemic adverse effects of TNF-alpha blockade observed after systemic injection of TNF-alpha inhibitors should be expected.

Semi-supervised remote sensing image classification with cluster kernels

A semisupervised support vector machine is presented for the classification of remote sensing images. The method exploits the wealth of unlabeled samples for regularizing the training kernel representation locally by means of cluster kernels. The method learns a suitable kernel directly from the image and thus avoids assuming a priori signal relations by using a predefined kernel structure. Good results are obtained in image classification examples when few labeled samples are available. The method scales almost linearly with the number of unlabeled samples and provides out-of-sample predictions.