Développement et validation d’un index de prédiction des risques d’institutionnalisation et de décès pour le contrôle des variables confondantes non-mesurées dans la population âgée

Le biais de confusion est un défi majeur des études observationnelles, surtout s'ils sont induits par des caractéristiques difficiles, voire impossibles, à mesurer dans les banques de données administratives de soins de santé. Un des biais de confusion souvent présents dans les études pharmacoépidémiologiques est la prescription sélective (en anglais « prescription channeling »), qui se manifeste lorsque le choix du traitement dépend de l'état de santé du patient et/ou de son expérience antérieure avec diverses options thérapeutiques. Parmi les méthodes de contrôle de ce biais, on retrouve le score de comorbidité, qui caractérise l'état de santé d'un patient à partir de médicaments délivrés ou de diagnostics médicaux rapportés dans les données de facturations des médecins. La performance des scores de comorbidité fait cependant l'objet de controverses car elle semble varier de façon importante selon la population d'intérêt. Les objectifs de cette thèse étaient de développer, valider, et comparer les performances de deux scores de comorbidité (un qui prédit le décès et l’autre qui prédit l’institutionnalisation), développés à partir des banques de services pharmaceutiques de la Régie de l'assurance-maladie du Québec (RAMQ) pour leur utilisation dans la population âgée. Cette thèse vise également à déterminer si l'inclusion de caractéristiques non rapportées ou peu valides dans les banques de données administratives (caractéristiques socio-démographiques, troubles mentaux ou du sommeil), améliore la performance des scores de comorbidité dans la population âgée. Une étude cas-témoins intra-cohorte fut réalisée. La cohorte source consistait en un échantillon aléatoire de 87 389 personnes âgées vivant à domicile, répartie en une cohorte de développement (n=61 172; 70%) et une cohorte de validation (n=26 217; 30%). Les données ont été obtenues à partir des banques de données de la RAMQ. Pour être inclus dans l’étude, les sujets devaient être âgés de 66 ans et plus, et être membres du régime public d'assurance-médicaments du Québec entre le 1er janvier 2000 et le 31 décembre 2009. Les scores ont été développés à partir de la méthode du Framingham Heart Study, et leur performance évaluée par la c-statistique et l’aire sous les courbes « Receiver Operating Curves ». Pour le dernier objectif qui est de documenter l’impact de l’ajout de variables non-mesurées ou peu valides dans les banques de données au score de comorbidité développé, une étude de cohorte prospective (2005-2008) a été réalisée. La population à l'étude, de même que les données, sont issues de l'Étude sur la Santé des Aînés (n=1 494). Les variables d'intérêt incluaient statut marital, soutien social, présence de troubles de santé mentale ainsi que troubles du sommeil. Tel que décrit dans l'article 1, le Geriatric Comorbidity Score (GCS) basé sur le décès, a été développé et a présenté une bonne performance (c-statistique=0.75; IC95% 0.73-0.78). Cette performance s'est avérée supérieure à celle du Chronic Disease Score (CDS) lorsqu'appliqué dans la population à l'étude (c-statistique du CDS : 0.47; IC 95%: 0.45-0.49). Une revue de littérature exhaustive a montré que les facteurs associés au décès étaient très différents de ceux associés à l’institutionnalisation, justifiant ainsi le développement d'un score spécifique pour prédire le risque d'institutionnalisation. La performance de ce dernier s'est avérée non statistiquement différente de celle du score de décès (c-statistique institutionnalisation : 0.79 IC95% 0.77-0.81). L'inclusion de variables non rapportées dans les banques de données administratives n'a amélioré que de 11% la performance du score de décès; le statut marital et le soutien social ayant le plus contribué à l'amélioration observée. En conclusion, de cette thèse, sont issues trois contributions majeures. D'une part, il a été démontré que la performance des scores de comorbidité basés sur le décès dépend de la population cible, d'où l'intérêt du Geriatric Comorbidity Score, qui fut développé pour la population âgée vivant à domicile. D'autre part, les médicaments associés au risque d'institutionnalisation diffèrent de ceux associés au risque de décès dans la population âgé, justifiant ainsi le développement de deux scores distincts. Cependant, les performances des deux scores sont semblables. Enfin, les résultats indiquent que, dans la population âgée, l'absence de certaines caractéristiques ne compromet pas de façon importante la performance des scores de comorbidité déterminés à partir de banques de données d'ordonnances. Par conséquent, les scores de comorbidité demeurent un outil de recherche important pour les études observationnelles.

Cohesion or confusion? Towards a typology for organizational learning research

The study of organizational learning is no longer in its infancy. Since Cyert and March first introduced the notion in the early 1960s, a plethora of books and journal publications have presented their own interpretations of the meaning and significance of the term. Despite such endeavours, there is little common agreement about what organizational learning represents and how future research may build cumulatively upon the many diverse ideas articulated. The intention here is by no means to address these issues, which have been comprehensively examined elsewhere. The purpose is rather to compare and contrast approaches in order to analyse similarities and dissimilarities, together with research challenges, for each approach. This is achieved by presenting a comparative framework to categorize the literature according to (a) its prescriptive/explanatory bias and (b) in line with the level of analysis, examining whether there is a focus on the organization as a whole or upon individuals and their work communities instead. The review concludes by presenting some preliminary suggestions for cross-quadrant research. © Blackwell Publishing Ltd 2006.

Hubble parameter reconstruction from a principal component analysis: minimizing the bias

Aims. A model-independent reconstruction of the cosmic expansion rate is essential to a robust analysis of cosmological observations. Our goal is to demonstrate that current data are able to provide reasonable constraints on the behavior of the Hubble parameter with redshift, independently of any cosmological model or underlying gravity theory. Methods. Using type Ia supernova data, we show that it is possible to analytically calculate the Fisher matrix components in a Hubble parameter analysis without assumptions about the energy content of the Universe. We used a principal component analysis to reconstruct the Hubble parameter as a linear combination of the Fisher matrix eigenvectors (principal components). To suppress the bias introduced by the high redshift behavior of the components, we considered the value of the Hubble parameter at high redshift as a free parameter. We first tested our procedure using a mock sample of type Ia supernova observations, we then applied it to the real data compiled by the Sloan Digital Sky Survey (SDSS) group. Results. In the mock sample analysis, we demonstrate that it is possible to drastically suppress the bias introduced by the high redshift behavior of the principal components. Applying our procedure to the real data, we show that it allows us to determine the behavior of the Hubble parameter with reasonable uncertainty, without introducing any ad-hoc parameterizations. Beyond that, our reconstruction agrees with completely independent measurements of the Hubble parameter obtained from red-envelope galaxies.

Experimental studies of di-jet survival and surface emission bias in Au plus Au collisions via angular correlations with respect to back-to-back leading hadrons

We report first results from an analysis based on a new multi-hadron correlation technique, exploring jet-medium interactions and di-jet surface emission bias at the BNL Relativistic Heavy Ion Collider (RHIC). Pairs of back-to-back high-transverse-momentum hadrons are used for triggers to study associated hadron distributions. In contrast with two-and three-particle correlations with a single trigger with similar kinematic selections, the associated hadron distribution of both trigger sides reveals no modification in either relative pseudorapidity Delta eta or relative azimuthal angle Delta phi from d + Au to central Au + Au collisions. We determine associated hadron yields and spectra as well as production rates for such correlated back-to-back triggers to gain additional insights on medium properties.

Low-bias negative differential resistance in graphene nanoribbon superlattices

We theoretically investigate negative differential resistance (NDR) for ballistic transport in semiconducting armchair graphene nanoribbon (aGNR) superlattices (5 to 20 barriers) at low bias voltages V(SD) < 500 mV. We combine the graphene Dirac Hamiltonian with the Landauer-Buttiker formalism to calculate the current I(SD) through the system. We find three distinct transport regimes in which NDR occurs: (i) a ""classical"" regime for wide layers, through which the transport across band gaps is strongly suppressed, leading to alternating regions of nearly unity and zero transmission probabilities as a function of V(SD) due to crossing of band gaps from different layers; (ii) a quantum regime dominated by superlattice miniband conduction, with current suppression arising from the misalignment of miniband states with increasing V(SD); and (iii) a Wannier-Stark ladder regime with current peaks occurring at the crossings of Wannier-Stark rungs from distinct ladders. We observe NDR at voltage biases as low as 10 mV with a high current density, making the aGNR superlattices attractive for device applications.

Universal zero-bias conductance through a quantum wire side-coupled to a quantum dot

A numerical renormalization-group study of the conductance through a quantum wire containing noninteracting electrons side-coupled to a quantum dot is reported. The temperature and the dot-energy dependence of the conductance are examined in the light of a recently derived linear mapping between the temperature-dependent conductance and the universal function describing the conductance for the symmetric Anderson model of a quantum wire with an embedded quantum dot. Two conduction paths, one traversing the wire, the other a bypass through the quantum dot, are identified. A gate potential applied to the quantum wire is shown to control the current through the bypass. When the potential favors transport through the wire, the conductance in the Kondo regime rises from nearly zero at low temperatures to nearly ballistic at high temperatures. When it favors the dot, the pattern is reversed: the conductance decays from nearly ballistic to nearly zero. When comparable currents flow through the two channels, the conductance is nearly temperature independent in the Kondo regime, and Fano antiresonances in the fixed-temperature plots of the conductance as a function of the dot-energy signal interference between them. Throughout the Kondo regime and, at low temperatures, even in the mixed-valence regime, the numerical data are in excellent agreement with the universal mapping.

Universal zero-bias conductance for the single-electron transistor

The thermal dependence of the zero-bias conductance for the single electron transistor is the target of two independent renormalization-group approaches, both based on the spin-degenerate Anderson impurity model. The first approach, an analytical derivation, maps the Kondo-regime conductance onto the universal conductance function for the particle-hole symmetric model. Linear, the mapping is parametrized by the Kondo temperature and the charge in the Kondo cloud. The second approach, a numerical renormalization-group computation of the conductance as a function the temperature and applied gate voltages offers a comprehensive view of zero-bias charge transport through the device. The first approach is exact in the Kondo regime; the second, essentially exact throughout the parametric space of the model. For illustrative purposes, conductance curves resulting from the two approaches are compared.

Short Cognitive Performance Test: Diagnostic Accuracy and Education Bias in Older Brazilian Adults

The ""Short Cognitive Performance Test"" (Syndrom Kurztest, SKT) is a cognitive screening battery designed to detect memory and attention deficits. The aim of this study was to evaluate the diagnostic accuracy of the SKT as a screening tool for mild cognitive impairment (MCI) and dementia. A total of 46 patients with Alzheimer`s disease (AD), 82 with MCI, and 56 healthy controls were included in the study. Patients and controls were allocated into two groups according to educational level (< 8 years or > 8 years). ROC analyses suggested that the SKT adequately discriminates AD from non-demented subjects (MCI and controls), irrespective of the education group. The test had good sensitivity to discriminate MCI from unimpaired controls in the sub-sample of individuals with more than 8 years of schooling. Our findings suggest that the SKT is a good screening test for cognitive impairment and dementia. However, test results must be interpreted with caution when administered to less-educated individuals.

Residual stresses in titanium nitride thin films obtained with step variation of substrate bias voltage during deposition

In this work, a series of depositions of titanium nitride (TiN) films on M2 and D2 steel substrates were conducted in a Triode Magnetron Sputtering chamber. The temperature; gas flow and pressure were kept constant during each run. The substrate bias was either decreased or increased in a sequence of steps. Residual stress measurements were later conducted through the grazing X-ray diffraction method. Different incident angles were used in order to change the penetration depth and to obtain values of residual stress at different film depths. A model described by Dolle was adapted as an attempt to calculate the values of residual stress at each incident angle as a function of the value from each individual layer. Stress results indicated that the decrease in bias voltage during the deposition has produced compressive residual stress gradients through the film thickness. On the other hand, much less pronounced gradients were found in one of the films deposited with increasing bias voltage. (C) 2010 Elsevier B.V. All rights reserved.

TiAlN coatings deposited by triode magnetron sputtering varying the bias voltage

TiAlN films were deposited on AISI O1 tool steel using a triode magnetron sputtering system. The bias voltage effect on the composition, thickness, crystallography, microstructure, hardness and adhesion strength was investigated. The coatings thickness and elemental composition analyses were carried out using scanning electron microscopy (SEM) together with energy dispersive X-ray (EDS). The re-sputtering effect due to the high-energy ions bombardment on the film surface influenced the coatings thickness. The films crystallography was investigated using X-ray diffraction characterization. The X-ray diffraction (XRD) data show that TiAlN coatings were crystallized in the cubic NaCl B1 structure, with orientations in the {111}, {200} {220} and {311} crystallographic planes. The surface morphology (roughness and grain size) of TiAlN coatings was investigated by atomic force microscopy (AFM). By increasing the substrate bias voltage from -40 to -150 V, hardness decreased from 32 GPa to 19 GPa. Scratch tester was used for measuring the critical loads and for measuring the adhesion. (C) 2011 Elsevier B. V. All rights reserved.

Extensions of discrete triangular distributions and boundary bias in kernel estimation for discrete functions

Asymmetric discrete triangular distributions are introduced in order to extend the symmetric ones serving for discrete associated kernels in the nonparametric estimation for discrete functions. The extension from one to two orders around the mode provides a large family of discrete distributions having a finite support. Establishing a bridge between Dirac and discrete uniform distributions, some different shapes are also obtained and their properties are investigated. In particular, the mean and variance are pointed out. Applications to discrete kernel estimators are given with a solution to a boundary bias problem. (C) 2010 Elsevier B.V. All rights reserved.

Bias-corrected Pearson estimating functions for Taylor`s power law applied to benthic macrofauna data

Estimation of Taylor`s power law for species abundance data may be performed by linear regression of the log empirical variances on the log means, but this method suffers from a problem of bias for sparse data. We show that the bias may be reduced by using a bias-corrected Pearson estimating function. Furthermore, we investigate a more general regression model allowing for site-specific covariates. This method may be efficiently implemented using a Newton scoring algorithm, with standard errors calculated from the inverse Godambe information matrix. The method is applied to a set of biomass data for benthic macrofauna from two Danish estuaries. (C) 2011 Elsevier B.V. All rights reserved.

Selection bias in gene extraction on the basis of microarray gene-expression data

In the context of cancer diagnosis and treatment, we consider the problem of constructing an accurate prediction rule on the basis of a relatively small number of tumor tissue samples of known type containing the expression data on very many (possibly thousands) genes. Recently, results have been presented in the literature suggesting that it is possible to construct a prediction rule from only a few genes such that it has a negligible prediction error rate. However, in these results the test error or the leave-one-out cross-validated error is calculated without allowance for the selection bias. There is no allowance because the rule is either tested on tissue samples that were used in the first instance to select the genes being used in the rule or because the cross-validation of the rule is not external to the selection process; that is, gene selection is not performed in training the rule at each stage of the cross-validation process. We describe how in practice the selection bias can be assessed and corrected for by either performing a cross-validation or applying the bootstrap external to the selection process. We recommend using 10-fold rather than leave-one-out cross-validation, and concerning the bootstrap, we suggest using the so-called. 632+ bootstrap error estimate designed to handle overfitted prediction rules. Using two published data sets, we demonstrate that when correction is made for the selection bias, the cross-validated error is no longer zero for a subset of only a few genes.

PCR bias toward the wild-type k-ras and p53 sequences: Implications for PCR detection of mutations and cancer diagnosis

PCR-based cancer diagnosis requires detection of rare mutations in k-ras, p53 or other genes. The assumption has been that mutant and wild-type sequences amplify with near equal efficiency, so that they are eventually present in proportions representative of the starting material. Work factor IX suggests that this assumption is invalid for one case of near-sequence identity To test the generality of this phenomenon and its relevance to cancer diagnosis, primers distant from point mutations in p53 and k-ras were used to amplify, wild-type and mutant sequences from these genes. A substantial bias against PCR amplification of mutants was observed for two regions of the p53 gene and one region of k-ras. For kras and p53, bias was observed when the wild-type and mutant sequences were amplified separately or when mixed in equal proportions before PCR. Bias was present with proofreading and non-proofreading polymerases. Mutant and wild-type segments of the factor V cystic fibrosis transmembrane conductance regulator and prothrombin genes were amplified and did not exhibit PCR bias. Therefore, the assumption of equal PCR efficiency for point mutant and wild-type sequences is invalid in several systems. Quantitative or diagnostic PCR will require validation for each locus, and enrichment strategies may be needed to optimize detection of mutants.