Logistic Regression in Modelling Data for CVC - Related Infection

2000 Mathematics Subject Classification: 62J12, 62P10.

Application of the D-Fullness Technique for Breakdown Point Study of the Trimmed Likelihood Estimator to a Generalized Logistic Model

2000 Mathematics Subject Classification: 62J12, 62F35

Modeling Data for Complications in Diabetics Using Logistic Regression

2010 Mathematics Subject Classification: 62P10.

Corrigendum for "Weierstrass Points with first Non-Gap four on a Double Covering of a Hyperelliptic Curve"

In the proof of Lemma 3.1 in [1] we need to show that we may take the two points p and q with p ≠ q such that p+q+(b-2)g21(C′)∼2(q1+… +qb-1) where q1,…,qb-1 are points of C′, but in the paper [1] we did not show that p ≠ q. Moreover, we hadn't been able to prove this using the method of our paper [1]. So we must add some more assumption to Lemma 3.1 and rewrite the statements of our paper after Lemma 3.1. The following is the correct version of Lemma 3.1 in [1] with its proof.

Weierstrass Points with First Non-Gap Four on a Double Covering of a Hyperelliptic Curve II

2000 Mathematics Subject Classification: Primary 14H55; Secondary 14H30, 14J26.

Optimising the diagnostic performance of the Geriatric Depression Scale

The aim of this work is to empirically generate a shortened version of the Geriatric Depression Scale (GDS), with the intention of maximising the diagnostic performance in the detection of depression compared with previously GDS validated versions, while optimizing the size of the instrument. A total of 233 individuals (128 from a Day Hospital, 105 randomly selected from the community) aged 60 or over completed the GDS and other measures. The 30 GDS items were entered in the Day Hospital sample as independent variables in a stepwise logistic regression analysis predicting diagnosis of Major Depression. A final solution of 10 items was retained, which correctly classified 97.4% of cases. The diagnostic performance of these 10 GDS items was analysed in the random sample with a receiver operating characteristic (ROC) curve. Sensitivity (100%), specificity (97.2%), positive (81.8%) and negative (100%) predictive power, and the area under the curve (0.994) were comparable with values for GDS-30 and higher compared with GDS-15, GDS-10 and GDS-5. In addition, the new scale proposed had excellent fit when testing its unidimensionality with CFA for categorical outcomes (e.g., CFI=0.99). The 10-item version of the GDS proposed here, the GDS-R, seems to retain the diagnostic performance for detecting depression in older adults of the GDS-30 items, while increasing the sensitivity and predictive values relative to other shortened versions.

Principal component and second generation wavelet analysis of Treasury yield curve evolution

Prices of U.S. Treasury securities vary over time and across maturities. When the market in Treasurys is sufficiently complete and frictionless, these prices may be modeled by a function time and maturity. A cross-section of this function for time held fixed is called the yield curve; the aggregate of these sections is the evolution of the yield curve. This dissertation studies aspects of this evolution. ^ There are two complementary approaches to the study of yield curve evolution here. The first is principal components analysis; the second is wavelet analysis. In both approaches both the time and maturity variables are discretized. In principal components analysis the vectors of yield curve shifts are viewed as observations of a multivariate normal distribution. The resulting covariance matrix is diagonalized; the resulting eigenvalues and eigenvectors (the principal components) are used to draw inferences about the yield curve evolution. ^ In wavelet analysis, the vectors of shifts are resolved into hierarchies of localized fundamental shifts (wavelets) that leave specified global properties invariant (average change and duration change). The hierarchies relate to the degree of localization with movements restricted to a single maturity at the base and general movements at the apex. Second generation wavelet techniques allow better adaptation of the model to economic observables. Statistically, the wavelet approach is inherently nonparametric while the wavelets themselves are better adapted to describing a complete market. ^ Principal components analysis provides information on the dimension of the yield curve process. While there is no clear demarkation between operative factors and noise, the top six principal components pick up 99% of total interest rate variation 95% of the time. An economically justified basis of this process is hard to find; for example a simple linear model will not suffice for the first principal component and the shape of this component is nonstationary. ^ Wavelet analysis works more directly with yield curve observations than principal components analysis. In fact the complete process from bond data to multiresolution is presented, including the dedicated Perl programs and the details of the portfolio metrics and specially adapted wavelet construction. The result is more robust statistics which provide balance to the more fragile principal components analysis. ^

Sequential Logistic Regression: A Method to Reveal Subtlety in Self-Efficacy

This paper uses self-efficacy to predict the success of women in introductory physics. We show how sequential logistic regression demonstrates the predictive ability of self-efficacy, and reveals variations with type of physics course. Also discussed are the sources of self-efficacy that have the largest impact on predictive ability.

Avaliação de polimorfismos funcionais nos genes de reparo XRCC1, APEX1, XPD e XPF em carcinomas de células escamosas orais

Base excision repair (BER) and nucleotide excision repair (NER) pathways play critical role in maintaining genome integrity. Polymorphisms in BER and NER genes which modulate the DNA repair capacity may affect the susceptibility and prognosis of oral cancer. This study was conducted with genomic DNA from 92 patients with oral squamous cell carcinomas (OSCC) and 130 controls. The cases were followed up to explore the associations between BER and NER genes polymorphisms and the risk and prognosis of OSCC. Four single-nucleotide polymorphisms (SNPs) in XRCC1 (rs25487), APEX1 (rs1130409), XPD (rs13181) and XPF (rs1799797) genes were tested by polymerase chain reaction – quantitative real time method. The GraphPad Prism version 6.0.1 statistical software was applied for statistical analysis of association. Odds ratio (OR), hazard ratio (HR), and their 95 % confidence intervals (CIs) were calculated by logistic regression. Kaplan-Meier curve and Cox proportional hazard model were used for prognostic analysis. The presence of polymorphic variants in XRCC1, APEX1, XPD and XPF genes were not associated with an increased risk of OSCC. Gene-environment interactions with smoking were not significant for any polymorphism. The presence of polymorphic variants of the XPD gene in association with alcohol consumption conferred an increased risk of 1.86 (95% CI: 0.86 – 4.01, p=0.03) for OSCC. Only APEX1 was associated with decreased specific survival (HR 3.94, 95% CI: 1.31 – 11.88, p=0.01). These results suggest an interaction between polymorphic variants of the XPF gene and alcohol consumption. Additionally APEX1 may represent a prognostic marker for OSCC.

Luoghi geometrici e curve celebri

Scopo di questo elaborato è affrontare lo studio di luoghi geometrici piani partendo dagli esempi più semplici che gli studenti incontrano nel loro percorso scolastico, per poi passare a studiare alcune curve celebri che sono definite come luoghi geometrici. Le curve nell'elaborato vengono disegnate con l'ausilio di Geogebra, con il quale sono state preparate delle animazioni da mostrare agli studenti. Di alcuni luoghi si forniscono dapprima le equazioni parametriche e successivamente, attraverso il teorema di eliminazione e il software Singular, viene ricavata l'equazione cartesiana.

Bilingual Advantage in Executive Functioning: P-Curve Meta-Analysis

Other

Risk Prediction for Epithelial Ovarian Cancer in 11 United States-Based Case-Control Studies: Incorporation of Epidemiologic Risk Factors and 17 Confirmed Genetic Loci.

Previously developed models for predicting absolute risk of invasive epithelial ovarian cancer have included a limited number of risk factors and have had low discriminatory power (area under the receiver operating characteristic curve (AUC) < 0.60). Because of this, we developed and internally validated a relative risk prediction model that incorporates 17 established epidemiologic risk factors and 17 genome-wide significant single nucleotide polymorphisms (SNPs) using data from 11 case-control studies in the United States (5,793 cases; 9,512 controls) from the Ovarian Cancer Association Consortium (data accrued from 1992 to 2010). We developed a hierarchical logistic regression model for predicting case-control status that included imputation of missing data. We randomly divided the data into an 80% training sample and used the remaining 20% for model evaluation. The AUC for the full model was 0.664. A reduced model without SNPs performed similarly (AUC = 0.649). Both models performed better than a baseline model that included age and study site only (AUC = 0.563). The best predictive power was obtained in the full model among women younger than 50 years of age (AUC = 0.714); however, the addition of SNPs increased the AUC the most for women older than 50 years of age (AUC = 0.638 vs. 0.616). Adapting this improved model to estimate absolute risk and evaluating it in prospective data sets is warranted.

Description of an 8 MW reference wind turbine

An 8 MW wind turbine is described in terms of mass distribution, dimensions, power curve, thrust curve, maximum design load and tower configuration. This turbine has been described as part of the EU FP7 project LEANWIND in order to facilitate research into logistics and naval architecture efficiencies for future offshore wind installations. The design of this 8 MW reference wind turbine has been checked and validated by the design consultancy DNV-GL. This turbine description is intended to bridge the gap between the NREL 5 MW and DTU 10 MW reference turbines and thus contribute to the standardisation of research and development activities in the offshore wind energy industry.

Effet préventif de la milrinone inhalée chez les patients avec hypertension pulmonaire subissant une chirurgie cardiaque sous circulation extracorporelle : une approche pharmacométrique

La circulation extracorporelle (CEC) est une technique utilisée en chirurgie cardiaque effectuée des milliers de fois chaque jour à travers le monde. L’instabilité hémodynamique associée au sevrage de la CEC difficile constitue la principale cause de mortalité en chirurgie cardiaque et l’hypertension pulmonaire (HP) a été identifiée comme un des facteurs de risque les plus importants. Récemment, une hypothèse a été émise suggérant que l'administration prophylactique (avant la CEC) de la milrinone par inhalation puisse avoir un effet préventif et faciliter le sevrage de la CEC chez les patients atteints d’HP. Toutefois, cette indication et voie d'administration pour la milrinone n'ont pas encore été approuvées par les organismes réglementaires. Jusqu'à présent, la recherche clinique sur la milrinone inhalée s’est principalement concentrée sur l’efficacité hémodynamique et l'innocuité chez les patients cardiaques, bien qu’aucun biomarqueur n’ait encore été établi. La dose la plus appropriée pour l’administration par nébulisation n'a pas été déterminée, de même que la caractérisation des profils pharmacocinétiques (PK) et pharmacodynamiques (PD) suite à l'inhalation. L'objectif de notre recherche consistait à caractériser la relation exposition-réponse de la milrinone inhalée administrée chez les patients subissant une chirurgie cardiaque sous CEC. Une méthode analytique par chromatographie liquide à haute performance couplée à un détecteur ultraviolet (HPLC-UV) a été optimisée et validée pour le dosage de la milrinone plasmatique suite à l’inhalation et s’est avérée sensible et précise. La limite de quantification (LLOQ) était de 1.25 ng/ml avec des valeurs de précision intra- et inter-dosage moyennes (CV%) <8%. Des patients souffrant d’HP pour lesquels une chirurgie cardiaque sous CEC était prévue ont d’abord été recrutés pour une étude pilote (n=12) et, par la suite, pour une étude à plus grande échelle (n=28) où la milrinone (5 mg) était administrée par inhalation pré-CEC. Dans l'étude pilote, nous avons comparé l'exposition systémique de la milrinone peu après son administration avec un nébuliseur pneumatique ou un nébuliseur à tamis vibrant. L’efficacité des nébuliseurs en termes de dose émise et dose inhalée a également été déterminée in vitro. Dans l'étude à plus grande échelle conduite en utilisant exclusivement le nébuliseur à tamis vibrant, la dose inhalée in vivo a été estimée et le profil pharmacocinétique de la milrinone inhalée a été pleinement caractérisé aux niveaux plasmatique et urinaire. Le ratio de la pression artérielle moyenne sur la pression artérielle pulmonaire moyenne (PAm/PAPm) a été choisi comme biomarqueur PD. La relation exposition-réponse de la milrinone a été caractérisée pendant la période d'inhalation en étudiant la relation entre l'aire sous la courbe de l’effet (ASCE) et l’aire sous la courbe des concentrations plasmatiques (ASC) de chacun des patients. Enfin, le ratio PAm/PAPm a été exploré comme un prédicteur potentiel de sortie de CEC difficile dans un modèle de régression logistique. Les expériences in vitro ont démontré que les doses émises étaient similaires pour les nébuliseurs pneumatique (64%) et à tamis vibrant (68%). Cependant, la dose inhalée était 2-3 fois supérieure (46% vs 17%) avec le nébuliseur à tamis vibrant, et ce, en accord avec les concentrations plasmatiques. Chez les patients, en raison des variations au niveau des facteurs liés au circuit et au ventilateur causant une plus grande dose expirée, la dose inhalée a été estimée inférieure (30%) et cela a été confirmé après récupération de la dose de milrinone dans l'urine 24 h (26%). Les concentrations plasmatiques maximales (Cmax: 41-189 ng/ml) et l'ampleur de la réponse maximale ΔRmax-R0 (0-65%) ont été observées à la fin de l'inhalation (10-30 min). Les données obtenues suite aux analyses PK sont en accord avec les données publiées pour la milrinone intraveineuse. Après la période d'inhalation, les ASCE individuelles étaient directement reliées aux ASC (P=0.045). Enfin, notre biomarqueur PD ainsi que la durée de CEC ont été identifiés comme des prédicteurs significatifs de la sortie de CEC difficile. La comparaison des ASC et ASCE correspondantes a fourni des données préliminaires supportant une preuve de concept pour l'utilisation du ratio PAm/PAPm comme biomarqueur PD prometteur et justifie de futures études PK/PD. Nous avons pu démontrer que la variation du ratio PAm/PAPm en réponse à la milrinone inhalée contribue à la prévention de la sortie de CEC difficile.