Memoria de trabajo y planificación como predictores de las competencias matemáticas tempranas

Introducción: La relación entre funciones ejecutivas y habilidades matemáticas ha sido ampliamente estudiada. Sin embargo, no existe consenso respecto de la contribución específica de la memoria de trabajo y la planificación en el desarrollo de competencias matemáticas tempranas. El objetivo de este estudio fue determinar la capacidad predictiva de estos dos dominios ejecutivos sobre las competencias matemáticas de preescolares. Método: Se implementó un diseño no experimental ex post facto, con una muestra de 104 niños/as chilenos/as. La evaluación de sus funciones ejecutivas se realizó con la tarea "inversión de números" de la Batería IV Woodcock-Muñoz para evaluar la memoria de trabajo verbal, la subprueba "Torpo, el topo torpe" del Test de Evaluación Neuropsicológica Infantil (TENI) para evaluar la memoria de trabajo visoespacial y el Test de Laberintos de Porteus para evaluar la planificación. Con el fin de evaluar las habilidades matemáticas se utilizó el Test de Evaluación Matemática Temprana Utrecht (TEMT-U), versión chilena. Se realizaron análisis descriptivos, correlaciones y modelos de regresión múltiple. Resultados: La memoria de trabajo verbal seguida por la memoria de trabajo visoespacial y la planificación fueron los mejores predictores de las competencias matemáticas de los/as niños/as. Conclusiones: Estos resultados sugieren que estas funciones ejecutivas desempeñan un papel clave en el aprendizaje de las matemáticas y aportan información específica a las/os educadoras/es para que puedan planificar sus estrategias de enseñanza en función de las demandas cognitivas que requiere cada habilidad matemática, lo que puede ser una vía potencial para promover mejores logros de aprendizaje en esta importante disciplina.

Introduction: The relationship between executive functions and mathematical skills has been extensively studied. However, there is no consensus regarding the specific contribution of working memory and planning in the development of early mathematical skills. The aim of this study was to determine the predictive capacity of these two executive domains on preschoolers' mathematical skills. Method: A non-experimental ex post facto design was implemented with a sample of 104 Chilean children. The evaluation of their executive functions was performed with the "number inversion" task of the Woodcock-Muñoz IV Battery to assess verbal working memory, the "Clumsy Mole the Clumsy Mole" subtest of the TENI Child Neuropsychological Evaluation Test to assess visuospatial working memory, and the Porteus Maze Test to assess planning. To assess mathematical skills, the Test de Evaluación Matemática Temprana Utretch TEMT-U, Chilean version, was used. Descriptive analyses, correlations and multiple regression models were performed. Results: Verbal working memory followed by visuospatial working memory and planning were the best predictors of children's mathematical skills. Conclusions: These results suggest that these executive functions play a key role in mathematics learning and provide specific information to educators so that they can plan their teaching strategies according to the cognitive demands required by each mathematical skill, which may be a potential way to promote better learning achievements in this important discipline.

Modelo estadístico para estimar el impacto histórico de la influenza sobre la mortalidad en Cuba / Statistical model to estimate the historical impact of influenza on mortality in Cuba

Introducción: La influenza tiene elevado impacto en la mortalidad humana y en Cuba la categoría influenza y neumonía ocupa el cuarto lugar entre sus causales generales. En los países templados, con marcada estacionalidad, esto se capta con modelos estadísticos, tarea que se dificulta en el trópico y pendiente en Cuba por la ausencia de igual definición estacional. Objetivo: Estimar el impacto histórico de la influenza tipo A y B y los subtipos A(H3N2) y A(H1N1) sobre la mortalidad mediante el ajuste de un modelo de regresión a las condiciones estacionales específicas de Cuba. Métodos: Se ejecutó un estudio longitudinal y retrospectivo. En un primer paso se ajustaron dos modelos de Poisson con la mortalidad influenza y neumonía total y las personas ≥ 65 años de edad como variables respuestas en los cinco meses de mayor positividad en influenza, desde la temporada 1987-1988 hasta la 2004-2005 y los positivos en tipo A y en tipo B como explicatorias. En otro par de modelos se estimó el impacto del A(H3N2) y el A(H1N1), considerando como respuesta los fallecidos atribuidos previamente al tipo A. Resultados: Se atribuyeron a la influenza 7803 fallecidos entre todas las edades y 6152 entre las personas ≥ 65 años de edad, con un 56,3 por ciento asociados al A(H3N2), el 17,6 por ciento al A(H1N1) y el 26,1 por ciento al tipo B. Conclusiones. Se logró estimar el impacto de la influenza sobre la mortalidad mediante el ajuste para Cuba de un modelo estadístico que permitió demostrar la asociación de la circulación de estos virus con la mortalidad en el país, lo que ratifica la necesidad de reforzar la vigilancia, el control y la vacunación contra esta infección viral. Se demuestra la posibilidad de ajustar estos modelos de regresión a otros virus respiratorios y a la actual pandemia por la COVID-19, en las condiciones estacionales de Cuba(AU)

Introduction: Influenza has a high impact on human mortality and in Cuba influenza and pneumonia rank fourth among its general causes. In temperate climate countries, with marked seasonality, this is captured by statistical models, a task that is difficult in the tropics and pending in Cuba due to the absence of the same seasonal definition. Objective: Estimate the historical impact of influenza type A and B and subtypes A(H3N2) and A(H1N1) on mortality, by adjusting a regression model to the specific seasonal conditions of Cuba. Methods: A longitudinal and retrospective study was performed. In a first step, two Poisson models were adjusted with influenza and total pneumonia mortality and people ≥ 65 years old as response variables in the five months with the highest positivity to influenza in the period 1987-1988 to 2004-2005, and the positive ones to type A and type B as explanatory variables. In another pair of models was estimated the impact of A(H3N2) and A(H1N1), considering as a response the deaths previously attributed to type A. Results: 7 803 deaths among all ages and 6 152 among 65-year-olds were attributed to influenza, with 56.3 percent associated to A(H3N2), 17.6 percent to A(H1N1) and 26.1 percent to type B. Conclusions: It was possible to estimate the impact of influenza on mortality by adjusting for Cuba a statistical model that demonstrated the association of the circulation of these viruses with the mortality in the country, which confirms the need to strengthen surveillance, control and vaccination against this viral infection. The possibility of adjusting in the seasonal conditions of Cuba these regression models to other respiratory viruses and the current pandemic by COVID-19 is demonstrated(AU)

Logistic regression analyses for preoperative assessment of liver functional reserve based on virtual touch tissues quantification and fibrosis-4 / 中华肝胆外科杂志

Objective:To investigate the effect of logistic regression model based on virtual touch tissues quantification (VTQ) and fibrosis index based on four factors (FIB-4) in assessing impaired liver reserve function (LFR) in hepatic surgery patients before surgical resection.Methods:From January 2016 to October 2018, 173 patients including 135 males and 38 females with the mean age of 58.6 years old, scheduled for potential hepatectomy in Nanjing Drum Tower Hospital, the Affiliated Hospital of Nanjing University Medical School, were enrolled in our retrospective study. According to indocyanine green retention test at 15 minutes (ICG R15), the patients were divided into two groups, LFR-impaired group ( n=11, ICG R15≥20%) and control group ( n=162, ICG R15 < 20%). VTQ, FIB-4, platelet count and other parameters were compared between two groups. The multivariate logistic regression model was used to establish a risk model to access the impaired LFR. Receiver operating characteristic (ROC) curve was used to analyze the efficacy of each parameter in LFR-impaired. Results:The platelet count in LFR-impaired group was lower than that in control group, VTQ and FIB-4 were higher than that in control group (all P<0.05). Logistic regression showed that VTQ ( OR=4.382, 95% CI: 1.380-13.918)) and FIB-4 ( OR=2.112, 95% CI: 1.342-3.325) were risk factors for LFR-impaired. The final prediction model of LFR-impaired group was Logit (P)=-6.185+ 0.748×FIB-4+ 1.477×VTQ. The cut-off point (sensitivity, specificity, accuracy) of logistic model, FIB-4 and VTQ were 0.098 (72.8%, 90.1%, 89.0%), 0.990 (90.9%, 79.0%, 79.8%) and 1.8 m/s (81.8%, 77.8%, 78.0%), respectively. The specificity, accuracy of logistic model was higher than FIB-4 or VTQ. Conclusions:Logistic regression model based on VTQ and FIB-4 may improve the specificity and accuracy in the diagnosis of significant LFR impairment. VTQ can further assist clinicians in preoperative evaluation of LFR.

Importancia de los modelos de regresión no lineales en la interpretación de datos de la COVID-19 en Colombia / Importance of nonlinear regression models in the interpretation of data from COVID-19 in Colombia

Introducción: Debido a los nocivos efectos económicos y sociales propiciados por el confinamiento de las personas, las entidades gubernamentales de Colombia, planean una cuarentena inteligente, basados en la interpretación del comportamiento de la curva de los datos, de la cual afirman ha presentado un reducción durante los últimos días. Objetivo: Destacar la importancia del análisis de los métodos de correlación no lineal y todos sus procedimientos de inferencia estadística para el diseño de un modelo matemático que permita la predicción de los datos basados en las edades de los casos positivos de COVID-19 en Colombia. Material y Métodos: Los resultados diarios se basan en el sitio web oficial del Instituto Nacional de Salud de Colombia. Todos los datos se analizan a través del software libre R-Kward® (Biblioteca R). El propósito de los análisis es evidenciar el valor de la matriz de correlación, la prueba de hipótesis, r2 y el modelo de correlación ideal, a través del cual se realiza una predicción. Resultados: Con un R2 de 0,9969 muy cercano a 1, y una prueba de hipótesis que garantiza la veracidad de la hipótesis alternativa, el modelo matemático de regresión que más se aproxima al comportamiento real de los datos de crecimiento de la COVID-19 es cuadrático. Conclusiones: El modelo cuadrático es positivo y creciente, mientras el número de contagios siga creciendo, por lo tanto, este momento no es ideal de hablar de un aplanamiento de la curva. Si el crecimiento es constante, el modelo podría tener una tendencia exponencial(AU)

Introduction: Due to the harmful economic and social effects caused by the confinement of people, the Colombian government entities have planned an intelligent quarantine based on the interpretation of the behavior in the curve data, from which they affirm that it has shown a reduction during the last days. Objective: To highlight the importance of the analysis of non-linear correlation models and all the statistical inference procedures for the design of a mathematical model that allows the prediction of data based on the age of positive cases of COVID-19 in Colombia. Material and Methods: The daily results are based on the information obtained from the official website of the Colombian National Institute of Health. The total data are analyzed through the R-Kward free software (R Library). The aim of the analysis is to show the value of the correlation matrix, hypothesis test, r2 and the ideal correlation model, with which prediction is made. Results: With an R2 value of 0.9969 very close to 1 and a hypothesis test that guarantees the veracity of the alternative hypothesis, the ideal mathematical model that aligns the growth data of COVID-19 is quadratic. Conclusions: The quadratic model is positive and increasing as long as the number of infections continue to grow; therefore, it is not an ideal moment to speak of a flattening of the curve. If the growth is constant, the model could have an exponential trend(AU)

Analysis of the adaptability of black bean cultivars by means of quantile regression / Análise da adaptabilidade de cultivares de feijão preto por meio de regressão quantílica

ABSTRACT: The aim of this study was to use quantile regression (QR) to characterize the effect of the adaptability parameter throughout the distribution of the productivity variable on black bean cultivars launched by different national research institutes (research centers) over the last 50 years. For this purpose, 40 cultivars developed by Brazilian genetic improvement programs between 1959 and 2013 were used. Initially, QR models were adjusted considering three quantiles (τ = 0.2, 0.5 and 0.8). Subsequently, with the confidence intervals, quantile models τ = 0.2 and 0.8 (QR0.2 and QR0.8) showed differences regarding the parameter of adaptability and average productivity. Finally, by grouping the cultivars into one of the two groups defined from QR0.2 and QR0.8, it was reported that the younger cultivars were associated to the quantile τ = 0.8, i.e., those with higher yields and more responsive conditions indicating that genetic improvement over the last 50 years resulted in an increase in both the productivity and the adaptability of cultivars.

RESUMO: Neste estudo objetivou-se utilizar a regressão quantílica (RQ) para caracterizar o efeito do parâmetro de adaptabilidade ao longo de toda a distribuição da variável produtividade em cultivares de feijão preto lançadas por diferentes instituições nacionais de pesquisa nos últimos 50 anos. Para tanto utilizou-se 40 cultivares desenvolvidas pelos programas brasileiros de melhoramento genético entre os anos de 1959 a 2013. Inicialmente foram ajustados modelos de RQ considerando três quantis (τ=0,2, 0,5, 0,8). Posteriormente, com os intervalos de confiança verificou-se que os modelos quantílicos τ=0,2 e 0,8 (RQ0,2 e RQ0,8) apresentaram diferenças quanto ao parâmetro de adaptabilidade e produtividade média. Finalmente, por meio do agrupamento das cultivares em um dos dois grupos definidos a partir de RQ0,2 e RQ0,8, constatou-se que as cultivares mais novas foram associadas ao quantil τ = 0,8, ou seja, aquelas com maiores produtividades e mais responsivas as condições ambientais indicando que o melhoramento ao longo dos últimos 50 anos possibilitou o incremento tanto na produtividade quanto na adaptabilidade das cultivares.

Bibliometrics and visualization analysis of land use regression models in ambient air pollution research / 中华流行病学杂志

Objective To quantitatively analyze the current status and development trends regarding the land use regression (LUR) models on ambient air pollution studies.Methods Relevant literature from the PubMed database before June 30,2017 was analyzed,using the Bibliographic Items Co-occurrence Matrix Builder (BICOMB 2.0).Keywords co-occurrence networks,cluster mapping and timeline mapping were generated,using the CiteSpace 5.1.R5 software.Relevant literature identified in three Chinese databases was also reviewed.Results Four hundred sixty four relevant papers were retrieved from the PubMed database.The number of papers published showed an annual increase,in line with the growing trend of the index.Most papers were published in the journal of Environmental Health Perspectives.Results from the Co-word cluster analysis identified five clusters:cluster #0 consisted of birth cohort studies related to the health effects of prenatal exposure to air pollution;cluster #1 referred to land use regression modeling and exposure assessment;cluster #2 was related to the epidemiology on traffic exposure;cluster #3 dealt with the exposure to ultrafine particles and related health effects;cluster #4 described the exposure to black carbon and related health effects.Data from Timeline mapping indicated that cluster #0 and #1 were the main research areas while cluster #3 and #4 were the up-coming hot areas of research.Ninety four relevant papers were retrieved from the Chinese databases with most of them related to studies on modeling.Conclusion In order to better assess the health-related risks of ambient air pollution,and to best inform preventative public health intervention policies,application of LUR models to environmental epidemiology studies in Chinashould be encouraged.

Bibliometrics and visualization analysis of land use regression models in ambient air pollution research / 中华流行病学杂志

Objective To quantitatively analyze the current status and development trends regarding the land use regression (LUR) models on ambient air pollution studies.Methods Relevant literature from the PubMed database before June 30,2017 was analyzed,using the Bibliographic Items Co-occurrence Matrix Builder (BICOMB 2.0).Keywords co-occurrence networks,cluster mapping and timeline mapping were generated,using the CiteSpace 5.1.R5 software.Relevant literature identified in three Chinese databases was also reviewed.Results Four hundred sixty four relevant papers were retrieved from the PubMed database.The number of papers published showed an annual increase,in line with the growing trend of the index.Most papers were published in the journal of Environmental Health Perspectives.Results from the Co-word cluster analysis identified five clusters:cluster #0 consisted of birth cohort studies related to the health effects of prenatal exposure to air pollution;cluster #1 referred to land use regression modeling and exposure assessment;cluster #2 was related to the epidemiology on traffic exposure;cluster #3 dealt with the exposure to ultrafine particles and related health effects;cluster #4 described the exposure to black carbon and related health effects.Data from Timeline mapping indicated that cluster #0 and #1 were the main research areas while cluster #3 and #4 were the up-coming hot areas of research.Ninety four relevant papers were retrieved from the Chinese databases with most of them related to studies on modeling.Conclusion In order to better assess the health-related risks of ambient air pollution,and to best inform preventative public health intervention policies,application of LUR models to environmental epidemiology studies in Chinashould be encouraged.

Modeling of the entrepreneurial survival equation of medellín's industrial sector

Introduction. The intention of this work is to invetigate the probability of survival of the new companies created in the Medellín Industrial sector between the years 2000 and 2010. Also to highlight some determinants of the factors of success in the consolidation and acceptance of companies in the Market, in the time lapses immediately following their gestation. Objective. Calculate the cumulative survival rate of companies belonging to the Industrial sector of the city of Medellín created in the period between 2000 and 2010. Considering the size, legal nature and industrial sector to which it is circumscribed. Materials and methods. To account for the objective was used the survival function in a certain period shows the percentage of companies alive after a certain number of periods after their appearance. The risk function shows the percentage of companies closing t periods of time after its birth. Results. The risk of disappearance of a company decreases as the antiquity increases, additionally, is smaller in companies that are born with a larger or big size. The creation of companies is greater among the smaller ones, but present higher mortality rates in the first years of life. The survival of new companies is positively related to their size at birth.

Introducción. El propósito del presente trabajo es el de investigar la probabilidad de supervivencia de las nuevas empresas creadas en el sector industrial de Medellín entre los años 2000 y 2010. Así mismo evidenciar algunos determinantes de los factores de éxito en la consolidación y aceptación de las empresas en el mercado, en los periodos de tiempo inmediatamente posteriores a su gestación. Objetivo. Calcular la tasa acumulada de supervivencia de las empresas pertenecientes al sector Industrial de la ciudad de Medellín creadas en el período comprendido entre los años 2000 y 2010. Esto teniendo en cuenta el tamaño, naturaleza jurídica y sector industrial al que se circunscriben. Materiales y métodos. Para dar cuenta del objetivo se utilizó la función de supervivencia en un cierto período muestra el porcentaje de empresas vivas después de que transcurran un número determinado de períodos tras su aparición. La función de riesgo muestra el porcentaje de empresas que cierra t períodos después de su nacimiento. A su vez, la función de supervivencia recoge el porcentaje de empresas vivas t períodos después del nacimiento. Resultados. El riesgo de desaparición de una empresa disminuye conforme aumenta la antigüedad, adicionalmente, es menor en las empresas que nacen con un mayor tamaño. La creación de empresas es mayor entre las de menor tamaño, pero presentan mayores tasas de mortalidad en los primeros años de vida. La supervivencia de las nuevas empresas se encuentra positivamente relacionada con su tamaño al nacer.

Introdução. O propósito do presente trabalho é o de investigar a probabilidade de supervivência das novas empresas criadas no setor industrial de Medellín entre os anos 2000 e 2010. Assim mesmo evidenciar alguns determinantes dos fatores de sucesso na consolidação e aceitação das empresas no mercado, nos períodos de tempo imediatamente posteriores à sua gestação. Objetivo. Calcular a taxa acumulada de supervivência das empresas pertencentes ao sector Industrial da cidade de Medellín criadas no período entre os anos 2000 e 2010. Isto tendo em conta o tamanho, natureza jurídica e setor industrial ao que se circunscrevem. Materiais e métodos. Para dar conta do objetivo se utilizou a função de supervivência num certo período de amostra a porcentagem de empresas vivas depois de que transcorram um número determinado de períodos após sua aparição. A função de risco mostra a porcentagem de empresas que fecha t períodos depois do seu nascimento. Por sua vez, a função de supervivência recolhe a porcentagem de empresas vivas t períodos depois do nascimento. Resultados. O risco de desaparição de uma empresa diminui conforme aumenta a antiguidade, adicionalmente, é menor nas empresas que nascem com um maior tamanho. A criação de empresas é maior entre as de menor tamanho, mas apresentam maiores taxas de mortalidade nos primeiros anos de vida. A supervivência das novas empresas se encontra positivamente relacionada com seu tamanho ao nascer.

Fatores de risco associados à intervenção com injeção intravítrea de anti-VEGF em pacientes com edema macular diabético / Risk factors related to the intervention with intravitreal anti-VEGF injection in patients with diabetic macular edema

Resumo Objetivo: Propor um modelo de regressão logística para auxiliar na decisão de realização da injeção intravítrea (IIV) de anti-VEGF, a partir da quantificação e hierarquização dos fatores de risco que compõem o perfil dos indivíduos diabéticos. Métodos: Trata-se de estudo transversal, observacional e inferencial, realizado em três instituições da Paraíba, de julho de 2015 a setembro de 2016. O modelo de regressão logística foi utilizado para obtenção do modelo preditivo e os dados foram analisados no software R®. Resultados: Foram avaliados 80 pacientes com diabetes tipo 1 ou 2, maiores de 18 anos, dos quais 57,5% não tiveram indicação de IIV e 42,5% receberam indicação deste tratamento. No grupo com edema macular diabético (EMD), a média de idade foi de 60,65 anos, sendo 52,94% do sexo feminino. Ainda nesse grupo, a maioria apresentou retinopatia diabética não-proliferativa severa ou retinopatia proliferativa (79,41%). Foram identificados como fatores de risco para EMD: o indivíduo ser aposentado (OR=5,22; p-valor 0,05), ter histórico pessoal de retinopatia diabética (OR=20,27; p-valor 0,006) e de tratamento prévio com anti-VEGF (OR=23,23; p-valor 0,002). Conclusão: Os resultados da pesquisa evidenciaram que um indivíduo diabético com baixa visual e apresentando esses três fatores deve ser encaminhado o quanto antes ao especialista, pois possui, com 91,17% de acerto, risco de apresentar EMD com necessidade de IIV de anti-VEGF. Essa ferramenta pode servir como coadjuvante na tomada de decisão, sobretudo do não-retinólogo, a fim de encaminhar para diagnóstico e tratamento precoces os indivíduos com EMD, o que pode ser decisivo na prevenção da perda visual irreversível nesses pacientes.

Abstract Purpose: To propose a predictive model to aid in the decision to perform the intravitreal anti-VEGF injection, based on the risk factors quantification and hierarchy presented by diabetic patients. Methods: It is a cross-sectional, observational and inferential study carried out in three institutions in Paraíba from July 2015 to September 2016. The logistic regression model was used to obtain the predictive model and data were analyzed in R(r) software. Results: Eighty patients with type 1 or 2 diabetes, over 18 years of age, were included, 57.5% of whom had no indication of IIV and 42.5% received an indication of this treatment. In the group with diabetic macular edema (DME), the mean age was 60.65 years, of which 52.94% were female. In this group, the majority presented severe non-proliferative diabetic retinopathy or proliferative retinopathy (79.41%). The main risk factors for DME were: be retired (OR = 5.22, p-value0.05), had a personal history of diabetic retinopathy (OR = 20.27, p-value 0.006), and previous treatment with anti-VEGF (OR = 23.23, p-value 0.002). Conclusion: The results of the research showed that a diabetic patient with low visual acuity and presenting these three factors should be referred as soon as possible to the specialist, since he presents a risk of presenting DME with need for anti-VEGF IIV, with 91.17% of accuracy. This tool can serve as an adjunct to decision making, especially the nonretinologist, in order to refer individuals with EMD to early diagnosis and treatment, which may be crucial in preventing irreversible visual loss in these patients.

Logistic regression analysis of ultrasonography in diagnosis of malignant thyroid nodules / 中国介入影像与治疗学

Objective To investigate the value of conventional ultrasound and CEUS in diagnosis of thyroid nodules with Logistic regression models.Methods A total of 218 cases of thyroid nodules (74 cases of malignant,144 cases of benign nodules) confirmed by pathology were enrolled.The boundary,morphology,anteroposterior and transverse diameter ratio,microcalcification,internal echogenicity,blood distribution and enhanced pattern of nodules were observed and analyzed with univariate analysis.The Logistic regression model was established with parameters which were significantly different of those features,and the receiver operating characteristic curves (ROC) were constructed.Results Hypoechoic,irregular morphology,blurred boundary,anteroposterior and transverse diameter ratio≥ 1,microcalcifications,blood distribution (Ⅰ,Ⅱ),heterogeneous enhanced pattern and low enhanced were significantly prognostic factors (all P＜0.01).Irregular morphology,microcalcifications,heterogeneous enhanced and low enhanced were independent prognostic factors (all P＜0.05).The accuracy of Logistic regression model was 82.57％,and the area under ROC curve was 0.906.Conclusion The Logistic regression model of boundary,morphology,anteroposterior and transverse diameter ratio,microcalcifica tions,internal echogenicity,blood distribution and enhanced pattern can help to diagnose malignant thyroid nodules.

Evaluation of transition zone prostate cancer by Logistic regression of prostate imaging reporting and data system version 2 combined with prostate specific antigen / 中国医学影像技术

Objective To establish the Logistic regression model by reporting and data system version 2 (PI-RADS v2)and prostate specific antigen (PSA),and to evaluate the diagnostic efficiency in transition zone prostate cancer (PCa).Methods MRI and PSA data of 33 patients with PCa and 54 patients with non-PCa confirmed by pathology were analyzed retrospectively.The PI-RADS v2 was used to evaluate the risk of 2 groups (from low to high as 1 to 5 points).Total PSA (t-PSA),free to total PSA ratio (f-PSA/t-PSA),PSA density (PSAD) and PI-RADS v2 scores were compared between 2 groups.The Logistic regression models were established with parameters which were significantly different between 2 groups.The Logistic regression was divide into three protocols:PI-RADS v2-+ t-PSA (A),PI-RADS v2 + f-PSA/t-PSA (B),PI-RADS v2+PSAD (C).The ROC curves were constructed by the new parameters Logit (P) and PI-RADS v2 scores for assessing the diagnostic efficiency.Results The t-PSA,f-PSA/t-PSA,PSAD and PI-RADS v2 scores had significant differences between the 2 groups (all P＜0.01).Predictive multivariate model of A,B,C was established as Logit (P)=-8.682+1.507 PI-RADS v2+0.234 t-PSA (x2=65.993,P＜0.01),Logit(P)=-5.425+1.906 PI-RADS v2 13.921 f-PSA/t-PSA (x2 =65.993,P＜0.01),Logit(P)=-7.534+1.045 PI-RADS v2+13.318 PSAD (x2 =74.036,P＜0.01),their area underthe curve (0.945,0.919,0.960) were all higher than that of PI-RADS v2 score (0.861,all P ＜0.01).The protocol C had the best diagnostic efficiency,and the sensitivity and specificity were 87.88 ％ and 92.59 ％.The sensitivity and specificity of PI-RADS v2 score were 87.88％ and 77.78％.Conclusion The diagnostic efficiency of the Logistic regression model which includes the PI-RADS v2 score and PSA are superior to the PI-RADS v2 score alone for transition zone PCa,which can provide a reliable basis for patients whether need biopsy or not.

Applying temporally-adjusted land use regression models to estimate ambient air pollution exposure during pregnancy / 中华预防医学杂志

The impact of maternal air pollution exposure on offspring health has received much attention. Precise and feasible exposure estimation is particularly important for clarifying exposure-response relationships and reducing heterogeneity among studies. Temporally-adjusted land use regression (LUR) models are exposure assessment methods developed in recent years that have the advantage of having high spatial-temporal resolution. Studies on the health effects of outdoor air pollution exposure during pregnancy have been increasingly carried out using this model. In China, research applying LUR models was done mostly at the model construction stage, and findings from related epidemiological studies were rarely reported. In this paper, the sources of heterogeneity and research progress of meta-analysis research on the associations between air pollution and adverse pregnancy outcomes were analyzed. The methods of the characteristics of temporally-adjusted LUR models were introduced. The current epidemiological studies on adverse pregnancy outcomes that applied this model were systematically summarized. Recommendations for the development and application of LUR models in China are presented. This will encourage the implementation of more valid exposure predictions during pregnancy in large-scale epidemiological studies on the health effects of air pollution in China.

Risk Prediction Using Genome-Wide Association Studies on Type 2 Diabetes

The success of genome-wide association studies (GWASs) has enabled us to improve risk assessment and provide novel genetic variants for diagnosis, prevention, and treatment. However, most variants discovered by GWASs have been reported to have very small effect sizes on complex human diseases, which has been a big hurdle in building risk prediction models. Recently, many statistical approaches based on penalized regression have been developed to solve the “large p and small n” problem. In this report, we evaluated the performance of several statistical methods for predicting a binary trait: stepwise logistic regression (SLR), least absolute shrinkage and selection operator (LASSO), and Elastic-Net (EN). We first built a prediction model by combining variable selection and prediction methods for type 2 diabetes using Affymetrix Genome-Wide Human SNP Array 5.0 from the Korean Association Resource project. We assessed the risk prediction performance using area under the receiver operating characteristic curve (AUC) for the internal and external validation datasets. In the internal validation, SLR-LASSO and SLR-EN tended to yield more accurate predictions than other combinations. During the external validation, the SLR-SLR and SLR-EN combinations achieved the highest AUC of 0.726. We propose these combinations as a potentially powerful risk prediction model for type 2 diabetes.

Prediction of Quantitative Traits Using Common Genetic Variants: Application to Body Mass Index

With the success of the genome-wide association studies (GWASs), many candidate loci for complex human diseases have been reported in the GWAS catalog. Recently, many disease prediction models based on penalized regression or statistical learning methods were proposed using candidate causal variants from significant single-nucleotide polymorphisms of GWASs. However, there have been only a few systematic studies comparing existing methods. In this study, we first constructed risk prediction models, such as stepwise linear regression (SLR), least absolute shrinkage and selection operator (LASSO), and Elastic-Net (EN), using a GWAS chip and GWAS catalog. We then compared the prediction accuracy by calculating the mean square error (MSE) value on data from the Korea Association Resource (KARE) with body mass index. Our results show that SLR provides a smaller MSE value than the other methods, while the numbers of selected variables in each model were similar.

Curvas de crecimiento del perímetro cefálico en niños de 0 a 3 años: una nueva aproximación / Head circumference growth curves in children 0 to 3 years of age: a new approach

Introducción: el perímetro cefálico es un indicador de salud y de crecimiento global craneal en la primera infancia, por lo que debe monitorearse. Usualmente, los patrones de referencia OMS utilizan el modelo Box Cox Power exponential y el método LMS para modelar el comportamiento del crecimiento del perímetro cefálico. Estos métodos tienen la debilidad de comparar cada individuo frente a una mediana poblacional, lo cual no permite caracterizar el crecimiento individual; en tanto que al usar los modelos longitudinales de efectos mixtos se puede evaluar el patrón individual de crecimiento y controlar la variabilidad entre sujetos. El objetivo fue hacer uso de los modelos longitudinales de efectos mixtos, caracterizar los patrones de crecimiento a partir del perímetro cefálico en niños de 0 a 3 años. Métodos: siendo éste un estudio longitudinal prospectivo, los criterios de elegibilidad para los niños obedecieron a factores de inclusión y exclusión (OMS); 265 niños colombianos (116 niñas, 149 niños), residentes en Bogotá, fueron distribuidos en 3 grupos G1: (0-12], G2: (12–24], G3: (24–36] meses. Se midieron cada 3 meses durante 1 año. Dos examinadores tuvieron entrenamiento y continua estandarización, monitoreo de adherencia a procedimientos de recolección y calidad de datos. Se calculó el error aleatorio y sistemático. Las curvas de crecimiento fueron construidas usando los modelos longitudinales mixtos. Para la estimación del modelo se utilizó el método de estimación de máxima verosimilitud restringida (REML), software estadístico R versión libre 2.15. Para el ajuste de los modelos el paquete lme4. Resultados: se ajustaron 6 modelos, observándose mayor pendiente de crecimiento de 0-12 meses. Conclusiones: la metodología utilizada permitió entender el comportamiento del perímetro cefálico por grupo, edad y sexo, y analizar datos con estructuras de desbalance.

Introduction: head circumference is an indicator of health and global cranial growth in early childhood, so it must be monitored. Usually, the WHO reference patterns use the Box Cox Power exponential model and the LMS method to model the behavior of head circumference growth. These methods are limited because they compare each individual against the median of a population, which prevents characterizing individual growth, while mixed-effect longitudinal models allow assessing individual growth patterns and controlling variability among subjects. The objective of this study was to use mixed-effect longitudinal models to characterize growth patterns based on head circumference in children 0 to 3 years of age. Methods: being a prospective longitudinal study, the criteria for children eligibility considered inclusion and exclusion factors (WHO); 265 Colombian children (116 girls, 149 boys) living in Bogotá were distributed in 3 groups: G1: (0-12], G2: (12-24], G3: (24-36] months. They were measured every 3 months for 1 year. Two examiners were trained and continuously standardized, and they were monitored on adherence to data quality and data collection procedures. Random and systematic errors were calculated. Growth curves were constructed using mixed longitudinal models. The model was estimated through the method of estimation of restricted maximum likelihood (REML), free R statistical software, version 2.15. To adjust the models, we used the lme4 package. Results: 6 models were adjusted, with maximum gradient of growth from 0 to 12 months. Conclusions: this methodology allowed understanding the behavior of head circumference by age group and sex, and analyzing data with unbalanced structures.

Positioning and number of nutritional levels in dose-response trials to estimate the optimal-level and the adjustment of the models / Posição e número de níveis nutricionais em experimentos dose-resposta na estimativa do nível-ótimo e ajuste dos modelos

The aim of this research was to evaluate the influence of the number and position of nutrient levels used in dose-response trials in the estimation of the optimal-level (OL) and the goodness of fit on the models: quadratic polynomial (QP), exponential (EXP), linear response plateau (LRP) and quadratic response plateau (QRP). It was used data from dose-response trials realized in FCAV-Unesp Jaboticabal considering the homogeneity of variances and normal distribution. The fit of the models were evaluated considered the following statistics: adjusted coefficient of determination (R²adj), coefficient of variation (CV) and the sum of the squares of deviations (SSD).It was verified in QP and EXP models that small changes on the placement and distribution of the levels caused great changes in the estimation of the OL. The LRP model was deeply influenced by the absence or presence of the level between the response and stabilization phases (change in the straight to plateau). The QRP needed more levels on the response phase and the last level on stabilization phase to estimate correctly the plateau. It was concluded that the OL and the adjust of the models are dependent on the positioning and the number of the levels and the specific characteristics of each model, but levels defined near to the true requirement and not so spaced are better to estimate the OL.

O objetivo deste trabalho foi avaliar a influência do número e posição de níveis nutricionais utilizados em ensaios dose-resposta na estimativa do nível-ótimo (OL) e ajuste dos modelos polinomial quadrático (QP), exponencial (EXP), linear response plateau (LRP) e quadratic respose plateau (QRP). Utilizaram-se dados provenientes de ensaios dose-resposta realizados na FCAV-Unesp Jaboticabal, atendendo as pressuposições de homocedasticidade e normalidade. O ajuste dos modelos foi avaliado considerando as seguintes estatísticas: coeficiente de determinação ajustado (R²adj), coeficiente de variação (CV) e soma dos quadrados dos desvios (SSD).Verificou-se que, nos modelos QP e EXP, pequenas mudanças na localização e distribuição dos níveis ocasionam grandes alterações na estimativa do OL. O modelo LRP foi influenciado pela ausência ou presença do nível intermediário às fases de resposta e estabilização (mudança da reta crescente para platô). O modelo QRP precisou de um número maior de níveis na fase de resposta e o último nível da fase de estabilização para estimar corretamente o platô. Pôde-se concluir que a determinação do OL e o ajuste dos modelos dependem da posição e quantidade de níveis, além das características específicas de cada modelo, mas níveis definidos próximos do verdadeiro requerimento e não muito espaçados são melhores para estimar corretamente o OL.

Birth Weight and Future Life-span in Finnish Triplets.

Aims: Interest in the distribution of birth weight arises because of the association between birth weight and the future health of the child. A common statistical result is that the birth weight distribution differs slightly from the Gaussian distribution. Methods: A standard attempt has been done to split the distribution into two components, a predominant Gaussian distribution and an unspecified “residual” distribution. Results: We considered birth weight data among triplets born in Finland in 1905-1959 and compare the birth weight among stillborn and live-born triplets. The stillbirth rates are 119.1 per 1000 births for males, 124.6 for females and 121.8 for all. The sex differences are not significant. The still birth rate for the period 1905-1930 was 119.5 and for the period 1931-1959, 124.2. We identified a strong association between birth weight of the triplets and their survival. The weight distribution for male triplets is described well by the Gaussian curve, while for females a slight deviation from the Gaussian distribution is discernible.

Evaluation of three mathematical functions to describe the relationship between body weight, body condition and testicular dimensions in yankasa sheep / Evaluación de tres funciones matemáticas para describir la relación entre peso corporal, condición corporal y dimensión testicular en carneros yankasa

Body size and testicular measurements have been found to be important parameters utilized in breeding soundness evaluation. The present study therefore, aimed at determining the relationship between body weight (BW), body condition score (BCS), testicular length (TL), testicular diameter (TD) and scrotal circumference (SC) in 120 extensively reared Yankasa rams (approximately 30 months old) using linear, quadratic and cubic predictive models. Coefficient of determination (R2), Adjusted R2, the estimate of Mallows' Cp, RMSE (Root mean squares error) and the parsimony principle (p=number of parameters) were used to compare the efficiency of the different models. Strong Pearson's correlation coefficients (r = 0.83-0.94; P<0.01) were found between BW, TL, TD and SC. Spearman correlations between BCS and other variables were also highly significant (r = 0.78-0.85; P<0.01). SC was the sole variable of utmost importance in estimating BW, which was best predicted using the cubic model. However, the optimal model for BW prediction comprised TD, SC and BCS with p, R2, Adjusted R2, RMSE and Cp values of 4, 0.948, 0.946, 1.673 and 4.85, respectively. The present findings could be exploited in husbandry and selection of breeding stock for sustainable sheep production especially within the resource-poor farming system under tropical and subtropical conditions.

El tamaño corporal y las mediciones testiculares son importantes parámetros utilizados en la evaluación del buen estado de reproducción. El presente estudio, tuvo como objetivo determinar la relación entre el peso corporal (PC), score de condición corporal (SCC), longitud testicular (LT), diámetro testicular (DT) y la circunferencia escrotal (CE) en 120 carneros Yankasa criados extensivamente (aproximadamente 30 meses de edad), utilizando modelos predictivos lineales, cuadráticos y cúbicos. Se utilizaron el coeficiente de determinación (R2), R2 ajustado, estimación Cp de Mallows, ERCM (errores de raíz cuadrada media) y el principio de parsimonia (p = número de parámetros) para comparar la eficiencia de los diferentes modelos. Un fuerte coeficiente de correlación de Pearson (r= 0,83-0,94, p<0,01 ) se encontró entre PC, LT, DT y CE. Las correlaciones de Spearman entre SCC y otras variables también fueron altamente significativas (r= 0,78-0,85, p<0,01). La CE fue la única variable de suma importancia en la estimación de PC, que fue predicha de mejor manera utilizando el modelo cúbico. Sin embargo, el modelo óptimo para la predicción del PC comprendiendo DT, CE y SCC con valores p, R2, R2 ajustado, ERCM y Cp de Mallows de 4; 0,948; 0,946; 1,673 y 4,85, respectivamente. Los presentes hallazgos podrían ser explotados en la cría y selección del ganado de cría para la producción sostenible de ovejas, en especial dentro de sistemas con escasos recursos agrícolas bajo condiciones tropicales y subtropicales.

Estimation of genetic parameters for test-day milk yield in first calving buffaloes / Estimación de parámetros genéticos para producción de leche en el día de control en búfalas de primer parto / Estimação de parâmetros genéticos para produção do leite no dia do controle em búfalas de primeiro parto

Background: the milk yield records measured along lactation provide an example of repeated measures; the random regression models are an appealing approach to model repeated measures and to estimate genetic parameters. Objective: to estimate the genetic parameters by modeling the additive genetic and the residual variance for test-day milk yield in first calving buffaloes. Methods: 3,986 test-day data from 1,246 first lactations of crossbred buffalo daughters of 23 sires and 391 dams between 1997 and 2008 from five farms were used. The model included the genetic and permanent environment additive as the random effect and the contemporary group (year, month of test-day) and age at calving as covariable (linear) fixed effects. The fixed (third order) and random (third to ninth order) regressions were obtained by Legendre polynomials. The residual variances were modeled with a homogeneous structure and various heterogeneous classes. The variance components were estimated using the WOMBAT statistical program (Meyer, 2006). Results: according to the likelihood ratio test, the best model included four variance classes, considering Legendre polynomials of the fourth order for permanent environment and additive genetic effects. The heritabilities estimates were low, varying from 0.0 to 0.14. The estimates of genetic correlations were high and positive among PDC1 and PDC8, except for PCD9, which was negative. This indicates that for any of the selection criteria adopted, the indirect genetic gain is expected for all lactation curves, except for PCD9. Conclusion: heterogeneity of residual variances should be considered in models whose goal is to examine the alterations of variances according to day of lactation.

Antecedentes: los registros de producción de leche medidos a lo largo de la lactancia son un ejemplo de medidas repetidas, los modelos de regresión aleatoria presentan un enfoque atractivo para modelar medidas repetidas y para estimar parámetros genéticos. Objetivo: estimar parámetros genéticos a través de la modelación de la varianza genética y residual para producción de leche en el día de control en búfalas de primer parto. Métodos: fueron analizados 3986 controles de producción de leche en la primera lactancia de 1246 búfalas, hijas de 391 hembras y 23 toros, durante los años 1997 hasta 2008 en 5 fincas. El modelo incluyó como efectos aleatorios genético aditivo y de ambiente permanente, como efectos fijos grupo contemporáneo compuesto por mes, año de control y la covariable de la edad de la búfala al parto (lineal). Las regresiones fijas (3er orden) y aleatorias (3er a 9no orden) fueron obtenidas mediante polinomios de Legendre. Las varianzas residuales fueron modeladas con una estructura homogénea y varias clases heterogéneas. Los componentes de varianza fueron estimados utilizando el programa WOMBAT. Resultados: de acuerdo con la prueba de la razón de verosimilitud, el mejor modelo fue con 4 clases de varianzas residuales, siendo considerado un polinomio de Legendre de cuarto orden para el efecto de ambiente permanente y genético aditivo. Las heredabilidades fueron bajas, variando desde 0,00 hasta 0,14. Las correlaciones genéticas fueron altas y positivas entre los PDC1 a PDC8, excepto en el PDC9 que fue negativo con respecto a los demás controles. Conclusiones: es necesario considerar la heterogeneidad de varianzas residuales en los modelos estudiados, con el fin de modelar los cambios en las variaciones respecto a los días en lactancia.

Antecedentes: os registros da produção do leite medidos ao longo da lactação, apresentam um exemplo de medidas repetidas. Os modelos de regressão aleatória apresentam abordagem atraente para modelar medidas repetidas e estimar parâmetros genéticos. Objetivo: estimar parámetros genéticos mediante a modelação das variâncias genéticas e residual da produção do leite no dia do controle em búfalas de primeiro parto. Métodos: foram analisados 3986 controles de produção de leite em primeiras lactações de 1246 búfalas, filhas de 391 fêmeas e 23 touros, entre 1997 e 2008 em 5 fazendas. No modelo foram incluídos como efeitos aleatórios o genético aditivo e ambiente permanente, e como fixos o grupo contemporâneo (mês e ano de controle) e a covariável a idade da búfala ao parto (Lineal). As regressões fixas (3° ordem) e aleatórias (3° a 9° ordem) foram obtidas mediante polinômios ortogonais de Legendre. As variâncias residuais foram modeladas mediante estruturas homogêneas e diferentes classes heterogêneas. Os componentes de variância foram estimadas mediante o software WOMBAT. Resultados: de acordo com a prova da máxima verossimilhança, o melhor modelo foi com 4 classes de variâncias residuais, sendo considerado polinômios de Legendre de quarto ordem para o efeito de ambiente permanente e genético aditivo. As herdabilidades foram baixas, variando desde 0,00 até 0,14. As correlações genéticas foram altas e positivas entre o PDC1 e PDC8, a exceção do PDC9 que apresentou valores negativos com respeito aos outros controles. Conclusões:é necessário considerar heterogeneidade de variâncias nos modelos estudados, tentando modelar as mudanças nas variações respeito aos dias em lactação.

Spatial regression methods to evaluate beekeeping production in the state of Rio de Janeiro / Métodos de regressão espacial para avaliação da produção apícola do estado do Rio de Janeiro

Brazilian beekeeping has been developed from the africanization of the honeybees and its high performance launches Brazil as one of the world´s largest honey producer. The Southeastern region has an expressive position in this market (45%), but the state of Rio de Janeiro is the smallest producer, despite presenting large areas of wild vegetation for honey production. In order to analyze the honey productivity in the state of Rio de Janeiro, this research used classic and spatial regression approaches. The data used in this study comprised the responses regarding beekeeping from 1418 beekeepers distributed throughout 72 counties of this state. The best statistical fit was a semiparametric spatial model. The proposed model could be used to estimate the annual honey yield per hive in regions and to detect production factors more related to beekeeping. Honey productivity was associated with the number of hives, wild swarm collection and losses in the apiaries. This paper highlights that the beekeeping sector needs support and help to elucidate the problems plaguing beekeepers, and the inclusion of spatial effects in the regression models is a useful tool in geographical data.

A apicultura brasileira se desenvolveu a partir da africanização das abelhas melíferas, e seu bom desempenho permitiu lançar o Brasil como um dos maiores produtores mundiais de mel. A região Sudeste ocupa uma posição significativa no mercado, mas o estado do Rio de Janeiro é o menor produtor, apesar de apresentar áreas expressivas de vegetação silvestre para a produção de mel. Para analisar a produtividade de mel no estado do Rio de Janeiro, esta pesquisa estudou diversos métodos de regressão clássica e espacial. Os dados analisados compreenderam respostas sobre apicultura de 1418 apicultores distribuídos em 72 municípios do Rio de Janeiro. O melhor ajuste estatístico utilizado foi um modelo semiparamétrico espacial. A utilidade do modelo proposto é estimar a produção anual de mel por colmeia nas diversas regiões e identificar os fatores de produção mais relacionados à apicultura. A produtividade de mel mostrou-se mais associada com o número de colmeias, a coleta de enxame silvestre e as perdas em apiários. Este trabalho destacou que o segmento apícola necessita de apoio para auxiliar na identificação dos problemas que afetam os apicultores. A utilização de efeitos espaciais em modelos de regressão são ferramentas úteis quando são utilizados dados geograficamente referenciados.