Antonio Sanhueza

The Generalized Birnbaum–Saunders Distribution and Its Theory, Methodology, and Application

In this paper, we discuss the class of generalized Birnbaum–Saunders distributions, which is a very flexible family suitable for modeling lifetime data as it allows for different degrees of kurtosis and asymmetry and unimodality as well as bimodality. We describe the theoretical developments on this model including properties, transformations and related distributions, lifetime analysis, and shape analysis. We also discuss methods of inference based on uncensored and censored data, diagnostics methods, goodness-of-fit tests, and random number generation algorithms for the generalized Birnbaum–Saunders model. Finally, we present some illustrative examples and show that this distribution fits the data better than the classical Birnbaum–Saunders model.

Lifetime analysis based on the generalized Birnbaum-Saunders distribution

In this paper, we consider a family of generalized Birnbaum-Saunders distributions and present a lifetime analysis based mainly on the hazard function of this model. In addition, we carry out maximum likelihood estimation by using an iterative algorithm, which produces robust estimates. Asymptotic inference is also presented. Next, the quality of the estimation method is examined by means of Monte Carlo simulations. We then provide a practical example to illustrate the obtained results. From this example and based on goodness-of-fit methods, we show that the GBS distribution results in a more appropriate model for modeling fatigue data than other models commonly used to model this type of data. Finally, we estimate the hazard function and the critical point of this function.

Mixture inverse Gaussian distributions and its transformations, moments and applications

Skewed models are important and necessary when parametric analyses are carried out on data. Mixture distributions produce widely flexible models with good statistical and probabilistic properties, and the mixture inverse Gaussian (MIG) model is one of those. Transformations of the MIG model also create new parametric distributions, which are useful in diverse situations. The aim of this paper is to discuss several aspects of the MIG distribution useful for modelling positive data. We specifically discuss transformations, the derivation of moments, fitting of models, and a shape analysis of the transformations. Finally, real examples from engineering, environment, insurance, and toxicology are presented for illustrating some of the results developed here. Three of the four data sets, which have arisen from the consulting work of the authors, are new and have not been previously analysed. All these examples display that the empirical fit of the MIG distribution to the data is very good.

A Skewed Sinh-Normal Distribution and Its Properties and Application to Air Pollution

In this article, we introduce a skewed version of the sinh-normal distribution and discuss some of its properties. In addition, we characterize an extension of the Birnbaum–Saunders model associated with this distribution from a probabilistic viewpoint along with a lifetime analysis based on its hazard rate. Finally, one of the proposed models is applied to air pollution data in order to illustrate its usefulness.

Promoter Methylation Profile in Preneoplastic and Neoplastic Gallbladder Lesions

Gallbladder carcinoma (GBC) is a highly malignant neoplasm and represents the leading cause of cancer death in Chilean women. In order to determine the potential role of promoter methylation in gallbladder carcinogenesis, we investigated the frequency of this epigenetic mechanism by methylation‐specific polymerase chain reaction (MSP) in 35 chronic cholecystitis (CC, separated according to the presence or absence of metaplasia), 19 early cancers (mucosa or muscularis propia invasion) and 48 advanced carcinomas with invasion of the gallbladder subserosa (25 cases) and serosa (23 cases). We examined 14 genes and observed an increase of multigenic methylation during tumoral progression which was not significantly associated with the patients age. Four genes (DAPK1, DLC1, TIMP3, and RARβ2) displayed a progressive increase in their methylation status from CC without metaplasia to advanced carcinoma invading the serosa layer (P ≤ 0.05). The survival analysis indicated that a methylated condition of DLC1 gene is significantly associated with poor prognosis (P = 0.04), whereas a methylated state of MGMT gene correlated with better patient survival (P = 0.006). Our findings indicate that aberrant hypermethylation of promoter regions is an early, progressive and cumulative event in gallbladder carcinogenesis. Furthermore, the methylation levels seems to accumulate in the progression of CC without metaplasia to CC with metaplasia, a fact that could provide new evidence to consider this morphological adaptation of GB mucosa as a premalignant lesion. Finally, the methylation status of some individual genes could be useful biomarkers with potential clinical application in diagnosis or prognosis of GBC if they are validated in a greater number of clinical samples.

Random number generators for the generalized Birnbaum–Saunders distribution

The generalized Birnbaum–Saunders distribution pertains to a class of lifetime models including both lighter and heavier tailed distributions. This model adapts well to lifetime data, even when outliers exist, and has other good theoretical properties and application perspectives. However, statistical inference tools may not exist in closed form for this model. Hence, simulation and numerical studies are needed, which require a random number generator. Three different ways to generate observations from this model are considered here. These generators are compared by utilizing a goodness-of-fit procedure as well as their effectiveness in predicting the true parameter values by using Monte Carlo simulations. This goodness-of-fit procedure may also be used as an estimation method. The quality of this estimation method is studied here. Finally, through a real data set, the generalized and classical Birnbaum–Saunders models are compared by using this estimation method.

Air Contaminant Statistical Distributions with Application to PM10 in Santiago, Chile

The use of statistical distributions to predict air quality is valuable for determining the impact of air chemical contaminants on human health. Concentrations of air pollutants are treated as random variables that can be modeled by a statistical distribution that is positively skewed and starts from zero. The type of distribution selected for analyzing air pollution data and its associated parameters depend on factors such as emission source and local meteorology and topography. International environmental guideline use appropriate distributions to compute exceedance probabilities and percentiles for setting administrative targets and issuing environmental alerts. The distribution bears a relationship to the normal distribution, and there are theoretical - and physical-based mechanistic arguments that support its use when analyzing air-pollutant data. Others distribution have also been used to model air population data, such as the beta, exponential, gamma, Johnson, log-logistic, Pearson, and Weibull distribution. One model also developed from physical-mechanistic considerations that has received considerable interest in recent year is the Birnbaum-Saunders distribution. This distribution has theoretical arguments and properties similar to those of the log-normal distribution, which renders it useful for modeling air contamination data. In this review, we have addressed the range of common atmospheric contaminants and the health effects they cause. We have also reviewed the statistical distributions that have been use to model air quality, after which we have detailed the problem of air contamination in Santiago, Chile. We have illustrated a methodology that is based on the Birnbaum-Saunders distributions to analyze air contamination data from Santiago, Chile. Finally, in the conclusions, we have provided a list of synoptic statements designed to help readers understand the significance of air pollution in Chile, and in Santiago, in particular, but that can be useful to other cites and countries.

Factors associated with morbitity in liver hydatid surgery

Background:  The purpose of the present paper was to determine the association between clinical evolutionary and laboratory variables with postoperative morbidity in patients surgically treated for liver hydatidosis (LH).

Systematic Review of Literature with Different Types of Designs

En ciertas situaciones, en especial frecuentes en el ambito de la cirugia y sus disciplinas afines (donde lo que predomina son estudios de tipo observacional), la conduccion de ensayos clinicos con asignacion aleatoria (EC) es muy dificil; por ende, realizar revisiones sistematicas (RS) con base en EC y posteriormente meta-analizar la informacion lo es aun mas. Por esta razon hemos generado una metodologia para realizar RS con diferentes tipos de disenos (incluyendo estudios observacionales), como una alternativa para aclarar la incertidumbre en el ambito de la terapia cuando existen pocos EC y la evidencia se apoya fundamentalmente en estudios descriptivos y observacionales. El objetivo de este estudio fue exponer una metodologia para conducir RS con diversos tipos de disenos. La metodologia, se basa en la ponderacion de los diferentes estudios primarios a traves de la aplicacion de un escore de calidad metodologica compuesto por 3 items (tipo de diseno del estudio, tamano de la poblacion estudiada y metodologia empleada en el estudio). Una vez asignado un puntaje se aplica un calculo de promedios ponderados con sus respectivos intervalos de confianza del 95% a cada variable que se desee estudiar, lo que permite finalmente realizar un meta-analisis y comparar grupos. Se presenta una propuesta metodologica para conducir RS con diversos tipos de disenos.

Curación asistida por presión negativa comparada con curación convencional en el tratamiento del pie diabético amputado. Ensayo clínico aleatorio

INTRODUCTION Foot amputation wounds in patients with diabetes are complex and treatment is often difficult. At the moment negative pressure wound therapy (NPWT) is widely used for the treatment of several types of wounds. Nevertheless, the clinical evidence to support the application of this dressing in foot amputation wounds in patients with diabetes is scarce. The aim of this study was to evaluate the efficacy of NPWT compared with standard wound dressing to treat diabetic foot amputation wounds. PATIENTS AND METHOD Randomised controlled trial. Diabetic patients aged 18 years or older with a foot amputation wound were assigned to treatment with NPWT (A group) or standard wound dressing (B group). Primary efficacy end point was time in reaching 90% of wound granulation. A size of sample of 11 patients per group was used. NPWT was prepared with a polyurethane ether foam dressing, a Nelaton catheter, a transparent adhesive drape and continuous negative pressure of 100 mmHg. The wound was treated every 48-72 h and evaluated weekly. Descriptive and analytical statistics were used. RESULTS There were 24 patients, with a mean age of 61.8 +/- 9 years (79% men), 12 in each group. The average time to reach 90% of granulation was lower in A group (18.8 +/- 6 days versus 32.3 +/- 13.7 days), a statistically significant difference (P = 0.007). CONCLUSION NPWT reduces the granulation time of diabetic foot amputation wounds by 40%, compared with the standard wound dressing.