21 resultados para b-hCG regression curve
em Biblioteca Digital da Produção Intelectual da Universidade de São Paulo
Resumo:
The objective of this paper is to model variations in test-day milk yields of first lactations of Holstein cows by RR using B-spline functions and Bayesian inference in order to fit adequate and parsimonious models for the estimation of genetic parameters. They used 152,145 test day milk yield records from 7317 first lactations of Holstein cows. The model established in this study was additive, permanent environmental and residual random effects. In addition, contemporary group and linear and quadratic effects of the age of cow at calving were included as fixed effects. Authors modeled the average lactation curve of the population with a fourth-order orthogonal Legendre polynomial. They concluded that a cubic B-spline with seven random regression coefficients for both the additive genetic and permanent environment effects was to be the best according to residual mean square and residual variance estimates. Moreover they urged a lower order model (quadratic B-spline with seven random regression coefficients for both random effects) could be adopted because it yielded practically the same genetic parameter estimates with parsimony. (C) 2012 Elsevier B.V. All rights reserved.
Resumo:
The objective of this study was to estimate (co)variance components using random regression on B-spline functions to weight records obtained from birth to adulthood. A total of 82 064 weight records of 8145 females obtained from the data bank of the Nellore Breeding Program (PMGRN/Nellore Brazil) which started in 1987, were used. The models included direct additive and maternal genetic effects and animal and maternal permanent environmental effects as random. Contemporary group and dam age at calving (linear and quadratic effect) were included as fixed effects, and orthogonal Legendre polynomials of age (cubic regression) were considered as random covariate. The random effects were modeled using B-spline functions considering linear, quadratic and cubic polynomials for each individual segment. Residual variances were grouped in five age classes. Direct additive genetic and animal permanent environmental effects were modeled using up to seven knots (six segments). A single segment with two knots at the end points of the curve was used for the estimation of maternal genetic and maternal permanent environmental effects. A total of 15 models were studied, with the number of parameters ranging from 17 to 81. The models that used B-splines were compared with multi-trait analyses with nine weight traits and to a random regression model that used orthogonal Legendre polynomials. A model fitting quadratic B-splines, with four knots or three segments for direct additive genetic effect and animal permanent environmental effect and two knots for maternal additive genetic effect and maternal permanent environmental effect, was the most appropriate and parsimonious model to describe the covariance structure of the data. Selection for higher weight, such as at young ages, should be performed taking into account an increase in mature cow weight. Particularly, this is important in most of Nellore beef cattle production systems, where the cow herd is maintained on range conditions. There is limited modification of the growth curve of Nellore cattle with respect to the aim of selecting them for rapid growth at young ages while maintaining constant adult weight.
Resumo:
A simple and sensitive analytical method for simultaneous determination of anastrozole, bicalutamide, and tamoxifen as well as their synthetic impurities, anastrozole pentamethyl, bicalutamide 3-fluoro-isomer, and tamoxifen e-isomer, was developed and validated by using high performance liquid chromatography (HPLC). The separation was achieved on a Symmetry (R) C-8 column (100 x 4.6 mm i.d., 3.5 mu m) at room temperature (+/- 24 degrees C), with a mobile phase consisting of acetonitrile/water containing 0.18% N,N dimethyloctylamine and pH adjusted to 3.0 with orthophosphoric acid (46.5/53.5, v/v) at a flow rate of 1.0 mL min(-1) within 20 min. The detection was made at a wavelength of 270 nm by using ultraviolet (UV) detector. No interference peaks from excipients and relative retention time indicated the specificity of the method. The calibration curve showed correlation coefficients (r) > 0.99 calculated by linear regression and analysis of variance (ANOVA). The limit of detection (LOD) and limit of quantitation (LOQ), respectively, were 2.2 and 6.7 mu g mL(-1) for anastrozole, 2.61 and 8.72 mu g mL(-1) for bicalutamide, 2.0 and 6.7 mu g mL(-1) for tamoxifen, 0.06 and 0.22 mu g mL(-1) for anastrozole pentamethyl, 0.02 and 0.07 mu g mL(-1) for bicalutamide 3-fluoro-isomer, and 0.002 and 0.007 mu g mL(-1) for tamoxifen e-isomer. Intraday and interday relative standard deviations (RSDs) were <2.0% (drugs) and <10% (degradation products) as well as the comparison between two different analysts, which were calculated by f test. (C) 2012 Elsevier B.V. All rights reserved.
Resumo:
An extension of some standard likelihood based procedures to heteroscedastic nonlinear regression models under scale mixtures of skew-normal (SMSN) distributions is developed. This novel class of models provides a useful generalization of the heteroscedastic symmetrical nonlinear regression models (Cysneiros et al., 2010), since the random term distributions cover both symmetric as well as asymmetric and heavy-tailed distributions such as skew-t, skew-slash, skew-contaminated normal, among others. A simple EM-type algorithm for iteratively computing maximum likelihood estimates of the parameters is presented and the observed information matrix is derived analytically. In order to examine the performance of the proposed methods, some simulation studies are presented to show the robust aspect of this flexible class against outlying and influential observations and that the maximum likelihood estimates based on the EM-type algorithm do provide good asymptotic properties. Furthermore, local influence measures and the one-step approximations of the estimates in the case-deletion model are obtained. Finally, an illustration of the methodology is given considering a data set previously analyzed under the homoscedastic skew-t nonlinear regression model. (C) 2012 Elsevier B.V. All rights reserved.
Resumo:
In this paper, we propose a cure rate survival model by assuming the number of competing causes of the event of interest follows the Geometric distribution and the time to event follow a Birnbaum Saunders distribution. We consider a frequentist analysis for parameter estimation of a Geometric Birnbaum Saunders model with cure rate. Finally, to analyze a data set from the medical area. (C) 2011 Elsevier B.V. All rights reserved.
Resumo:
Cryptococcosis is a subacute or chronic systemic mycosis with a cosmopolitan nature, caused by yeast of the genus Cryptococcus neoformans. The model of systemic cryptococcosis in mice with severe combined immunodeficiency (SCID) is useful for immunological and therapeutic study of the disease in immunodeficient hosts. Amphotericin B, fluconazole and flucytosine are the drugs most commonly used to treat cryptococcosis. Voriconazole is a triazole with high bioavailability, large distribution volume, and excellent penetration of the central nervous system. The objective of this study was to evaluate treatment with amphotericin B (AMB), voriconazole (VRC), and AMB, used in combination with VRC, of experimental pulmonary cryptococcosis in a murine model (SCID). The animals were inoculated intravenously (iv) with a solution containing 3.0 x 10(5) viable cells of C. neoformans ATCC 90112, (serotype A). Treatments were performed with amphotericin B (1.5 mg/kg/day), voriconazole (40.0 mg/kg/day) and AMB (1.5 mg/kg/day) combined with VRC (40.0 mg/kg/day); began 1 day after the initial infection; were daily; and lasted 15 days. Evaluations were performed using analysis of the survival curve and isolation of yeast in the lung tissue. There was a significant increase in survival in groups treated with AMB combined with VRC, compared with the untreated group and groups receiving other treatments (P < 0.05). In the group treated only with VRC and AMB combined with VRC, there was a significant reduction (P < 0.05) in the isolation of C. neoformans in lung tissue. Amphotericin B combined with voriconazole may be an effective alternative to increasing survival and may reduce yeast in the lung tissue of mice with pulmonary cryptococcosis and SCID.
Resumo:
The objective of this research was to use non-linear models to describe the growth pattern in Santa Ines sheep and to study the influence of environmental effects on curve parameters with the best-fit model. The models included the Brody, Richards, Von Bertalanffy, Gompertz, and Logistic models. We used 773 field reports on 162 animals ranging in age from 120 to 774 days, including 46 males and 116 females. The statistics used to evaluate the quality of fit included RMS (residual mean square), C% (percentage of convergence), R-2 (adjusted determination coefficient) and MAD (mean absolute deviation). Of the fixed effects studied, the only significant relationship was the effect of sex on parameter A. The Richards model was problematic during the process of convergence. Considering all studied criteria, the Logistic model presented the best fit in describing the growth pattern in Santa Ines sheep. (C) 2011 Elsevier B.V. All rights reserved.
Resumo:
In this paper we obtain asymptotic expansions, up to order n(-1/2) and under a sequence of Pitman alternatives, for the nonnull distribution functions of the likelihood ratio, Wald, score and gradient test statistics in the class of symmetric linear regression models. This is a wide class of models which encompasses the t model and several other symmetric distributions with longer-than normal tails. The asymptotic distributions of all four statistics are obtained for testing a subset of regression parameters. Furthermore, in order to compare the finite-sample performance of these tests in this class of models, Monte Carlo simulations are presented. An empirical application to a real data set is considered for illustrative purposes. (C) 2011 Elsevier B.V. All rights reserved.
Resumo:
Background There are no studies that describe the impact of the cumulative fluid balance on the outcomes of cancer patients admitted to intensive care units ICUs. The aim of our study was to evaluate the relationship between fluid balance and clinical outcomes in these patients. Method One hundred twenty-two cancer patients were prospectively evaluated for survival during a 30-day period. Univariate (Chi-square, t-test, MannWhitney) and multiple logistic regression analyses were used to identify the admission parameters associated with mortality. Results The mean cumulative fluid balance was significantly higher in non-survivors than in survivors [1675?ml/24?h (4712921) vs. 887?ml/24?h (104557), P?=?0.017]. We used the area under the curve and the intersection of the sensibility and specificity curves to define a cumulative fluid balance value of 1100?ml/24?h. This value was used in the univariate model. In the multivariate model, the following variables were significantly associated with mortality in cancer patients: the Acute Physiology and Chronic Health Evaluation II score at admission [Odds ratio (OR) 1.15; 95% confidence interval (CI) (1.051.26), P?=?0.003], the Lung Injury Score at admission [OR 2.23; 95% CI (1.293.87), P?=?0.004] and a positive fluid balance higher than 1100?ml/24?h at ICU [OR 5.14; 95% CI (1.4518.24), P?=?0.011]. Conclusion A cumulative positive fluid balance higher than 1100?ml/24?h was independently associated with mortality in patients with cancer. These findings highlight the importance of improving the evaluation of these patients' volemic state and indicate that defined goals should be used to guide fluid therapy.
Resumo:
Background: We aimed to investigate the performance of five different trend analysis criteria for the detection of glaucomatous progression and to determine the most frequently and rapidly progressing locations of the visual field. Design: Retrospective cohort. Participants or Samples: Treated glaucoma patients with =8 Swedish Interactive Thresholding Algorithm (SITA)-standard 24-2 visual field tests. Methods: Progression was determined using trend analysis. Five different criteria were used: (A) =1 significantly progressing point; (B) =2 significantly progressing points; (C) =2 progressing points located in the same hemifield; (D) at least two adjacent progressing points located in the same hemifield; (E) =2 progressing points in the same Garway-Heath map sector. Main Outcome Measures: Number of progressing eyes and false-positive results. Results: We included 587 patients. The number of eyes reaching a progression endpoint using each criterion was: A = 300 (51%); B = 212 (36%); C = 194 (33%); D = 170 (29%); and E = 186 (31%) (P = 0.03). The numbers of eyes with positive slopes were: A = 13 (4.3%); B = 3 (1.4%); C = 3 (1.5%); D = 2 (1.1%); and E = 3 (1.6%) (P = 0.06). The global slopes for progressing eyes were more negative in Groups B, C and D than in Group A (P = 0.004). The visual field locations that progressed more often were those in the nasal field adjacent to the horizontal midline. Conclusions: Pointwise linear regression criteria that take into account the retinal nerve fibre layer anatomy enhances the specificity of trend analysis for the detection glaucomatous visual field progression.
Resumo:
Background: Tuberculosis (TB) remains a public health issue worldwide. The lack of specific clinical symptoms to diagnose TB makes the correct decision to admit patients to respiratory isolation a difficult task for the clinician. Isolation of patients without the disease is common and increases health costs. Decision models for the diagnosis of TB in patients attending hospitals can increase the quality of care and decrease costs, without the risk of hospital transmission. We present a predictive model for predicting pulmonary TB in hospitalized patients in a high prevalence area in order to contribute to a more rational use of isolation rooms without increasing the risk of transmission. Methods: Cross sectional study of patients admitted to CFFH from March 2003 to December 2004. A classification and regression tree (CART) model was generated and validated. The area under the ROC curve (AUC), sensitivity, specificity, positive and negative predictive values were used to evaluate the performance of model. Validation of the model was performed with a different sample of patients admitted to the same hospital from January to December 2005. Results: We studied 290 patients admitted with clinical suspicion of TB. Diagnosis was confirmed in 26.5% of them. Pulmonary TB was present in 83.7% of the patients with TB (62.3% with positive sputum smear) and HIV/AIDS was present in 56.9% of patients. The validated CART model showed sensitivity, specificity, positive predictive value and negative predictive value of 60.00%, 76.16%, 33.33%, and 90.55%, respectively. The AUC was 79.70%. Conclusions: The CART model developed for these hospitalized patients with clinical suspicion of TB had fair to good predictive performance for pulmonary TB. The most important variable for prediction of TB diagnosis was chest radiograph results. Prospective validation is still necessary, but our model offer an alternative for decision making in whether to isolate patients with clinical suspicion of TB in tertiary health facilities in countries with limited resources.
Resumo:
Model diagnostics is an integral part of model determination and an important part of the model diagnostics is residual analysis. We adapt and implement residuals considered in the literature for the probit, logistic and skew-probit links under binary regression. New latent residuals for the skew-probit link are proposed here. We have detected the presence of outliers using the residuals proposed here for different models in a simulated dataset and a real medical dataset.
Resumo:
Background. The link between endogenous estrogen, coronary artery disease (CAD), and death in postmenopausal women is uncertain. We analyzed the association between death and blood levels of estrone in postmenopausal women with known coronary artery disease (CAD) or with a high-risk factor score for CAD. Methods. 251 postmenopausal women age 50-90 years not on estrogen therapy. Fasting blood for estrone and heart disease risk factors were collected at baseline. Women were grouped according to their estrone levels (<15 and >= 15 pg/mL). Fatal events were recorded after 5.8 perpendicular to 1.4 years of followup. Results. The Kaplan-Meier survival curve showed a significant trend (P = 0.039) of greater all-cause mortality in women with low estrone levels (< 15 pg/mL). Cox multivariate regression analysis model adjusted for body mass index, diabetes, dyslipidemia, family history, and estrone showed estrone (OR = 0.45; P = 0.038) as the only independent variable for all-cause mortality. Multivariate regression model adjusted for age, body mass index, hypertension, diabetes, dyslipidemia, family history, and estrone showed that only age (OR = 1.06; P = 0.017) was an independent predictor of all-cause mortality. Conclusions. Postmenopausal women with known CAD or with a high-risk factor score for CAD and low estrone levels (< 15 pg/mL) had increased all-cause mortality.
Resumo:
The beta-Birnbaum-Saunders (Cordeiro and Lemonte, 2011) and Birnbaum-Saunders (Birnbaum and Saunders, 1969a) distributions have been used quite effectively to model failure times for materials subject to fatigue and lifetime data. We define the log-beta-Birnbaum-Saunders distribution by the logarithm of the beta-Birnbaum-Saunders distribution. Explicit expressions for its generating function and moments are derived. We propose a new log-beta-Birnbaum-Saunders regression model that can be applied to censored data and be used more effectively in survival analysis. We obtain the maximum likelihood estimates of the model parameters for censored data and investigate influence diagnostics. The new location-scale regression model is modified for the possibility that long-term survivors may be presented in the data. Its usefulness is illustrated by means of two real data sets. (C) 2011 Elsevier B.V. All rights reserved.
Resumo:
Objective. The aim of this study was to investigate the effect of CAPE on the insulin signaling and inflammatory pathway in the liver of mice with high fat diet induced obesity. Material/Methods. Swiss mice were fed with standard chow or high-fat diet for 12-week. After the eighth week, animals in the HFD group with serum glucose levels higher than 200 mg/dL were divided into two groups, HFD and HFD receiving 30 mg/kg of CAPE for 4 weeks. After 12 weeks, the blood samples could be collected and liver tissue extracted for hormonal and biochemical measurements, and insulin signaling and inflammatory pathway analyzes. Results. The high-fat diet group exhibited more weight gain, glucose intolerance, and hepatic steatosis compared with standard diet group. The CAPE treatment showed improvement in glucose sensitivity characterized by an area under glucose curve similar to the control group in an oral glucose tolerance test Furthermore, CAPE treatment promoted amelioration in hepatic steatosis compared with the high-fat diet group. The increase in glucose sensitivity was associated with the improvement in insulin-stimulated phosphorylation of the insulin receptor substrate-2, followed by an increase in Akt phosphorylation. In addition, it was observed that CAPE reduced the induction of the inflammatory pathway, c-jun-N- terminal kinase, the nuclear factor kappa B, and cyclooxygenase-2 expression, respectively. Conclusions. Overall, these findings indicate that CAPE exhibited anti-inflammatory activity that partly restores normal metabolism, reduces the molecular changes observed in obesity and insulin resistance, and therefore has a potential as a therapeutic agent in obesity. (C) 2012 Elsevier Inc. All rights reserved.