937 resultados para additive variance


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BACKGROUND Chronic HCV infection is a leading cause of liver-related morbidity globally. The innate and adaptive immune responses are thought to be important in determining viral outcomes. Polymorphisms associated with the IFNL3 (IL28B) gene are strongly associated with spontaneous clearance and treatment outcomes. OBJECTIVE This study investigates the importance of HLA genes in the context of genetic variation associated with the innate immune genes IFNL3 and KIR2DS3. DESIGN We assess the collective influence of HLA and innate immune genes on viral outcomes in an Irish cohort of women (n=319) who had been infected from a single source as well as a more heterogeneous cohort (Swiss Cohort, n=461). In the Irish cohort, a number of HLA alleles are associated with different outcomes, and the impact of IFNL3-linked polymorphisms is profound. RESULTS Logistic regression was performed on data from the Irish cohort, and indicates that the HLA-A*03 (OR 0.36 (0.15 to 0.89), p=0.027) -B*27 (OR 0.12 (0.03 to 0.45), p=<0.001), -DRB1*01:01 (OR 0.2 (0.07 to 0.61), p=0.005), -DRB1*04:01 (OR 0.31 (0.12 to 0.85, p=0.02) and the CC IFNL3 rs12979860 genotypes (OR 0.1 (0.04 to 0.23), p<0.001) are significantly associated with viral clearance. Furthermore, DQB1*02:01 (OR 4.2 (2.04 to 8.66), p=0.008), KIR2DS3 (OR 4.36 (1.62 to 11.74), p=0.004) and the rs12979860 IFNL3 'T' allele are associated with chronic infection. This study finds no interactive effect between IFNL3 and these Class I and II alleles in relation to viral clearance. There is a clear additive effect, however. Data from the Swiss cohort also confirms independent and additive effects of HLA Class I, II and IFNL3 genes in their prediction of viral outcome. CONCLUSIONS This data supports a critical role for the adaptive immune response in the control of HCV in concert with the innate immune response.

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INTRODUCTION Anemia and renal impairment are important co-morbidities among patients with coronary artery disease undergoing Percutaneous Coronary Intervention (PCI). Disease progression to eventual death can be understood as the combined effect of baseline characteristics and intermediate outcomes. METHODS Using data from a prospective cohort study, we investigated clinical pathways reflecting the transitions from PCI through intermediate ischemic or hemorrhagic events to all-cause mortality in a multi-state analysis as a function of anemia (hemoglobin concentration <120 g/l and <130 g/l, for women and men, respectively) and renal impairment (creatinine clearance <60 ml/min) at baseline. RESULTS Among 6029 patients undergoing PCI, anemia and renal impairment were observed isolated or in combination in 990 (16.4%), 384 (6.4%), and 309 (5.1%) patients, respectively. The most frequent transition was from PCI to death (6.7%, 95% CI 6.1-7.3), followed by ischemic events (4.8%, 95 CI 4.3-5.4) and bleeding (3.4%, 95% CI 3.0-3.9). Among patients with both anemia and renal impairment, the risk of death was increased 4-fold as compared to the reference group (HR 3.9, 95% CI 2.9-5.4) and roughly doubled as compared to patients with either anemia (HR 1.7, 95% CI 1.3-2.2) or renal impairment (HR 2.1, 95% CI 1.5-2.9) alone. Hazard ratios indicated an increased risk of bleeding in all three groups compared to patients with neither anemia nor renal impairment. CONCLUSIONS Applying a multi-state model we found evidence for a gradient of risk for the composite of bleeding, ischemic events, or death as a function of hemoglobin value and estimated glomerular filtration rate at baseline.

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Background: Current literature suggests a positive influence of additive classical homeopathyon global health and well-being in cancer patients. Besides encouraging case reports, thereis little if any research on long-term survival of patients who obtain homeopathic care duringcancer treatment. Design: Data from cancer patients who had undergone homeopathic treatment complementaryto conventional anti-cancer treatment at the Outpatient Unit for Homeopathy in MalignantDiseases, Medical University Vienna, Department of Medicine I, Vienna, Austria, were collected,described and a retrospective subgroup-analysis with regard to survival time was performed.Patient inclusion criteria were at least three homeopathic consultations, fatal prognosis ofdisease, quantitative and qualitative description of patient characteristics, and survival time. Results: In four years, a total of 538 patients were recorded to have visited the OutpatientUnit Homeopathy in Malignant Diseases, Medical University Vienna, Department of Medicine I, Vienna, Austria. 62.8% of them were women, and nearly 20% had breast cancer. From the 53.7%(n = 287) who had undergone at least three homeopathic consultations within four years, 18.7%(n = 54) fulfilled inclusion criteria for survival analysis. The surveyed neoplasms were glioblas-toma, lung, cholangiocellular and pancreatic carcinomas, metastasized sarcoma, and renal cellcarcinoma. Median overall survival was compared to expert expectations of survival outcomesby specific cancer type and was prolonged across observed cancer entities (p < 0.001). Conclusion: Extended survival time in this sample of cancer patients with fatal prognosis butadditive homeopathic treatment is interesting. However, findings are based on a small sample,and with only limited data available about patient and treatment characteristics. The relationshipbetween homeopathic treatment and survival time requires prospective investigation in largersamples possibly using matched-pair control analysis or randomized trials.

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We propose a nonparametric variance estimator when ranked set sampling (RSS) and judgment post stratification (JPS) are applied by measuring a concomitant variable. Our proposed estimator is obtained by conditioning on observed concomitant values and using nonparametric kernel regression.

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Laser ablation/ionisation mass spectrometry with a vertical resolution at a nanometre scale was applied for the quantitative characterisation of the chemical composition of additive-assisted Cu electroplated deposits used in the microchip industry. The detailed chemical analysis complements information gathered by optical techniques and allows new insights into the metal deposition process.

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Previous studies (e.g., Hamori, 2000; Ho and Tsui, 2003; Fountas et al., 2004) find high volatility persistence of economic growth rates using generalized autoregressive conditional heteroskedasticity (GARCH) specifications. This paper reexamines the Japanese case, using the same approach and showing that this finding of high volatility persistence reflects the Great Moderation, which features a sharp decline in the variance as well as two falls in the mean of the growth rates identified by Bai and Perronâs (1998, 2003) multiple structural change test. Our empirical results provide new evidence. First, excess kurtosis drops substantially or disappears in the GARCH or exponential GARCH model that corrects for an additive outlier. Second, using the outlier-corrected data, the integrated GARCH effect or high volatility persistence remains in the specification once we introduce intercept-shift dummies into the mean equation. Third, the time-varying variance falls sharply, only when we incorporate the break in the variance equation. Fourth, the ARCH in mean model finds no effects of our more correct measure of output volatility on output growth or of output growth on its volatility.

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This paper revisits the issue of conditional volatility in real GDP growth rates for Canada, Japan, the United Kingdom, and the United States. Previous studies find high persistence in the volatility. This paper shows that this finding largely reflects a nonstationary variance. Output growth in the four countries became noticeably less volatile over the past few decades. In this paper, we employ the modified ICSS algorithm to detect structural change in the unconditional variance of output growth. One structural break exists in each of the four countries. We then use generalized autoregressive conditional heteroskedasticity (GARCH) specifications modeling output growth and its volatility with and without the break in volatility. The evidence shows that the time-varying variance falls sharply in Canada, Japan, and the U.K. and disappears in the U.S., excess kurtosis vanishes in Canada, Japan, and the U.S. and drops substantially in the U.K., once we incorporate the break in the variance equation of output for the four countries. That is, the integrated GARCH (IGARCH) effect proves spurious and the GARCH model demonstrates misspecification, if researchers neglect a nonstationary unconditional variance.

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Although many family-based genetic studies have collected dietary data, very few have used the dietary information in published findings. No single solution has been presented or discussed in the literature to deal with the problem of using factor analyses for the analyses of dietary data from several related individuals from a given household. The standard statistical approach of factor analysis cannot be applied to the VIVA LA FAMILIA Study diet data to ascertain dietary patterns since this population consists of three children from each family, thus the dietary patterns of the related children may be correlated and non-independent. Addressing this problem in this project will enable us to describe the dietary patterns in Hispanic families and to explore the relationships between dietary patterns and childhood obesity. ^ In the VIVA LA FAMILIA Study, an overweight child was first identified and then his/her siblings and parents were brought in for data collection which included 24 hour recalls and food frequency questionnaire (FFQ). Dietary intake data were collected using FFQ and 24 hour recalls on 1030 Hispanic children from 319 families. ^ The design of the VIVA LA FAMILIA Study has important and unique statistical considerations since its participants are related to each other, the majority form distinct nuclear families. Thus, the standard approach of factor analysis cannot be applied to these diet data to ascertain dietary patterns. In this project we propose to investigate whether the determinants of the correlation matrix of each family unit will allow us to adjust the original correlation matrix of the dietary intake data prior to ascertaining dietary intake patterns. If these methods are appropriate, then in the future the dietary patterns among related individuals could be assessed by standard orthogonal principal component factor analysis.^

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Many studies have shown relationships between air pollution and the rate of hospital admissions for asthma. A few studies have controlled for age-specific effects by adding separate smoothing functions for each age group. However, it has not yet been reported whether air pollution effects are significantly different for different age groups. This lack of information is the motivation for this study, which tests the hypothesis that air pollution effects on asthmatic hospital admissions are significantly different by age groups. Each air pollutant's effect on asthmatic hospital admissions by age groups was estimated separately. In this study, daily time-series data for hospital admission rates from seven cities in Korea from June 1999 through 2003 were analyzed. The outcome variable, daily hospital admission rates for asthma, was related to five air pollutants which were used as the independent variables, namely particulate matter <10 micrometers (μm) in aerodynamic diameter (PM10), carbon monoxide (CO), ozone (O3), nitrogen dioxide (NO2), and sulfur dioxide (SO2). Meteorological variables were considered as confounders. Admission data were divided into three age groups: children (<15 years of age), adults (ages 15-64), and elderly (≥ 65 years of age). The adult age group was considered to be the reference group for each city. In order to estimate age-specific air pollution effects, the analysis was separated into two stages. In the first stage, Generalized Additive Models (GAMs) with cubic spline for smoothing were applied to estimate the age-city-specific air pollution effects on asthmatic hospital admission rates by city and age group. In the second stage, the Bayesian Hierarchical Model with non-informative prior which has large variance was used to combine city-specific effects by age groups. The hypothesis test showed that the effects of PM10, CO and NO2 were significantly different by age groups. Assuming that the air pollution effect for adults is zero as a reference, age-specific air pollution effects were: -0.00154 (95% confidence interval(CI)= (-0.0030,-0.0001)) for children and 0.00126 (95% CI = (0.0006, 0.0019)) for the elderly for PM 10; -0.0195 (95% CI = (-0.0386,-0.0004)) for children for CO; and 0.00494 (95% CI = (0.0028, 0.0071)) for the elderly for NO2. Relative rates (RRs) were 1.008 (95% CI = (1.000-1.017)) in adults and 1.021 (95% CI = (1.012-1.030)) in the elderly for every 10 μg/m3 increase of PM10 , 1.019 (95% CI = (1.005-1.033)) in adults and 1.022 (95% CI = (1.012-1.033)) in the elderly for every 0.1 part per million (ppm) increase of CO; 1.006 (95%CI = (1.002-1.009)) and 1.019 (95%CI = (1.007-1.032)) in the elderly for every 1 part per billion (ppb) increase of NO2 and SO2, respectively. Asthma hospital admissions were significantly increased for PM10 and CO in adults, and for PM10, CO, NO2 and SO2 in the elderly.^