845 resultados para Interval Variable
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BACKGROUND: Periodontitis has been identified as a potential risk factor in cardiovascular diseases. It is possible that the stimulation of host responses to oral infections may result in vascular damage and the inducement of blood clotting. The aim of this study was to assess the role of periodontal infection and bacterial burden as an explanatory variable to the activation of the inflammatory process leading to acute coronary syndrome (ACS). METHODS: A total of 161 consecutive surviving cases admitted with a diagnosis of ACS and 161 control subjects, matched with cases according to their gender, socioeconomic level, and smoking status, were studied. Serum white blood cell (WBC) counts, high- and low-density lipoprotein (HDL/LDL) levels, high-sensitivity C-reactive protein (hsC-rp) levels, and clinical periodontal routine parameters were studied. The subgingival pathogens were assayed by the checkerboard DNA-DNA hybridization method. RESULTS: Total oral bacterial load was higher in the subjects with ACS (mean difference: 17.4x10(5); SD: 10.8; 95% confidence interval [CI]: 4.2 to 17.4; P<0.001), and significant for 26 of 40 species including Porphyromonas gingivalis, Tannerella forsythensis, and Treponema denticola. Serum WBC counts, hsC-rp levels, Streptococcus intermedius, and Streptococcus sanguis, were explanatory factors to acute coronary syndrome status (Nagelkerke r2=0.49). CONCLUSION: The oral bacterial load of S. intermedius, S. sanguis, Streptococcus anginosus, T. forsythensis, T. denticola, and P. gingivalis may be concomitant risk factors in the development of ACS.
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The construction of a reliable, practically useful prediction rule for future response is heavily dependent on the "adequacy" of the fitted regression model. In this article, we consider the absolute prediction error, the expected value of the absolute difference between the future and predicted responses, as the model evaluation criterion. This prediction error is easier to interpret than the average squared error and is equivalent to the mis-classification error for the binary outcome. We show that the distributions of the apparent error and its cross-validation counterparts are approximately normal even under a misspecified fitted model. When the prediction rule is "unsmooth", the variance of the above normal distribution can be estimated well via a perturbation-resampling method. We also show how to approximate the distribution of the difference of the estimated prediction errors from two competing models. With two real examples, we demonstrate that the resulting interval estimates for prediction errors provide much more information about model adequacy than the point estimates alone.
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This paper introduces a novel approach to making inference about the regression parameters in the accelerated failure time (AFT) model for current status and interval censored data. The estimator is constructed by inverting a Wald type test for testing a null proportional hazards model. A numerically efficient Markov chain Monte Carlo (MCMC) based resampling method is proposed to simultaneously obtain the point estimator and a consistent estimator of its variance-covariance matrix. We illustrate our approach with interval censored data sets from two clinical studies. Extensive numerical studies are conducted to evaluate the finite sample performance of the new estimators.
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Traffic particle concentrations show considerable spatial variability within a metropolitan area. We consider latent variable semiparametric regression models for modeling the spatial and temporal variability of black carbon and elemental carbon concentrations in the greater Boston area. Measurements of these pollutants, which are markers of traffic particles, were obtained from several individual exposure studies conducted at specific household locations as well as 15 ambient monitoring sites in the city. The models allow for both flexible, nonlinear effects of covariates and for unexplained spatial and temporal variability in exposure. In addition, the different individual exposure studies recorded different surrogates of traffic particles, with some recording only outdoor concentrations of black or elemental carbon, some recording indoor concentrations of black carbon, and others recording both indoor and outdoor concentrations of black carbon. A joint model for outdoor and indoor exposure that specifies a spatially varying latent variable provides greater spatial coverage in the area of interest. We propose a penalised spline formation of the model that relates to generalised kringing of the latent traffic pollution variable and leads to a natural Bayesian Markov Chain Monte Carlo algorithm for model fitting. We propose methods that allow us to control the degress of freedom of the smoother in a Bayesian framework. Finally, we present results from an analysis that applies the model to data from summer and winter separately
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The purpose of this study is to develop statistical methodology to facilitate indirect estimation of the concentration of antiretroviral drugs and viral loads in the prostate gland and the seminal vesicle. The differences in antiretroviral drug concentrations in these organs may lead to suboptimal concentrations in one gland compared to the other. Suboptimal levels of the antiretroviral drugs will not be able to fully suppress the virus in that gland, lead to a source of sexually transmissible virus and increase the chance of selecting for drug resistant virus. This information may be useful selecting antiretroviral drug regimen that will achieve optimal concentrations in most of male genital tract glands. Using fractionally collected semen ejaculates, Lundquist (1949) measured levels of surrogate markers in each fraction that are uniquely produced by specific male accessory glands. To determine the original glandular concentrations of the surrogate markers, Lundquist solved a simultaneous series of linear equations. This method has several limitations. In particular, it does not yield a unique solution, it does not address measurement error, and it disregards inter-subject variability in the parameters. To cope with these limitations, we developed a mechanistic latent variable model based on the physiology of the male genital tract and surrogate markers. We employ a Bayesian approach and perform a sensitivity analysis with regard to the distributional assumptions on the random effects and priors. The model and Bayesian approach is validated on experimental data where the concentration of a drug should be (biologically) differentially distributed between the two glands. In this example, the Bayesian model-based conclusions are found to be robust to model specification and this hierarchical approach leads to more scientifically valid conclusions than the original methodology. In particular, unlike existing methods, the proposed model based approach was not affected by a common form of outliers.
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In medical follow-up studies, ordered bivariate survival data are frequently encountered when bivariate failure events are used as the outcomes to identify the progression of a disease. In cancer studies interest could be focused on bivariate failure times, for example, time from birth to cancer onset and time from cancer onset to death. This paper considers a sampling scheme where the first failure event (cancer onset) is identified within a calendar time interval, the time of the initiating event (birth) can be retrospectively confirmed, and the occurrence of the second event (death) is observed sub ject to right censoring. To analyze this type of bivariate failure time data, it is important to recognize the presence of bias arising due to interval sampling. In this paper, nonparametric and semiparametric methods are developed to analyze the bivariate survival data with interval sampling under stationary and semi-stationary conditions. Numerical studies demonstrate the proposed estimating approaches perform well with practical sample sizes in different simulated models. We apply the proposed methods to SEER ovarian cancer registry data for illustration of the methods and theory.
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PURPOSE: To characterize the phenotype and map the locus responsible for autosomal recessive inherited ovine microphthalmia (OMO) in sheep. METHODS: Microphthalmia-affected lambs and their available relatives were collected in a field, and experimental matings were performed to obtain affected and normal lambs for detailed necropsy and histologic examinations. The matings resulted in 18 sheep families with 48 cases of microphthalmia. A comparative candidate gene approach was used to map the disease locus within the sheep genome. Initially, 27 loci responsible for the microphthalmia-anophthalmia phenotypes in humans or mice were selected to test for comparative linkage. Fifty flanking markers that were predicted from comparative genomic analysis to be closely linked to these genes were tested for linkage to the disease locus. After observation of statistical evidence for linkage, a confirmatory fine mapping strategy was applied by further genotyping of 43 microsatellites. RESULTS: The clinical and pathologic examinations showed slightly variable expressivity of isolated bilateral microphthalmia. The anterior eye chamber was small or absent, and a white mass admixed with cystic spaces extended from the papilla to the anterior eye chamber, while no recognizable vitreous body or lens was found within the affected eyes. Significant linkage to a single candidate region was identified at sheep chromosome 23. Fine mapping and haplotype analysis assigned the candidate region to a critical interval of 12.4 cM. This ovine chromosome segment encompasses an ancestral chromosomal breakpoint corresponding to two orthologue segments of human chromosomes 18, short and long arms. For the examined animals, we excluded the complete coding region and adjacent intronic regions of ovine TGIF1 to harbor disease-causing mutations. CONCLUSIONS: This is the first genetic localization for hereditary ovine isolated microphthalmia. It seems unlikely that a mutation in the TGIF1 gene is responsible for this disorder. The studied sheep represent a valuable large animal model for similar human ocular phenotypes.
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BACKGROUND AND AIMS: There are few standardised questionnaires for the assessment of respiratory symptoms in preschool children. We have developed and tested the short-term repeatability of a postal questionnaire on respiratory symptoms for 1-year-old children. METHODS: A newly developed postal questionnaire for the assessment of wheeze and other respiratory symptoms was sent to parents of a population-based random sample of 4300 children aged 12-24 months. After an interval of 3 months, a random sample of 800 respondents received the questionnaire a second time. The responses were compared using Cohen's kappa (kappa) to assess agreement corrected for chance. RESULTS: The first questionnaire was returned by 3194 (74%) families, the second one by 460/800 (58%). Repeatability was excellent (kappa 0.80-0.96) for questions on household characteristics, environmental exposures and family history, good (kappa 0.61-0.80) for questions on prevalence, severity and treatment of wheeze, and moderate (kappa 0.39-0.66) for chronic cough and upper respiratory symptoms. CONCLUSIONS: This short postal questionnaire designed for use in population-based studies has excellent repeatability for family and household characteristics and good repeatability for questions on wheeze. Short-term changes in symptom status might be responsible for variable answers on recent chronic cough and upper respiratory symptoms. Overall, the questionnaire is a valuable instrument for community-based research on respiratory symptoms in 1 to 2-year-old children.
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We describe the case of a 16-year-old woman with a surgically corrected tetralogy of Fallot presenting with recurrent wide-QRS-complex tachycardia. The tachycardia could be induced and terminated with ventricular stimulation only. QRS morphology during sinus rhythm and tachycardia was identical and variable VA-conduction was observed. Mapping of the tachycardia showed that variations of HH intervals preceded VV intervals. Therefore, a mechanism involving re-entry within the bundle branches was suggested. However, detailed mapping showed cranial to caudal depolarization of the His bundle, leading to the diagnosis of atrioventricular node re-entrant tachycardia. The tachycardia was abolished by radiofrequency catheter ablation of the slow AV nodal pathway. We conclude that variable VA conduction can occur in patients with atrioventricular node re-entrant tachycardia. The atrial tissue is not always an integral part of the re-entrant circuit.
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The 1s-2s interval has been measured in the muonium (;mgr;(+)e(-)) atom by Doppler-free two-photon pulsed laser spectroscopy. The frequency separation of the states was determined to be 2 455 528 941.0(9.8) MHz, in good agreement with quantum electrodynamics. The result may be interpreted as a measurement of the muon-electron charge ratio as -1-1.1(2.1)x10(-9). We expect significantly higher accuracy at future high flux muon sources and from cw laser technology.
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OBJECTIVES: In patients with a clinically isolated syndrome (CIS), the time interval to convert to clinically definite multiple sclerosis (CDMS) is highly variable. Individual and geographical prognostic factors remain to be determined. Whether anti-myelin antibodies may predict the risk of conversion to CDMS in Swiss CIS patients of the canton Berne was the subject of the study. METHODS: Anti-myelin oligodendrocyte glycoprotein and anti-myelin basic protein antibodies were determined prospectively in patients admitted to our department. RESULTS: After a mean follow-up of 12 months, none of nine antibody-negative, but 22 of 30 antibody-positive patients had progressed to CDMS. Beta-Interferon treatment delayed the time to conversion from a mean of 7.4 to 10.9 months. CONCLUSIONS: In a Swiss cohort, antibody-negative CIS patients have a favorable short-term prognosis, and antibody-positive patients benefit from early treatment.
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PURPOSE: The clinical role of CAD systems to detect breast cancer, which have not been on cancer containing mammograms not detected by the radiologist was proven retrospectively. METHODS: All patients from 1992 to 2005 with a histologically verified malignant breast lesion and a mammogram at our department, were analyzed in retrospect focussing on the time of detection of the malignant lesion. All prior mammograms were analyzed by CAD (CADx, USA). The resulting CAD printout was matched with the cancer containing images yielding to the radiological diagnosis of breast cancer. CAD performance, sensitivity as well as the association of CAD and radiological features were analyzed. RESULTS: 278 mammograms fulfilled the inclusion criteria. 111 cases showed a retrospectively visible lesion (71 masses, 23 single microcalcification clusters, 16 masses with microcalcifications, in one case two microcalcification clusters). 54/87 masses and 34/41 microcalcifications were detected by CAD. Detection rates varied from 9/20 (ACR 1) to 5/7 (ACR 4) (45% vs. 71%). The detection of microcalcifications was not influenced by breast tissue density. CONCLUSION: CAD might be useful in an earlier detection of subtle breast cancer cases, which might remain otherwise undetected.