Early identification of leptospirosis-associated pulmonary hemorrhage syndrome by use of a validated prediction model

Objective: To identify prediction factors for the development of leptospirosis-associated pulmonary hemorrhage syndrome (LPHS). Methods: We conducted a prospective cohort study. The study comprised of 203 patients, aged >= 14 years, admitted with complications of the severe form of leptospirosis at the Emilio Ribas Institute of Infectology (Sao Paulo, Brazil) between 1998 and 2004. Laboratory and demographic data were obtained and the severity of illness score and involvement of the lungs and others organs were determined. Logistic regression was performed to identify independent predictors of LPHS. A prospective validation cohort of 97 subjects with severe form of leptospirosis admitted at the same hospital between 2004 and 2006 was used to independently evaluate the predictive value of the model. Results: The overall mortality rate was 7.9%. Multivariate logistic regression revealed that five factors were independently associated with the development of LPHS: serum potassium (mmol/L) (OR = 2.6; 95% CI = 1.1-5.9); serum creatinine (mmol/L) (OR = 1.2; 95% CI = 1.1-1.4); respiratory rate (breaths/min) (OR = 1.1; 95% CI = 1.1-1.2); presenting shock (OR = 69.9; 95% CI = 20.1-236.4), and Glasgow Coma Scale Score (GCS) < 15 (OR = 7.7; 95% CI = 1.3-23.0). We used these findings to calculate the risk of LPHS by the use of a spreadsheet. In the validation cohort, the equation classified correctly 92% of patients (Kappa statistic = 0.80). Conclusions: We developed and validated a multivariate model for predicting LPHS. This tool should prove useful in identifying LPHS patients, allowing earlier management and thereby reducing mortality. (C) 2009 The British Infection Society. Published by Elsevier Ltd. All rights reserved.

Long-term survivor mixture model with random effects: application to a multi-centre clinical trial of carcinoma

A mixture model incorporating long-term survivors has been adopted in the field of biostatistics where some individuals may never experience the failure event under study. The surviving fractions may be considered as cured. In most applications, the survival times are assumed to be independent. However, when the survival data are obtained from a multi-centre clinical trial, it is conceived that the environ mental conditions and facilities shared within clinic affects the proportion cured as well as the failure risk for the uncured individuals. It necessitates a long-term survivor mixture model with random effects. In this paper, the long-term survivor mixture model is extended for the analysis of multivariate failure time data using the generalized linear mixed model (GLMM) approach. The proposed model is applied to analyse a numerical data set from a multi-centre clinical trial of carcinoma as an illustration. Some simulation experiments are performed to assess the applicability of the model based on the average biases of the estimates formed. Copyright (C) 2001 John Wiley & Sons, Ltd.

A dynamic model with on-line identification for rotary sugar drying processes

A dynamic modelling methodology, which combines on-line variable estimation and parameter identification with physical laws to form an adaptive model for rotary sugar drying processes, is developed in this paper. In contrast to the conventional rate-based models using empirical transfer coefficients, the heat and mass transfer rates are estimated by using on-line measurements in the new model. Furthermore, a set of improved sectional solid transport equations with localized parameters is developed in this work to reidentified on-line using measurement data, the model is able to closely track the dynamic behaviour of rotary drying processes within a broad range of operational conditions. This adaptive model is validated against experimental data obtained from a pilot-scale rotary sugar dryer. The proposed modelling methodology can be easily incorporated into nonlinear model based control schemes to form a unified modelling and control framework.place the global correlation for the computation of solid retention time. Since a number of key model variables and parameters are identified on-line using measurement data, the model is able to closely track the dynamic behaviour of rotary drying processes within a broad range of operational conditions. This adaptive model is validated against experimental data obtained from a pilot-scale rotary sugar dryer. The proposed modelling methodology can be easily incorporated into nonlinear model based control schemes to form a unified modelling and control framework.

Assessment of body composition by bioelectrical impedance analysis without the need for measurement of height

Conventional whole-body single frequency bioelectrical impedance analysis (BIA) of body composition typically uses height as a surrogate measure of conductor length. A new method of BIA analysis for the prediction of body cell mass (BCM) and extracellular water (ECW, as % body weight) not using height has been introduced-the Soft Tissue Analyser (STA(TM), Akern Sri, Florence, Italy)-making it ideal for use in subjects where measurement of height is difficult or impossible. The performance of the new analytical method in predicting BCM and ECW in 139 normal control subjects was assessed by comparison with reference data obtained from a four-component (4-C) model of body composition and with predictions obtained from conventional BIA analysis. Both predicted BCM and ECW were strongly (r = 0.82, SEE = 6.3 kg and 0.89, SEE = 1.3 kg respectively) correlated with the corresponding 4-C model measurements although differing significantly from the lines of identity (P < 0.0001). Fat-free mass, calculated from STA estimates of BCM and ECW, was better predicted (r = 0.91, SEE = 5.6 kg). The significant differences in STA-group mean values for BCM and ECW and wide limits of agreement compared with the reference data indicate that the method cannot be used with confidence for prediction of these body compartments despite the obvious advantage of not requiring an accurate measurement of height. (C) 2001 Harcourt Publishers Ltd.

Continuous quantum measurement of two coupled quantum dots using a point contact: A quantum trajectory approach

We obtain the finite-temperature unconditional master equation of the density matrix for two coupled quantum dots (CQD's) when one dot is subjected to a measurement of its electron occupation number using a point contact (PC). To determine how the CQD system state depends on the actual current through the PC device, we use the so-called quantum trajectory method to derive the zero-temperature conditional master equation. We first treat the electron tunneling through the PC barrier as a classical stochastic point process (a quantum-jump model). Then we show explicitly that our results can be extended to the quantum-diffusive limit when the average electron tunneling rate is very large compared to the extra change of the tunneling rate due to the presence of the electron in the dot closer to the PC. We find that in both quantum-jump and quantum-diffusive cases, the conditional dynamics of the CQD system can be described by the stochastic Schrodinger equations for its conditioned state vector if and only if the information carried away from the CQD system by the PC reservoirs can be recovered by the perfect detection of the measurements.

MRI based diffusion and perfusion predictive model to estimate stroke evolution

In this study we present a novel automated strategy for predicting infarct evolution, based on MR diffusion and perfusion images acquired in the acute stage of stroke. The validity of this methodology was tested on novel patient data including data acquired from an independent stroke clinic. Regions-of-interest (ROIs) defining the initial diffusion lesion and tissue with abnormal hemodynamic function as defined by the mean transit time (MTT) abnormality were automatically extracted from DWI/PI maps. Quantitative measures of cerebral blood flow (CBF) and volume (CBV) along with ratio measures defined relative to the contralateral hemisphere (r(a)CBF and r(a)CBV) were calculated for the MTT ROIs. A parametric normal classifier algorithm incorporating these measures was used to predict infarct growth. The mean r(a)CBF and r(a)CBV values for eventually infarcted MTT tissue were 0.70 +/-0.19 and 1.20 +/-0.36. For recovered tissue the mean values were 0.99 +/-0.25 and 1.87 +/-0.71, respectively. There was a significant difference between these two regions for both measures (P

Analysis of the gate capacitance measurement technique and its application for the evaluation of hot-carrier degradation in submicrometer MOSFETs

The use of gate-to-drain capacitance (C-gd) measurement as a tool to characterize hot-carrier-induced charge centers in submicron n- and p-MOSFET's has been reviewed and demonstrated. By analyzing the change in C-gd measured at room and cryogenic temperature before and after high gate-to-drain transverse field (high field) and maximum substrate current (I-bmax) stress, it is concluded that the degradation was found to be mostly due to trapping of majority carriers and generation of interface states. These interface states were found to be acceptor states at top half of band gap for n-MOSFETs and donor states at bottom half of band gap for p-MOSFETs. In general, hot electrons are more likely to be trapped in gate oxide as compared to hot holes while the presence of hot holes generates more interface states. Also, we have demonstrated a new method for extracting the spatial distribution of oxide trapped charge, Q(ot), through gate-to-substrate capacitance (C-gb) measurement. This method is simple to implement and does not require additional information from simulation or detailed knowledge of the device's structure. (C) 2001 Elsevier Science Ltd. All rights reserved.

Maximum Likelihood Estimation of Mixture Densities for Binned and Truncated Multivariate Data

Binning and truncation of data are common in data analysis and machine learning. This paper addresses the problem of fitting mixture densities to multivariate binned and truncated data. The EM approach proposed by McLachlan and Jones (Biometrics, 44: 2, 571-578, 1988) for the univariate case is generalized to multivariate measurements. The multivariate solution requires the evaluation of multidimensional integrals over each bin at each iteration of the EM procedure. Naive implementation of the procedure can lead to computationally inefficient results. To reduce the computational cost a number of straightforward numerical techniques are proposed. Results on simulated data indicate that the proposed methods can achieve significant computational gains with no loss in the accuracy of the final parameter estimates. Furthermore, experimental results suggest that with a sufficient number of bins and data points it is possible to estimate the true underlying density almost as well as if the data were not binned. The paper concludes with a brief description of an application of this approach to diagnosis of iron deficiency anemia, in the context of binned and truncated bivariate measurements of volume and hemoglobin concentration from an individual's red blood cells.

Simulation of interface states effect on the scanning capacitance microscopy measurement of p-n junctions

A two-dimensional numerical simulation model of interface states in scanning capacitance microscopy (SCM) measurements of p-n junctions is presented-In the model, amphoteric interface states with two transition energies in the Si band gap are represented as fixed charges to account for their behavior in SCM measurements. The interface states are shown to cause a stretch-out-and a parallel shift of the capacitance-voltage characteristics in the depletion. and neutral regions of p-n junctions, respectively. This explains the discrepancy between - the SCM measurement and simulation near p-n junctions, and thus modeling interface states is crucial for SCM dopant profiling of p-n junctions. (C) 2002 American Institute of Physics.

MR image-based measurement of rates of change in volumes of brain structures. Part 1: Method and validation

A detailed analysis procedure is described for evaluating rates of volumetric change in brain structures based on structural magnetic resonance (MR) images. In this procedure, a series of image processing tools have been employed to address the problems encountered in measuring rates of change based on structural MR images. These tools include an algorithm for intensity non-uniforniity correction, a robust algorithm for three-dimensional image registration with sub-voxel precision and an algorithm for brain tissue segmentation. However, a unique feature in the procedure is the use of a fractional volume model that has been developed to provide a quantitative measure for the partial volume effect. With this model, the fractional constituent tissue volumes are evaluated for voxels at the tissue boundary that manifest partial volume effect, thus allowing tissue boundaries be defined at a sub-voxel level and in an automated fashion. Validation studies are presented on key algorithms including segmentation and registration. An overall assessment of the method is provided through the evaluation of the rates of brain atrophy in a group of normal elderly subjects for which the rate of brain atrophy due to normal aging is predictably small. An application of the method is given in Part 11 where the rates of brain atrophy in various brain regions are studied in relation to normal aging and Alzheimer's disease. (C) 2002 Elsevier Science Inc. All rights reserved.

Motor and functional skills of children with developmental coordination disorder: A pilot investigation of measurement issues

This paper reports on the motor and functional outcomes of 20 children with developmental coordination disorder (DCD) aged 4-8 years consecutively referred to a pediatric physiotherapy service. Children with a Movement ABC (M-ABC) score less than the 15th percentile, and with no concurrent medical, sensory, physical, intellectual or neurological impairments, were recruited. The Motor Assessment Outcomes Model (MAOM) [Coster and Haley, Infants and Young Children 4 (1992) 11] provided the theoretical base for measurement selection, and preliminary findings at the activities and participation levels of the model are reported in this article. Children with DCD performed at the lower end of the normal range on the Pea-body Developmental Motor Scales (fine motor total score) (M = 85.65, SD = 12.23). Performance on the Visual Motor Integration Test (VMI) standard scores was within the average range (M = 96.15, SD = 10.69). Videotaped observations of the children's writing and cutting indicated that 29% were left-handed and that a large proportion of all children (31%) utilized unusual pencil grasp patterns and immature prehension of scissors. Measurement at the participation level involved use of the Pictorial Scale of Perceived Competence and Social Acceptance (PCSA) and Pediatric Evaluation of Disability Inventory (PEDI). Overall, these young children rated themselves towards the more competent and accepted end of the PCSA over the dimensions of physical and cognitive competence and peer and maternal acceptance. The PEDI revealed generally average performance on social (M = 49.98, SD = 16.62) and mobility function (M = 54.71, SD = 3.99), however, self-care function was below the average range for age (M = 38.01, SD = 12.19). The utility of the MAOM as a framework for comprehensive measurement of functional and motor outcomes of DCD in young children is discussed. (C) 2003 Elsevier B.V. All rights reserved.

Impulse-response function of splanchnic circulation with model-independent constraints: theory and experimental validation

Modeling physiological processes using tracer kinetic methods requires knowledge of the time course of the tracer concentration in blood supplying the organ. For liver studies, however, inaccessibility of the portal vein makes direct measurement of the hepatic dual-input function impossible in humans. We want to develop a method to predict the portal venous time-activity curve from measurements of an arterial time-activity curve. An impulse-response function based on a continuous distribution of washout constants is developed and validated for the gut. Experiments with simultaneous blood sampling in aorta and portal vein were made in 13 anesthetized pigs following inhalation of intravascular [O-15] CO or injections of diffusible 3-O[ C-11] methylglucose (MG). The parameters of the impulse-response function have a physiological interpretation in terms of the distribution of washout constants and are mathematically equivalent to the mean transit time ( T) and standard deviation of transit times. The results include estimates of mean transit times from the aorta to the portal vein in pigs: (T) over bar = 0.35 +/- 0.05 min for CO and 1.7 +/- 0.1 min for MG. The prediction of the portal venous time-activity curve benefits from constraining the regression fits by parameters estimated independently. This is strong evidence for the physiological relevance of the impulse-response function, which includes asymptotically, and thereby justifies kinetically, a useful and simple power law. Similarity between our parameter estimates in pigs and parameter estimates in normal humans suggests that the proposed model can be adapted for use in humans.

A model to investigate hepatic extraction of oxygen during anaesthesia in the dog

Measurement of hepatic oxygen extraction was performed on six healthy Greyhound dogs over a two hour period. The Greyhounds were anaesthetised and a right subcostal surgical incision performed. Ultrasonic flow transducers were used to measure flow rate in the hepatic artery and the portal vein. The blood oxygen tensions in arterial blood and in the portal and hepatic veins were also measured. Hepatic oxygen extraction remained stable throughout the study, despite a steady decline in arterial blood pressure. The methodology described in this study provides a direct measure of oxygen uptake by the liver in the dog and could readily be used to investigate hepatic uptake of drugs. (C) 2003 Elsevier Ltd. All rights reserved.

Model-based analysis of anaerobic acetate uptake by a mixed culture of polyphosphate-accumulating and glycogen-accumulating organisms

An increasing number of studies shows that the glycogen-accumulating organisms (GAOs) can survive and may indeed proliferate under the alternating anaerobic/aerobic conditions found in EBPR systems, thus forming a strong competitor of the polyphosphate-accumulating organisms (PAOs). Understanding their behaviors in a mixed PAO and GAO culture under various operational conditions is essential for developing operating strategies that disadvantage the growth of this group of unwanted organisms. A model-based data analysis method is developed in this paper for the study of the anaerobic PAO and GAO activities in a mixed PAO and GAO culture. The method primarily makes use of the hydrogen ion production rate and the carbon dioxide transfer rate resulting from the acetate uptake processes by PAOs and GAOs, measured with a recently developed titration and off-gas analysis (TOGA) sensor. The method is demonstrated using the data from a laboratory-scale sequencing batch reactor (SBR) operated under alternating anaerobic and aerobic conditions. The data analysis using the proposed method strongly indicates a coexistence of PAOs and GAOs in the system, which was independently confirmed by fluorescent in situ hybridization (FISH) measurement. The model-based analysis also allowed the identification of the respective acetate uptake rates by PAOs and GAOs, along with a number of kinetic and stoichiometric parameters involved in the PAO and GAO models. The excellent fit between the model predictions and the experimental data not involved in parameter identification shows that the parameter values found are reliable and accurate. It also demonstrates that the current anaerobic PAO and GAO models are able to accurately characterize the PAO/GAO mixed culture obtained in this study. This is of major importance as no pure culture of either PAOs or GAOs has been reported to date, and hence the current PAO and GAO models were developed for the interpretation of experimental results of mixed cultures. The proposed method is readily applicable for detailed investigations of the competition between PAOs and GAOs in enriched cultures. However, the fermentation of organic substrates carried out by ordinary heterotrophs needs to be accounted for when the method is applied to the study of PAO and GAO competition in full-scale sludges. (C) 2003 Wiley Periodicals, Inc.