Spatial impact of isolation distances between parcels of GM and non-GM maize.
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Biomedical subjects
Publications and source records attributed to Olivier Thas.
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BACKGROUND: This study investigates the accuracy of a composite index, the A-Line(R) auditory evoked potentials index version 1.6 (AAI1.6; Danmeter A/S, Odense, Denmark), as a measure of cerebral anesthetic drug effect in a model for predicting a calculated effect site concentration of propofol (CePROP). The AAI1.6 algorithm extracts information from the midlatency auditory evoked potentials, the spontaneous electroencephalographic activity, and the detection of burst suppression. The former version of this monitor, the A-Line auditory evoked potential index version 1.5, is only based on fast extracted midlatency auditory evoked potential information. METHODS: After institutional ethics committee approval (University Hospital, Ghent, Belgium), informed consent was obtained from 13 patients (10 women, 3 men) with an American Society of Anesthesiologists physical status of I, aged 18-65 yr, who were scheduled to undergo ambulatory gynecologic or urologic surgery. The authors evaluated for Bispectral Index, A-Line auditory evoked potential index, version 1.5, AAI1.6 scaled from 0 to 100 and AAI1.6 scaled from 0 to 60, the interpatient stability at baseline, the detection of burst suppression, prediction probability, and correlation with CePROP, during a constant infusion of 1% propofol at 300 ml/h. The authors developed pharmacodynamic models relating the predicted CePROP to each measure of cerebral anesthetic drug effect. RESULTS: Bispectral Index had the lowest interindividual baseline variability. No significant difference was found with prediction probability analysis for all measures. Comparisons for correlation were performed for all indices. The AAI1.6 scaled to 60 had a significantly higher correlation with CePROP compared with all other measures. The AAI1.6 scaled to 100 had a significant higher correlation with CePROP compared with the A-Line auditory evoked potential index version 1.5 (P < 0.05) CONCLUSIONS: The authors found that the application of AAI1.6 has a better correlation with a calculated CePROP compared with a solitary fast extracting midlatency auditory evoked potential measure. Whether this improvement in pharmacodynamic tracing is accompanied by an improved clinical performance should be investigated using clinical endpoints.
In this article we construct three smooth goodness-of-fit tests for testing for the zero-inflated Poisson (ZIP) distribution against general smooth alternatives in the sense of Neyman. We apply our tests to a data set previously claimed to be ZIP distributed, and show that the ZIP is not a good model to describe the data. At rejection of the null hypothesis of ZIP, the individual components of the test statistic, which are directly related to interpretable parameters in a smooth model, may be used to gain insight into an alternative distribution.
BACKGROUND: The authors compared the behavior of two calculations of electroencephalographic spectral entropy, state entropy (SE) and response entropy (RE), with the A-Line ARX Index (AAI) and the Bispectral Index (BIS) and as measures of anesthetic drug effect. They compared the measures for baseline variability, burst suppression, and prediction probability. They also developed pharmacodynamic models relating SE, RE, AAI, and BIS to the calculated propofol effect-site concentration (Ceprop). METHODS: With institutional review board approval, the authors studied 10 patients. All patients received 50 mg/min propofol until either burst suppression greater than 80% or mean arterial pressure less than 50 mmHg was observed. SE, RE, AAI, and BIS were continuously recorded. Ceprop was calculated from the propofol infusion profile. Baseline variability, prediction of burst suppression, prediction probability, and Spearman rank correlation were calculated for SE, RE, AAI, and BIS. The relations between Ceprop and the electroencephalographic measures of drug effect were estimated using nonlinear mixed effect modeling. RESULTS: Baseline variability was lowest when using SE and RE. Burst suppression was most accurately detected by spectral entropy. Prediction probability and individualized Spearman rank correlation were highest for BIS and lowest for SE. Nonlinear mixed effect modeling generated reasonable models relating all four measures to Ceprop. CONCLUSIONS: Compared with BIS and AAI, both SE and RE seem to be useful electroencephalographic measures of anesthetic drug effect, with low baseline variability and accurate burst suppression prediction. The ability of the measures to predict Ceprop was best for BIS.
Concentrations of 27 priority volatile organic compounds were measured in water samples of the North Sea and Scheldt estuary during a 3-year monitoring study. Despite the use of a sensitive analytical method, a number of data were censored. That is, some concentrations were below the decision limit or critical level defined by IUPAC. To characterize the observed measurement results, an attempt was made to identify an appropriate procedure to compute summary statistics for the censored data sets. Several parametric and robust parametric approaches based on the maximum likelihood principle and probability-plot regression method were evaluated for the estimation of the mean, standard deviation, median and interquartile range using three uncensored analytes (1,1,2-trichloroethane, tetrachloroethene and o-xylene) from the monitoring survey. Performance was assessed by artificially censoring the observed concentrations and estimating moments and quantiles at each censoring level. Results showed that methods with the least distributional assumptions, such as the robust bias-corrected restricted maximum likelihood method, perform best for estimating the mean and standard deviation, while both parametric and robust parametric techniques can be used for quantiles. Hence, summary statistics could be estimated with little bias (5-10%) up to 80% of censoring for the data sets employed in this study.