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Background: Despite the known impact of propofol and remifentanil on hemodynamics and patient outcomes, there is a lack of comprehensive quantitative analysis, particularly in surgical settings, considering the influence of noxious stimuli. The aim of this study was to develop a quantitative semi-mechanistic population model that characterized the time course changes in mean arterial pressure (MAP) and heart rate (HR) due to the effects of propofol, remifentanil, and different types of noxious stimulation related to the clinical routine. Methods: Data from a prospective study were used; the study analyzed the effects of propofol and remifentanil general anesthesia on female patients in physical status of I-II according to the American Society of Anesthesiologists (ASA I-II) undergoing gynecology surgery. Patients were consecutively assigned to different administration schemes of propofol and remifentanil targeted at different effect-site concentrations. Esophageal instrumentation, laryngeal mask airway insertion, hysteroscopy, and tetanus stimuli were applied. Data from patients with chronic hypertension were discarded. Results: MAP and HR observations from 77 patients were analyzed. The hemodynamic effects were described using turn-over models incorporating feedback mechanisms. Analyses revealed that propofol and remifentanil elicited effects on the turn-over of MAP and HR, respectively, with estimates of plasma drug concentrations causing an inhibition-half of the maximum effect (C50) of 8.79 µg∙mL−1 and 4.57 ng∙mL−1. Hysteroscopy exerted an increase in MAP (but not in HR), which was well-characterized by the model, with a predicted typical increase of 28 mmHg and a dissipation half-life of 33 min. The impact of other noxious stimuli on MAP or HR could not be identified. Model simulations indicated that propofol and remifentanil, titrated to inhibit the motor response to noxious stimuli, regardless of dose combinations, cause a significant risk of hypotension, especially following induction and at the end of surgery (when surgical intervention is completed, before the awakening phase). Conclusions: The developed semi-mechanistic and fully identifiable model provides quantitative information on how propofol, remifentanil, and surgical stimulus (hysteroscopy) interact to produce the hemodynamic changes (of MAP and HR) commonly observed in clinical practice.

Abstract Intraoperative targeting of the analgesic effect still lacks an optimal solution. Opioids are currently the main drug used to achieve antinociception, and although underdosing can lead to an increased stress response, overdose can also lead to undesirable adverse effects. To better understand how to achieve the optimal analgesic effect of opioids, we studied the influence of remifentanil on the pupillary reflex dilation (PRD) and its relationship with the reflex movement response to a standardized noxious stimulus. The main objective was to generate population pharmacodynamic models relating remifentanil predicted concentrations to movement and to pupillary dilation during general anesthesia. A total of 78 patients undergoing gynecological surgery under general anesthesia were recruited for the study. PRD and movement response to a tetanic stimulus were measured multiple times before and after surgery. We used nonlinear mixed effects modeling to generate a population pharmacodynamic model to describe both the time profiles of PRD and movement responses to noxious stimulation. Our model demonstrated that movement and PRD are equally depressed by remifentanil. Using the developed model, we changed the intensity of stimulation and simulated remifentanil predicted concentrations maximizing the probability of absence of movement response. An estimated effect site concentration of 2 ng/ml of remifentanil was found to inhibit movement to a tetanic stimulation with a probability of 81%.

The influence of private self-consciousness on the components of Ajzen and Fishbein's attitude model (attitude and subjective norm) is analysed. The impact of past behaviour on both current behaviour and behavioural intention is also studied. This model was applied to the prediction of voting intention and reported behaviour in the Spanish Parliamentary elections held in 1989. Attitude showed stronger influence than subjective norm on behavioural intention for subjects with a higher private self-consciousness. The opposite was true for subjects having a lower private self-consciousness. Past behaviour had a significant influence on both behavioural intention and behaviour. [ABSTRACT FROM AUTHOR]

The aim of this study was to analyse the influence of social representation on both social perceptions and social judgments. In the first stage of this study. 47 drug users and 80 'normal' subjects were asked to respond to a questionnaire about representations of drugs. Three weeks later we contacted the some subjects. They were asked to answer some questions about a fictitious story in which an actor labelled as 'a drug user' or 'a person' disputed with a trader. Three different social representations of drugs were found. It was shown that these social representations were anchored in different social groups which were defined by their proximity to the world of drugs. Subjects were themselves drug users shared an accepting or an ambivalent social representation of drugs but they also made the most negative judgements about the causes of a fictitious dispute between a trader and a drug addict. Moreover, these subjects had the most negative perception of the drug addict. Furthermore, some factors which increase the salience of social representations were studied. The effect on social perception and causal attributions of the interaction between social representations, the context and personal involvement in drugs was also shown. Some relations between the theory of social representations and the theories about asymmetrical intergroup relationships are exposed. [ABSTRACT FROM AUTHOR]

Segmentation is one of the most important stages in iris recognition systems. In this paper, image preprocessing algorithms are applied in order to evaluate their impact on successful iris segmentation. The preprocessing algorithms are based on histogram adjustment, Gaussian filters and suppression of specular reflections in human eye images. The segmentation method introduced by Masek is applied on 199 images acquired under unconstrained conditions, belonging to the CASIA-irisV3 database, before and after applying the preprocessing algorithms. Then, the impact of image preprocessing algorithms on the percentage of successful iris segmentation is evaluated by means of a visual inspection of images in order to determine if circumferences of iris and pupil were detected correctly. An increase from 59% to 73% in percentage of successful iris segmentation is obtained with an algorithm that combine elimination of specular reflections, followed by the implementation of a Gaussian filter having a 5x5 kernel. The results highlight the importance of a preprocessing stage as a previous step in order to improve the performance during the edge detection and iris segmentation processes.

The refined multiscale entropy (RMSE) approach is commonly applied to assess complexity as a function of the time scale. RMSE is normally based on the computation of sample entropy (SampEn) estimating complexity as conditional entropy. However, SampEn is dependent on the length and standard deviation of the data. Recently, fuzzy entropy (FuzEn) has been proposed, including several refinements, as an alternative to counteract these limitations. In this work, FuzEn, translated FuzEn (TFuzEn), translated-reflected FuzEn (TRFuzEn), inherent FuzEn (IFuzEn), and inherent translated FuzEn (ITFuzEn) were exploited as entropy-based measures in the computation of RMSE and their performance was compared to that of SampEn. FuzEn metrics were applied to synthetic time series of different lengths to evaluate the consistency of the different approaches. In addition, electroencephalograms of patients under sedation-analgesia procedure were analyzed based on the patient’s response after the application of painful stimulation, such as nail bed compression or endoscopy tube insertion. Significant differences in FuzEn metrics were observed over simulations and real data as a function of the data length and the pain responses. Findings indicated that FuzEn, when exploited in RMSE applications, showed similar behavior to SampEn in long series, but its consistency was better than that of SampEn in short series both over simulations and real data. Conversely, its variants should be utilized with more caution, especially whether processes exhibit an important deterministic component and/or in nociception prediction at long scales.

The level of sedation in patients undergoing medical procedures is decided to assure unconsciousness and prevent pain. The monitors of depth of anesthesia, based on the analysis of the electroencephalogram (EEG), have been progressively introduced into the daily practice to provide additional information about the state of the patient. However, the quantification of analgesia still remains an open problem. The purpose of this work was to analyze the capability of prediction of nociceptive responses based on refined multiscale entropy (RMSE) and auto mutual information function (AMIF) applied to EEG signals recorded in 378 patients scheduled to undergo ultrasonographic endoscopy under sedation-analgesia. Two observed categorical responses after the application of painful stimulation were analyzed: the evaluation of the Ramsay Sedation Scale (RSS) after nail bed compression and the presence of gag reflex (GAG) during endoscopy tube insertion. In addition, bispectrum (BIS), heart rate (HR), predicted concentrations of propofol (CeProp) and remifentanil (CeRemi) were annotated with a resolution of 1 s. Results showed that functions based on RMSE, AMIF, HR and CeRemi permitted predicting different stimulation responses during sedation better than BIS.