1,338 research outputs found

    Preventing Debt Crises

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    Debt Sustainability after the Pandemic: a Rift between Advanced and Developing Economies?

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    The aftermath of the Covid-19 health crisis poses major fiscal challenges to many countries, both advanced and developing. A key issue facing policymakers is the amount of available fiscal space given the recent surge in public debt. Exceptional shocks like the pandemic can push countries beyond their debt sustainability limit, inevitably constraining countries’ fiscal space. Against this backdrop this paper estimates the development of public debt limits and ensuing fiscal space for a panel of G20 economies - developed and developing - since the 1990s. This analysis suggests that advanced and developing economies face entirely different conditions for the conduct of independent fiscal policies to address major shocks, with the former generally much better placed

    Hidden Markov models based on symbolic dynamics for statistical modeling of cardiovascular control in hypertensive pregnancy disorders

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    Copyright © 2006 IEEEDiscrete hidden Markov models (HMMs) were applied to classify pregnancy disorders. The observation sequence was generated by transforming RR and systolic blood pressure time series using symbolic dynamics. Time series were recorded from 15 women with pregnancy-induced hypertension, 34 with preeclampsia and 41 controls beyond 30th gestational week. HMMs with five to ten hidden states were found to be sufficient to characterize different blood pressure variability, whereas significant classification in RR-based HMMs was found using fifteen hidden states. Pregnancy disorders preeclampsia and pregnancy induced hypertension revealed different patho-physiological autonomous regulation supposing different etiology of both disorders.V. Baier, M. Baumert, P. Caminal, M. VallverdĂș, R. Faber, and A. Vos

    Modeling the Effect of Propofol and Remifentanil Combinations for Sedation-Analgesia in Endoscopic Procedures Using an Adaptive Neuro Fuzzy Inference System (ANFIS)

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    BACKGROUND: The increasing demand for anesthetic procedures in the gastrointestinal endoscopy area has not been followed by a similar increase in the methods to provide and control sedation and analgesia for these patients. In this study, we evaluated different combinations of propofol and remifentanil, administered through a target-controlled infusion system, to estimate the optimal concentrations as well as the best way to control the sedative effects induced by the combinations of drugs in patients undergoing ultrasonographic endoscopy. METHODS: One hundred twenty patients undergoing ultrasonographic endoscopy were randomized to receive, by means of a target-controlled infusion system, a fixed effect-site concentration of either propofol or remifentanil of 8 different possible concentrations, allowing adjustment of the concentrations of the other drug. Predicted effect-site propofol (C(e)pro) and remifentanil (C(e)remi) concentrations, parameters derived from auditory evoked potential, autoregressive auditory evoked potential index (AAI/2) and electroencephalogram (bispectral index [BIS] and index of consciousness [IoC]) signals, as well as categorical scores of sedation (Ramsay Sedation Scale [RSS] score) in the presence or absence of nociceptive stimulation, were collected, recorded, and analyzed using an Adaptive Neuro Fuzzy Inference System. The models described for the relationship between C(e)pro and C(e)remi versus AAI/2, BIS, and IoC were diagnosed for inaccuracy using median absolute performance error (MDAPE) and median root mean squared error (MDRMSE), and for bias using median performance error (MDPE). The models were validated in a prospective group of 68 new patients receiving different combinations of propofol and remifentanil. The predictive ability (P(k)) of AAI/2, BIS, and IoC with respect to the sedation level, RSS score, was also explored. RESULTS: Data from 110 patients were analyzed in the training group. The resulting estimated models had an MDAPE of 32.87, 12.89, and 8.77; an MDRMSE of 17.01, 12.81, and 9.40; and an MDPE of -1.86, 3.97, and 2.21 for AAI/2, BIS, and IoC, respectively, in the absence of stimulation and similar values under stimulation. P(k) values were 0.82, 0.81, and 0.85 for AAI/2, BIS, and IoC, respectively. The model predicted the prospective validation data with an MDAPE of 34.81, 14.78, and 10.25; an MDRMSE of 16.81, 15.91, and 11.81; an MDPE of -8.37, 5.65, and -1.43; and P(k) values of 0.81, 0.8, and 0.8 for AAI/2, BIS, and IoC, respectively. CONCLUSION: A model relating C(e)pro and C(e)remi to AAI/2, BIS, and IoC has been developed and prospectively validated. Based on these models, the (C(e)pro, C(e)remi) concentration pairs that provide an RSS score of 4 range from (1.8 Όg·mL(-1), 1.5 ng·mL(-1)) to (2.7 Όg·mL(-1), 0 ng·mL(-1)). These concentrations are associated with AAI/2 values of 25 to 30, BIS of 71 to 75, and IoC of 72 to 76. The presence of noxious stimulation increases the requirements of C(e)pro and C(e)remi to achieve the same degree of sedative effects

    Cerebral state index during propofol anesthesia:A Comparison with the Bispectral Index and the A-Line ARX Index

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    Background: The objective of this study was to prospectively test the Cerebral State Index designed for measuring the depth of anesthesia. The Cerebral State Index is calculated using a fuzzy logic combination of four subparameters of the electroencephalographic signal. The performance of the Cerebral State index was compared with that of the Bispectral Index and the A-Line ARX Index. Methods: This study applied raw data from two previously published clinical protocols. The patients in protocol 1 were given a continuous propofol infusion, 300 ml/h, until 80% of burst suppression occurred. In protocol 2, a stepwise increased target-controlled infusion of propofol was administered to patients until loss of response to noxious stimuli while the Observer's Assessment of Alertness and Sedation was registered every 4 min. The Cerebral State index was calculated off-line from the recorded electroencephalographic data. The Spearman rank correlation coefficient between electronic indices and the effect site concentration of propofol was calculated along with the prediction probability of each index to predict the Observer's Assessment of Alertness and Sedation level. Results: The Spearman rank correlation coefficients between the Cerebral State Index, Bispectral Index, and A-Line ARX Index and the propofol effect site concentration were -0.94, -0.89, and -0.82, respectively, in protocol 1, whereas the prediction probability values between the Cerebral State Index, Bispectral Index, and A-Line ARX Index and the Observer's Assessment of Alertness and Sedation score in protocol 2 were 0.92, 0.93, and 0.91, respectively. Conclusion: The Cerebral State Index detects well the graduated levels of propofol anesthesia when compared with the propofol effect site concentration and the Observer's Assessment of Alertness and Sedation score

    Detrended Fluctuation Analysis of Heart Rate by Means of Symbolic Series

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    Abstract Detrended fluctuation analysis (DFA) Introduction Fluctuations of time intervals between consecutive heartbeats exhibit a complex dynamics, which is influenced by the activity of many regulatory systems interacting over a wide range of time or space scales The study of heart rate time series using detrended fluctuation analysis (DFA) has been shown to be a useful tool for diagnostic in patients with cardiac diseases Previous studies Variability of heart rate fluctuations has been also studied by using RR increment series ( RR series) and, particularly, by using series constructed with the magnitude and the sign of RR series In this work, an alternative methodology was introduced in order to improve the statistical differentiation between risk groups of suffering cardiac death, by applying DFA over RR series. The methodology considered a symbolic transformation of RR series by means of an alphabet with four symbols. Results were compared with those calculated over original RR series and, series corresponding with magnitude and sign of RR series. Methods Analyzed databas

    Symbolic Dynamic Analysis of Relations Between Cardiac and Breathing Cycles in Patients on Weaning Trials

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    Traditional time-domain techniques of data analysis are often not sufficient to characterize the complex dynamics of the cardiorespiratory interdependencies during the weaning trials. In this paper, the interactions between the heart rate (HR) and the breathing rate (BR) were studied using joint symbolic dynamic analysis. A total of 133 patients on weaning trials from mechanical ventilation were analyzed: 94 patients with successful weaning (group S) and 39 patients that failed to maintain spontaneous breathing (group F). The word distribution matrix enabled a coarse-grained quantitative assessment of short-term nonlinear analysis of the cardiorespiratory interactions. The histogram of the occurrence probability of the cardiorespiratory words presented a higher homogeneity in group F than in group S, measured with a higher number of forbidden words in group S as well as a higher number of words whose probability of occurrence is higher than a probability threshold in group S. The discriminant analysis revealed the best results when applying symbolic dynamic variables. Therefore, we hypothesize that joint symbolic dynamic analysis provides enhanced information about different interactions between HR and BR, when comparing patients with successful weaning and patients that failed to maintain spontaneous breathing in the weaning procedure
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