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PubMedDate not supplied

[Essence and significance of surgery. Part I -- Birth of surgery: determining factors and contexts].

The author intends to particularly analyse the origin of Surgery as regards its deterministic factors and contexts, resounding the essence and the meaning of Surgery itself. The primary core of the surgical practice dates back to Prehistoric Times, when, driven by his self-preservation instinct, the cave man, when suffering from some trauma, performed on himself a series of more or less immediate "actions" in order to remain healthy. At the same time, a second meaningful nucleus of the surgical experience rises contiguously to the operations the Prehistoric Man performed on another member of his clan. The third stage of this ongoing process, coincident with the origin of surgery in the strict sense of the word, goes back to the tribal context: in fact, in this social organisation only one member of the group was specifically assigned to treat diseases, based on group regulations. For the mediterranean area, the chronological development of this evolution is likely to have started 250,000 years ago in connection with the experience initially of Neanderthal Man and subsequently Cro-Magnon Man in Pleistocene and Holocene of the Quarternary Era respectively, and it could have finished at the beginning of the Neolithic, when the "ancient civilization" of the Mediterranean Basin arose in approximately 10,000 B.C.

General Surgery↗
PubMed1997

Dynamics of the neural discharge in snail neurons.

Spike trains recorded under weak sinusoidal driving from central neurons of Lymnaea stagnalis appear quite irregular and envisage the possibility of an underlying chaotic process. Therefore, the sequences of interspike intervals are analyzed in the framework of non-linear dynamics. Since, for several reasons, these sequences are rather short, the analysis is performed by using methods of non-linear forecasting. To reject the null hypothesis that the original time series is a realization of a linear stochastic process with the same autocorrelation function, the results obtained on the original data are compared with those from surrogate data sets. Some 'non-linear' predictability occurs only in narrow regions of the space of stimulus parameters and the frequency of perturbation is critical in determining it. Moreover, it is shown that such behavior can be qualitatively mimicked by the FitzHugh-Nagumo model driven by a weak sinusoidal signal plus noise. It is argued that the narrowness of the non-linear predictability regions renders quite unlikely the detection of deterministic dynamics in the activity of these neurons.

Action Potentials↗
PubMed1997

A fully automated system for the evaluation of masseter silent periods.

Exteroceptive suppression of masseter muscle activity, 'masseter inhibitory reflex', comprises one or 2 silent periods (SP1 and SP2) interrupting the voluntary activation. The main problem when evaluating exteroceptive suppression is the lack of an objective and precise measure for the onset and end of the silent period which so far has not been overcome by various automated systems. We describe a new fully automated system for determining the onset and end of the masseter silent period. The decision approach is essentially based upon deterministic properties of median filters which are used to partition the local variances of the EMG traces into constant segments and edges between them. The system was tested in 13 healthy volunteers with 2 subjects tested serially 10 times each to get estimates of the inter- and intra-individual variability. The performance of the system compared favourably to that of a simpler approach and to earlier results from our laboratory. The inter-individual variability of the SP1 onset was 17 times smaller than when based on a subjective decision process.

Adolescent↗
PubMed2006

The generalisability of pharmacoeconomic studies: issues and challenges ahead.

Developing from a previous review, this article revisits the generalisability theme to summarise recent advances in methodology and provide an update of challenges faced by producers and users of pharmacoeconomic data. Our original evaluative criteria encompassed technical issues, applicability and transferability. The technical elements of best practice are comparatively uncontroversial: choosing relevant alternatives; transparent reporting of methods and findings; accessing and applying the best-quality evidence; using best methods to synthesise data; and using deterministic sensitivity analysis to explore potential systematic bias whilst employing probabilistic sensitivity analysis to explore the influence of random error at the whole model level. The applicability of economic findings within their original policy context (e.g. national analyses based on generalisable within-country data) can be determined, provided that best practice guidelines for economic modelling are adhered to. The transferability of economic findings (from one policy setting to another, e.g. country, region, clinical setting or patient population) requires careful exploration of changes in resource implications, unit prices and outcomes, a process facilitated again by transparent reporting of methods, adjustment for baseline risk and potentially by recent statistical developments intended to deal with hierarchically structured data. Although there is considerable consensus in the published literature about these key issues, limitations remain for economic analysis as implemented because of its opaqueness of method, failure to reflect the opportunity cost of decisions and lack of societal mandate. If the primary purpose of health economic evaluation is to help society to obtain the best value from limited resources, then, at a time when most technologically advanced societies need to engage with the realities of limited healthcare funding, technocratic solutions alone appear insufficient. Making health economic findings accessible to patients, clinicians and society, in the form of relevant narratives, will help this essential debate and expose assumptions underpinning economic analysis to broader critical inspection.

Economics, Pharmaceutical↗
PubMed1998

Models for haplotype evolution in a nonstationary population.

Haplotype mapping has emerged in the past few years as a powerful tool for the fine mapping of disease genes. It is typically carried out on a sample of affected individuals from a population isolate. If the chromosome neighborhood of a disease gene is saturated with markers, then each new mutation in the population or existing mutation introduced by a population founder exhibits a unique haplotype signature at the time of its introduction. Partial disruption of these signatures by recombination can be visualized in affects and provide important clues to the location of the disease gene. The current paper models haplotype evolution with the intention of clarifying the most favorable circumstances for haplotype mapping. Comparisons with linkage mapping are stressed. For dominant diseases, both deterministic and stochastic models are suggested. Numerical examples based on Finnish population parameters illustrate the general theory in the presence of the complications of selection, mutation, and slow, exponential growth of the isolate.

Biological Evolution↗
PubMed2003

Probabilistic Monte Carlo based mapping of cerebral connections utilising whole-brain crossing fibre information.

A methodology is presented for estimation of a probability density function of cerebral fibre orientations when one or two fibres are present in a voxel. All data are acquired on a clinical MR scanner, using widely available acquisition techniques. The method models measurements of water diffusion in a single fibre by a Gaussian density function and in multiple fibres by a mixture of Gaussian densities. The effects of noise on complex MR diffusion weighted data are explicitly simluated and parameterised. This information is used for standard and Monte Carlo streamline methods. Deterministic and probabilistic maps of anatomical voxel scale connectivity between brain regions are generated.

Algorithms↗
PubMed2005

A stochastic version of corticosteriod pharmacogenomic model.

The purpose of this study was to develop a stochastic version of corticosteriod fifth generation pharmacogenomic model. The Gillespie algorithm was used to generate the independent time courses of the receptor messenger RNA (mRNA). Initial parameters for the stochastic simulation were adapted from the study by Jin et al. The result obtained from the proposed stochastic model showed an overall agreement with the deterministic fifth generation model. This study suggested that because the stochastic model takes into account the "noise" nature of gene regulation, it would have potential application in pharmacogenomic modeling.

Adrenal Cortex Hormones↗
PubMed2003

Localization of electroreceptive function in rabbits.

The detection process by which animals react to the presence of electromagnetic fields (EMFs) may be a form of sensory transduction. However, the anatomic location of signal transduction in most species is unknown. Attempts to solve this problem by applying local EMFs and registering the resulting changes in the electroencephalogram (EEG) have not succeeded because of the nonstationarity of the EEG and the insensitivity of linear methods of analysis. We approached the problem of localizing electroreception in rabbits by using recurrence quantification analysis (RQA), a novel method of nonlinear analysis designed to detect small deterministic changes in a larger signal irrespective of considerations involving stationarity. When 2.5 G, 60 Hz was applied to the entire body, increased determinism in the EEG was found in all 10 animals studied, as evidenced by statistically significant increases in two RQA quantifiers. A similar result occurred when the field was applied only to the front half of each animal, but no effect on the EEG was seen when the field was applied only to the back half. When the field was localized to the head, the effect on the determinism in the EEG was again seen. When the field was further localized to the eye, the effect did not occur. Overall, the results indicated that detection of the field occurred in cells or extracellular structures in the head, probably the brain, although the methods used did not have the resolution to discriminate between specific brain structures. Thus, our results showed that the presence of transient deterministic brain states induced by an EMF signal could be documented using dynamical analysis, thereby allowing us to infer the approximate anatomic location of the signal's transduction.

Animals↗
PubMed1995

A survey of films for use as dosimeters in interventional radiology.

Analysis of radiation doses in interventional radiological procedures that can lead to deterministic radiation effects such as erythema and epilation would assist physicians in planning patients care after exposure and in reducing doses. Photographic films used to measure skin exposure in the past are too sensitive for the high doses involved in interventional procedures. Seventeen different types of films, many of which are generally available in hospitals, were surveyed to see if any would meet the demands of interventional radiology. Sensitometric curves obtained demonstrate that most films are inappropriate for high dose procedures. Using Kodak Fine Grain Positive and Dupont duplicating films and automatic processing, doses as high as 2.8 Gy could be measured with reasonable accuracy. Similar results can be obtained by manually processing Kodak XV-2 verification film at room temperature.

Automation↗
PubMed2003

Escaping from cycles through a glass transition.

A random walk is performed over a disordered media composed of N sites random and uniformly distributed inside a d-dimensional hypercube. The walker cannot remain in the same site and hops to one of its n neighboring sites with a transition probability that depends on the distance D between sites according to a cost function E(D). The stochasticity level is parametrized by a formal temperature T. In the case T=0, the walk is deterministic and ergodicity is broken: the phase space is divided in a O(N) number of attractor basins of two-cycles that trap the walker. For d=1, analytic results indicate the existence of a glass transition at T(1)=1/2 as N--> infinity. Below T1, the average trapping time in two-cycles diverges and an out-of-equilibrium behavior appears. Similar glass transitions occur in higher dimensions when the right cost function is chosen. We also present some results for the statistics of distances for Poisson spatial point processes.

Journal Article↗
PubMed2004

A point-process model of human heartbeat intervals: new definitions of heart rate and heart rate variability.

Heart rate is a vital sign, whereas heart rate variability is an important quantitative measure of cardiovascular regulation by the autonomic nervous system. Although the design of algorithms to compute heart rate and assess heart rate variability is an active area of research, none of the approaches considers the natural point-process structure of human heartbeats, and none gives instantaneous estimates of heart rate variability. We model the stochastic structure of heartbeat intervals as a history-dependent inverse Gaussian process and derive from it an explicit probability density that gives new definitions of heart rate and heart rate variability: instantaneous R-R interval and heart rate standard deviations. We estimate the time-varying parameters of the inverse Gaussian model by local maximum likelihood and assess model goodness-of-fit by Kolmogorov-Smirnov tests based on the time-rescaling theorem. We illustrate our new definitions in an analysis of human heartbeat intervals from 10 healthy subjects undergoing a tilt-table experiment. Although several studies have identified deterministic, nonlinear dynamical features in human heartbeat intervals, our analysis shows that a highly accurate description of these series at rest and in extreme physiological conditions may be given by an elementary, physiologically based, stochastic model.

Adult↗
PubMed1985

Stochastic branching model for hemopoietic progenitor cell differentiation.

We present algebraic expressions describing the predictions of a stochastic branching model for differentiation of hemopoietic progenitor cells. The model assumes that there is a fixed probability, p (0 less than or equal to p less than or equal to 1), that commitment to a differentiative event occurs per progenitor cell division for each daughter cell. The model describes properties of in vitro hemopoietic cell differentiation including the population structure at the time the first progenitor cell becomes committed, the number of committed progenitor cells engendered by a single progenitor cell, and the probability of eventual commitment of all daughter cells derived from a single progenitor or stem cell. Application of the model to experimental data obtained from erythroid cultures suggests that the observed data can be explained by the stochastic branching model alone without making the deterministic assumption that there is a differentiative hierarchy in the lineage of the progenitors of erythropoiesis (BFU-E). The qualitative and quantitative aspects of the proposed stochastic model are discussed in conjunction with other analogous stochastic branching models.

Cell Division↗
PubMed1997

Iterated Prisoner's Dilemma: pay-off variance.

The iterated Prisoner's Dilemma (IPD) is usually analysed by evaluating arithmetic mean pay-offs in an ESS analysis. We consider several points that the standard argument does not address. Finite population size and finite numbers of matches in the IPD game lead us to consider both pay-off variance and the sampling process in the evolutionary game. We provide a general form for the pay-off variance of the Markov strategist in the IPD game, and present a general analysis of the initial invasion process of an "all defection strategist" (ALLD) into a "tit-for-tat" (TFT) strategist population by considering stochastic processes. Finite population size, strategic error an the variances of pay-offs alter the prediction concerning the initial invasion of ALLD compared with the standard Evolutionarily Stable Strategy (ESS) analysis. Even though TFT gets the larger arithmetic mean, the variance of its pay-off is also larger when the expected iterations of the game are sufficiently large. Therefore, the boundary of the parameter of the probability of game continuity, w, above which ALLD does not have advantage to invade into the TFT population, becomes a bit larger than predicted by the deterministic model.

Biological Evolution↗
PubMed1992

A statistical analysis of the ECG measurements used in computerized interpretation of acute anterior myocardial infarction with applications to interpretive criteria development.

Computerized interpretation of the electrocardiogram (ECG) for detection of acute myocardial infarction (AMI) has been an area of active investigation for the past few years. Advances in the development of criteria for increased accuracy have resulted through the use of clinically correlated databases. Previously, using such databases, the sensitivity for interpretation of AMI in the Marquette 12SL ECG analysis program has increased from 21% to 65% with specificity remaining unchanged (99%). This study attempted to find measurements of the QRS and ST-segment from 7 of the 12 standard ECG leads to increase the sensitivity of detection of anterior AMI to the level of a trained physician while maintaining the current level of specificity. Regression analyses were performed on the measurements to see which ones could improve sensitivity and what effect they had on specificity. There was no clear separation of the individual measurements between the normal database or the true positive and true negative anterior AMI databases for maintaining high specificity. In a parallel study of the same data, deterministic criteria combining both ST and T wave information increased the sensitivity of the 12SL analysis program for detection of anterior AMI to 71% on a clinically correlated anterior AMI database and 75% on a physician interpreted anterior AMI database while maintaining the specificity at 99%.

Adult↗
PubMed2005

Heart rate variability in dairy cows-influences of breed and milking system.

Heart rate variability parameters in the time, frequency and nonlinear domains were investigated in two breeds of dairy cows (Austrian Simmental and Brown Swiss) milked either in an automatic milking system with partially forced cow traffic or in a herringbone milking parlour. Recordings were made of 24 cows (six of each breed and milking system) during lying, standing idle, and standing being milked, and analysed with linear mixed effects models taking the covariates time of day, live body weight, milk yield, stage of lactation and stage of pregnancy into account. Heart rate and nonlinear deterministic shares were higher, and heart rate variability in the time and frequency domains was lower, later in the day, in cows with higher body weight and in Simmental compared to Brown Swiss cows. Differences in the linear and nonlinear domains during lying indicated an increased level of chronic stress in cows in the automatic milking system with partially forced cow traffic, compared to cows milked in the herringbone milking parlour. No effects of milking system were found during milking, indicating that the stressor in the automatic milking system was not the milking process itself.

Analysis of Variance↗
PubMed1994

Low-dimensional chaos in biological systems.

During the past five years general rules have been developed for the application of chaos theory to biology and medicine, which enable investigators to avoid the pitfalls that invalidated and trivialized many earlier results. The importance of biological chaos is that the variables governing the spatial and temporal geometries of the system may be few in number, fractional in dimension, and thus enable low-energy control with complex deterministic consequences. The complexity of control inherent in chaotic systems may be important in the dynamics of gene expression and translation. Extending these ideas may lead to completely novel ways to modulate protein production by introducing simple pulses at critical times or places.

Algorithms↗
PubMedDate not supplied

Robust nonlinear autoregressive moving average model parameter estimation using stochastic recurrent artificial neural networks.

In this study, we introduce a new approach for estimating linear and nonlinear stochastic autoregressive moving average (ARMA) model parameters, given a corrupt signal, using artificial recurrent neural networks. This new approach is a two-step approach in which the parameters of the deterministic part of the stochastic ARMA model are first estimated via a three-layer artificial neural network (deterministic estimation step) and then reestimated using the prediction error as one of the inputs to the artificial neural networks in an iterative algorithm (stochastic estimation step). The prediction error is obtained by subtracting the corrupt signal of the estimated ARMA model obtained via the deterministic estimation step from the system output response. We present computer simulation examples to show the efficacy of the proposed stochastic recurrent neural network approach in obtaining accurate model predictions. Furthermore, we compare the performance of the new approach to that of the deterministic recurrent neural network approach. Using this simple two-step procedure, we obtain more robust model predictions than with the deterministic recurrent neural network approach despite the presence of significant amounts of either dynamic or measurement noise in the output signal. The comparison between the deterministic and stochastic recurrent neural network approaches is furthered by applying both approaches to experimentally obtained renal blood pressure and flow signals.

Algorithms↗
PubMed2004

A systems approach to error prevention in medicine.

Minimization of medical errors is at the core of all clinical medical practices. The first tenet of care is to do no harm. The enormous complexity of modern medical care has made error detection and management extremely difficult. Traditional deterministic methods of solving the "error issue" cannot cope with the huge number of potential errors that are possible. Systems thinking and approach to error reduction provides a different avenue for tackling this challenging dilemma. The intent of this article is to introduce a systems view of medical errors and to explain how it can provide new insights about dealing with massively complex organizations such as the healthcare system. Important features include an understanding of system relationships, sources of error, human components, optimization versus perfection in systems and the interrelationships between human and system processes.

Delivery of Health Care↗