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Search Results: 1 - 10 of 151665 matches for " Scott B; "
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An animated depiction of major depression epidemiology
Scott B Patten
BMC Psychiatry , 2007, DOI: 10.1186/1471-244x-7-23
Abstract: In this study, up-to-date data on major depression epidemiology were integrated using a discrete event simulation model. The mathematical model was animated in Virtual Reality Modeling Language (VRML) to create a visual, rather than mathematical, depiction of the epidemiology.Consistent with existing literature, the model highlights potential advantages of population health strategies that emphasize access to effective long-term treatment. The paper contains a web-link to the animation.Visual animation of epidemiological results may be an effective knowledge translation tool. In clinical practice, such animations could potentially assist with patient education and enhanced long-term compliance.A comprehensive picture of the epidemiology of an episodic condition cannot be embodied in a single parameter such as an estimate of incidence or prevalence. The incidence of major depressive disorder conveys information about the risk of onset of an initial episode, but this is of limited value for clinical practice (where presentations occur after onset) or for public policy (since the rate of onset of new episodes does not adequately reflect the burden of disease). Prevalence is in some respects an even more obscure parameter. Prevalence is the number or proportion ("prevalence proportion") of population members who have a disorder at a point ("point prevalence") in time or during a period ("period prevalence") in time. This parameter is salient to the problem of quantifying disease burden but ultimately reflects a balance between entry into the prevalence pool (incidence or recurrence) and a other factors such as episode duration and mortality.Attempts to integrate epidemiological estimates into a comprehensive "picture" of the epidemiology of major depression have used Markov models [1,2] and micro-simulation approaches [3]. The complexity of major depression epidemiology has required the development of fairly complex models, the mathematics of which may not be of great i
Major depression epidemiology from a diathesis-stress conceptualization
Scott B Patten
BMC Psychiatry , 2013, DOI: 10.1186/1471-244x-13-19
Abstract: Simulation provides an opportunity to explore these issues. In this study, a simulation model based on an intuitive representation of diathesis-stress interaction was developed. Both diathesis and stress were represented using continuous distributions, without categorization. A diagnostic threshold was then applied to the simulation output to create nominal categories and to explore their consistency with available information.An apparently complex epidemiologic pattern emerged from the diathesis-stress interaction when thresholds were applied: incidence was time dependent, recurrence depended on the number of past episodes, baseline symptoms were associated with an increased risk of subsequent episodes and the remission rate declined with increasing episode duration.A diathesis-stress conceptualization coupled with application of a threshold-based diagnostic definition may explain several of the apparent complexities of major depression epidemiology. Some of these complexities may be artifacts of the nominal diagnostic approach. These observations should encourage an empirical exploration of whether diathesis-stress interactions provide a more parsimonious framework for understanding depression than current approaches.Depressive symptoms can be measured using rating scales, which provide an assessment of symptom severity on an ordinal or continuous scale. However, such ratings do not capture important aspects of the concept of a depressive disorder, as this is currently understood. Disorder definitions, and hence most available epidemiologic data, derive from nominal classifications (e.g. major depression (MD) as a named category rather than a scaled rating) that incorporate symptom severity but also thresholds for duration and severity of symptoms and require features such as dysfunction, distress or danger [1]. Diagnostic categories typically play a larger role than symptom ratings in medical practice because they align more closely with clinical decision-making.
Accumulation of major depressive episodes over time in a prospective study indicates that retrospectively assessed lifetime prevalence estimates are too low
Scott B Patten
BMC Psychiatry , 2009, DOI: 10.1186/1471-244x-9-19
Abstract: The NPHS is a longitudinal study that has followed a community sample representative of household residents since 1994. Follow-up interviews have been completed every two years and have incorporated the Composite International Diagnostic Interview short form for major depression. Data are currently available for seven such interview cycles spanning the time frame 1994 to 2006. In this study, cumulative prevalence was calculated by determining the proportion of respondents who had one or more major depressive episodes during this follow-up interval.The annual prevalence of MDD ranged between 4% and 5% of the population during each assessment, consistent with existing literature. However, 19.7% of the population had at least one major depressive episode during follow-up. This included 24.2% of women and 14.2% of men. These estimates are nearly twice as high as the lifetime prevalence of major depressive episodes reported by cross-sectional studies during same time interval.In this study, prospectively observed cumulative prevalence over a relatively brief interval of time exceeded lifetime prevalence estimates by a considerable extent. This supports the idea that lifetime prevalence estimates are vulnerable to recall bias and that existing estimates are too low for this reason.Lifetime prevalence is one of the most frequently reported parameters in psychiatric epidemiology. Lifetime prevalence represents the proportion of the population who have experienced a disorder at some time in their life up to the time of interview. In the case of Major Depressive Disorder, this is the proportion of the population who have experienced a major depressive episode (MDE) but not a manic, hypomanic or mixed episode and who do not have a concurrent psychotic disorder. In Canada, the lifetime prevalence of MDE is 12.2% [1] as determined by a national survey called the Canadian Community Health Survey, Mental Health and Wellbeing (CCHS 1.2) conducted in 2002. Similar values have been r
Problems encountered with the use of simulation in an attempt to enhance interpretation of a secondary data source in epidemiologic mental health research
Scott B Patten
BMC Research Notes , 2010, DOI: 10.1186/1756-0500-3-231
Abstract: The data source was a Canadian longitudinal study called the National Population Health Survey (NPHS). A simulation model representing the course of depressive episodes was used to reshape estimates deriving from binary and ordinal logistic models (fit to the NPHS data) into equations more capable of informing clinical and public health decisions. Discrete event simulation was used for this purpose. Whereas the intention was to clarify a complex epidemiology, the models themselves needed to become excessively complex in order to provide an accurate description of the data.Simulation methods are useful in circumstances where a representation of a real-world system has practical value. In this particular scenario, the usefulness of simulation was limited both by problems with the data source and by inherent complexity of the underlying epidemiology.Major Depressive Disorder (MDD) is a mood disorder that is characterized by one or more major depressive episodes (MDE). Clinical practice guidelines for MDD have historically regarded the diagnosis as a de facto indication of treatment need (e.g.[1]). However, in community studies application of diagnostic criteria for MDD has been shown to identify some short lived episodes that may not be associated with a need for treatment [2]. This has led to more recent recommendations acknowledging the apparent heterogeneity of this condition. For example, in the strategy of "watchful waiting" treatment may be delayed for several weeks while there is ongoing monitoring in order to determine whether an episode will resolve without active treatment [3]. For mild episodes, guided self-management has also been proposed as a reasonable intervention [3,4].It would be helpful to make use of epidemiologic data in order to quantify the probability of various outcomes and ultimately to use this information as a means of supporting clinical decisions. Recently, the predictD study has reported predictive algorithms for the risk of MDE in genera
The impact of antidepressant treatment on population health: synthesis of data from two national data sources in Canada
Scott B Patten
Population Health Metrics , 2004, DOI: 10.1186/1478-7954-2-9
Abstract: Data from two Canadian general health surveys were used in this analysis: the National Population Health Survey (NPHS) and the Canadian Community Health Survey (CCHS). The NPHS is a longitudinal study that collected data between 1994 and 2000. These longitudinal data allowed an approximation of episode incidence to be calculated. The cross-sectional CCHS allowed estimation of episode duration. The surveys used the same sampling frame and both incorporated a Short Form version of the Composite International Diagnostic Interview.Episodes occurring in antidepressant users lasted longer than those in non-users. The apparent incidence of major depressive episodes among those taking antidepressants was higher than that among respondents not taking antidepressants. Changes in duration and incidence over the data collection interval were not observed.The most probable explanation for these results is confounding by indication and/or severity: members of the general population who are taking antidepressants probably have more highly recurrent and more severe mood disorders. In part, this may have been due to the use of a brief predictive diagnostic interview, which may be prone to detection of sub-clinical cases. Whereas antidepressant use increased considerably over the data-collection period, differences in episode incidence and duration over time were not observed. This suggests that the impact of antidepressant medications on population health may have been less than expected.Depressive disorders are among the most important contributors to disease burden at the population level http://www.who.int/whr2001/2001/ webcite. While primary prevention for this condition has remained an elusive goal, provision of treatment has been viewed as having the capacity to reduce its impact on population health. Randomized, controlled clinical trials confirm that treatment with antidepressant medications can favorably impact the course of major depressive disorder. Clinical practice guid
Contribution of anaerobic energy expenditure to whole body thermogenesis
Christopher B Scott
Nutrition & Metabolism , 2005, DOI: 10.1186/1743-7075-2-14
Abstract: "...(animals) take up oxygen and complex compounds made by plants, discharge these compounds largely in the form of carbonic acid (CO2)and water as the products of combustion and partly as simpler reduced products, thus consuming a certain quantity of chemical potential energy, and generate thereby heat and mechanical energy" (H.L.F. Helmholtz, 1821-1894)Measurements of heat loss and oxygen uptake are the two major methods for determining energy expenditure although they do not always provide equivalent results at equivalent time points [1-4]. The focus on oxygen uptake follows from the extensive involvement of mitochondria in ATP re-synthesis accompanied by concomitant heat production [5-8]. Sites of ATP hydrolysis (e.g. contracting muscle) represent another source of energy transfer and heat exchange. Non-steady state periods of rapid growth and development, disease, arousal from torpor, heavy/severe exercise and hypoxia, however, offer proof of how tenuous the relationship between heat loss and oxygen uptake can be [1,3,4,9-11]. In isolated mammalian cells, for example, the accelerated production of lactate has been shown to make a substantial contribution to heat production beyond mitochondrial (aerobic) involvement [12]. If heat serves as the standard measure of energy expenditure then anaerobic energy transfer, specifically rapid glycolysis and glycogenolysis with lactate production (i.e., rapid anaerobic ATP re-synthesis) has the potential to make significant contributions to cellular energy expenditure.Glycolysis as a form of fermentation has been a part of life for an estimated three billion years [13]. It has been observed that anaerobic glycolysis and oxygen uptake often behave in a reciprocal manner. Pasteur, for example, demonstrated that glucose utilization in yeast was more rapid when oxygen was absent [14]. It was subsequently hypothesized that alterations in aerobic respiration influence glycolytic rate. Crabtree [15] described the suppression of ox
Dengue in the Americas and Southeast Asia: do they differ?
Halstead,Scott B.;
Revista Panamericana de Salud Pública , 2006, DOI: 10.1590/S1020-49892006001100007
Abstract: the populations of southeast asia (se asia) and tropical america are similar, and all four dengue viruses of asian origin are endemic in both regions. yet, during comparable 5-year periods, se asia experienced 1.16 million cases of dengue hemorrhagic fever (dhf), principally in children, whereas in the americas there were 2.8 million dengue fever (df) cases, principally in adults, and only 65 000 dhf cases. this review aims to explain these regional differences. in se asia, world war ii amplified aedes aegypti populations and the spread of dengue viruses. in the americas, efforts to eradicate a. aegypti in the 1940s and 1950s contained dengue epidemics mainly to the caribbean basin. cuba escaped infections with the american genotype dengue-2 and an asian dengue-3 endemic in the 1960s and 1970s. successive infections with dengue-1 and an asian genotype dengue-2 resulted in the 1981 dhf epidemic. when this dengue-2 virus was introduced in other caribbean countries, it encountered populations highly immune to the american genotype dengue-2. during the 1980s and 1990s, rapidly expanding populations of a. aegypti in brazil permitted successive epidemics of dengue-1, -2, and -3. these exposures, however, resulted mainly in df, with surprisingly few cases of dhf. the absence of high rates of severe dengue disease in brazil, as elsewhere in the americas, may be partly explained by the widespread prevalence of human dengue resistance genes. understanding the nature and distribution of these genes holds promise for containing severe dengue. future research on dengue infections should emphasize population-based designs.
Dengue hemorrhagic fever: two infections and antibody dependent enhancement, a brief history and personal memoir
Scott B Halstead
Revista Cubana de Medicina Tropical , 2002,
A major depression prognosis calculator based on episode duration
Patten Scott B
Clinical Practice and Epidemiology in Mental Health , 2006, DOI: 10.1186/1745-0179-2-13
Abstract: Background Epidemiological data have shown that the probability of recovery from an episode declines with increasing episode duration, such that the duration of an episode may be an important factor in determining whether treatment is required. The objective of this study is to incorporate episode duration data into a calculator predicting the probability of recovery during a specified interval of time. Methods Data from two Canadian epidemiological studies were used, both studies were components of a program undertaken by the Canadian national statistical agency. One component was a cross-sectional psychiatric epidemiological survey (n = 36,984) and the other was a longitudinal study (n = 17,262). Results A Weibull distribution provided a good description of episode durations reported by subjects with major depression in the cross-sectional survey. This distribution was used to develop a discrete event simulation model for episode duration calibrated using the longitudinal data. The resulting estimates were then incorporated into a predictive calculator. During the early weeks of an episode, recovery probabilities are high. The model predicts that approximately 20% will recover in the first week after diagnostic criteria for major depression are met. However, after six months of illness, recovery during a subsequent week is less than 1%. Conclusion The duration of an episode is relevant to the probability of recovery. This epidemiological feature of depressive disorders can inform prognostic judgments. Watchful waiting may be an appropriate strategy for mild episodes of recent onset, but the risks and benefits of this strategy must be assessed in relation to time since onset of the episode.
Markov models of major depression for linking psychiatric epidemiology to clinical practice
Patten Scott B
Clinical Practice and Epidemiology in Mental Health , 2005, DOI: 10.1186/1745-0179-1-2
Abstract: Background Most epidemiological studies of major depression report estimates of period prevalence. Such estimates are useful for public health applications, but are not very helpful for informing clinical practice. Period prevalence is determined predominantly by incidence and episode duration, but it is difficult to connect these epidemiological concepts to clinical issues such as risk and prognosis. Incidence is important for primary and secondary prevention, and prognostic information is useful for clinical decision-making. The objective of this study was to decompose period prevalence data for major depression into its constituent elements, thereby enhancing the value of these estimates for clinical practice. Data from a series of population-based Canadian studies were used in the analysis. Markov models depicting incidence, prevalence and recovery from major depressive episodes were developed. Monte Carlo simulation was used to constrain model parameters to the epidemiological data. Results The association of sex with major depression was found to be due to a higher incidence in women. In distinction, the higher prevalence in unmarried subjects was mostly due to a different prognosis. Age-related changes in prevalence were influenced by both factors. Education, which was not found to be associated with major depression in the survey data, had no impact either on risk or prognosis. Conclusion The period prevalence of major depression is influenced both by incidence (risk) and episode duration (prognosis). Mathematical modeling of the underlying epidemiological relationships can make such data more readily interpretable in relation to clinical practice.
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