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ABSTRACT: Weather is the most frequently proposed factor driving apparent seasonal trends in stroke admissions. Here, we present the largest study of the association between weather and ischemic stroke in the USA to date. We consider admissions to 155 United States hospitals in 20 states during the five-year period from 2004 to 2008. The data set included 196,439 stroke admissions, which were classified as ischemic (n=98,930), hemorrhagic (n=18,960), or transient ischemic attack (n=78,549). Variations in stroke admissions were tested to determine if they tracked seasonal and transient weather patterns over the same time period. Using autocorrelation analyses, no significant seasonal changes in stroke admissions were observed over the study period. Using time-series analyses, no significant association was observed between any weather variable and any stroke subtype over the five-year study. This study suggests that seasonal associations between weather and stroke are highly confounded, and an association between weather and stroke is virtually non-existent. Therefore, previous studies reporting an association between specific weather patterns and stroke should be interpreted with caution.
Journal of Clinical Neuroscience 03/2011; 18(5):618-23. · 1.25 Impact Factor
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ABSTRACT: Alcohol and drug use is known to be a major factor affecting the incidence of traumatic injury. However, the ways in which immediate pre-injury substance use affects patients' clinical care and outcomes remains unclear. The goal of the present study is to determine the associations between pre-injury use of alcohol or drugs and patient injury severity, hospital course, and clinical outcome.
This study used more than 200,000 records from the National Trauma Data Bank (NTDB), which is the largest trauma registry in the United States. Incidents in the NTDB were placed into one of four classes: alcohol related, drug related, alcohol-and-drug related, and substance negative. Logistic regression models were used to determine comorbid conditions or treatment complications that were significantly associated with pre-injury substance use. Hospital charges were associated with the presence or absence of drugs and alcohol, and patient outcomes were assessed using discharge disposition as delimited by the NTDB.
The rates of complications arising during treatment were 8.3, 10.9, 9.9 and 8.6 per one hundred incidents in the alcohol related, drug related, alcohol-and-drug related, and substance-negative classes, respectively. Regression models suggested that pre-injury alcohol use is associated with a 15% higher risk of infection, whereas pre-injury drug use is associated with a 30% higher risk of infection. Pre-injury substance use did not appear to significantly impact clinical outcomes following treatment for traumatic injury, however.
This study suggests that pre-injury drug use is associated with a significantly higher complication rate. In particular, infection during hospitalization is a significant risk for both alcohol and drug related trauma visits, and drug-related trauma incidents are associated with increased risk for additional circulatory complications. Although drug and alcohol related trauma incidents are not associated with appreciably worse clinical outcomes, patients experiencing such complications are associated with significantly greater length of stay and higher hospitalization costs. Therefore significant benefits to trauma patients could be gained with enhanced surveillance for pre-injury substance use upon admission to the ED, and closer monitoring for infection or circulatory complications during their period of hospitalization.
Journal of Trauma Management & Outcomes 01/2011; 5:3.
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ABSTRACT: A seasonal and meteorological influence on the incidence of spontaneous subarachnoid hemorrhage (SAH) has been suggested, but a consensus in the literature has yet to emerge.
This study examines the impact of weather patterns on the incidence of SAH using a geographically broad analysis of hospital admissions and represents the largest study of the topic to date.
We retrospectively analyzed SAH admissions to 155 US hospitals during the calendar years 2004 to 2008 (N = 7758). Daily weather readings for temperature, pressure, and humidity were obtained for the same period from National Oceanic and Atmospheric Administration weather stations located near each hospital. The daily values of each weather variable were associated with the daily volume of SAH admissions using a combination of correlation and time-series analyses.
No seasonal trends were observed in the monthly volume of SAH admissions during the study period. No significant correlation was detected between the daily SAH admission volume and the day's weather, the previous day's weather, or the 24-hour weather change.
This study represents the most comprehensive investigation of the association between weather and spontaneous SAH to date. The results suggest that neither season nor weather significantly influences the incidence of SAH.
Neurosurgery 01/2011; 68(1):132-8; discussion 138-9. · 2.79 Impact Factor
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ABSTRACT: As their power and utility increase, genome-wide association (GWA) studies are poised to become an important element of the neurosurgeon's toolkit for diagnosing and treating disease. In this paper, the authors review recent findings and discuss issues associated with gathering and analyzing GWA data for the study of neurological diseases and disorders, including those of neurosurgical importance. Their goal is to provide neurosurgeons and other clinicians with a better understanding of the practical and theoretical issues associated with this line of research. A modern GWA study involves testing hundreds of thousands of genetic markers across an entire genome, often in thousands of individuals, for any significant association with a particular disease. The number of markers assayed in a study presents several practical and theoretical issues that must be considered when planning the study. Genome-wide association studies show great promise in our understanding of the genes underlying common neurological diseases and disorders, as well as in leading to a new generation of genetic tests for clinicians.
Neurosurgical FOCUS 01/2010; 28(1):E2. · 2.87 Impact Factor
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ABSTRACT: Evolution by natural selection is fundamentally shaped by the fitness landscapes in which it occurs. Yet fitness landscapes are vast and complex, and thus we know relatively little about the long-range constraints they impose on evolutionary dynamics. Here, we exhaustively survey the structural landscapes of RNA molecules of lengths 12 to 18 nucleotides, and develop a network model to describe the relationship between sequence and structure. We find that phenotype abundance--the number of genotypes producing a particular phenotype--varies in a predictable manner and critically influences evolutionary dynamics. A study of naturally occurring functional RNA molecules using a new structural statistic suggests that these molecules are biased toward abundant phenotypes. This supports an "ascent of the abundant" hypothesis, in which evolution yields abundant phenotypes even when they are not the most fit.
PLoS Computational Biology 01/2008; 4(7):e1000110. · 5.22 Impact Factor
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ABSTRACT: Recent advances in molecular biology and computation have enabled evolutionary biologists to develop models that explicitly capture molecular structure. By including complex and realistic maps from genotypes to phenotypes, such models are yielding important new insights into evolutionary processes. In particular, computer simulations of evolving RNA structure have inspired a new conceptual framework for thinking about patterns of mutational connectivity and general theories about the nature of evolutionary transitions, the evolutionary ascent of nonoptimal phenotypes, and the origins of mutational robustness and modular structures. Here, we describe this class of RNA models and review the major conceptual contributions they have made to evolutionary biology.
Annu. Rev. Ecol. Evol. Syst. 01/2007; 38.
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ABSTRACT: Deleterious mutations are considered a major impediment to adaptation, and there are straightforward expectations for the rate at which they accumulate as a function of population size and mutation rate. In a simulation model of an evolving population of asexually replicating RNA molecules, initially deleterious mutations accumulated at rates nearly equal to that of initially beneficial mutations, without impeding evolutionary progress. As the mutation rate was increased within a moderate range, deleterious mutation accumulation and mean fitness improvement both increased. The fixation rates were higher than predicted by many population-genetic models. This seemingly paradoxical result was resolved in part by the observation that, during the time to fixation, the selection coefficient (s) of initially deleterious mutations reversed to confer a selective advantage. Significantly, more than half of the fixations of initially deleterious mutations involved fitness reversals. These fitness reversals had a substantial effect on the total fitness of the genome and thus contributed to its success in the population. Despite the relative importance of fitness reversals, however, the probabilities of fixation for both initially beneficial and initially deleterious mutations were exceedingly small (on the order of 10(-5) of all mutations).
PLoS Computational Biology 11/2006; 2(10):e141. · 5.22 Impact Factor
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ABSTRACT: Beneficial mutations are the driving force of evolution by natural selection. Yet, relatively little is known about the distribution of the fitness effects of beneficial mutations in populations. Recent work of Gillespie and Orr suggested some of the first generalizations for the distributions of beneficial fitness effects and, surprisingly, they depend only weakly on biological details. In particular, the theory suggests that beneficial mutations obey an exponential distribution of fitness effects, with the same exponential parameter across different regions of genotype space, provided only that few possible beneficial mutations are available to that genotype. Here we tested this hypothesis with a quasi-empirical model of RNA evolution in which fitness is based on the secondary structures of molecules and their thermodynamic stabilities. The fitnesses of randomly selected genotypes appeared to follow a Gumbel-type distribution and thus conform to a basic assumption of adaptation theory. However, the observed distributions of beneficial fitness effects conflict with specific predictions of the theory. In particular, the distributions of beneficial fitness effects appeared exponential only when the vast majority of small-effect beneficial mutations were ignored. Additionally, the distribution of beneficial fitness effects varied with the fitness of the parent genotype. We believe that correlation of the fitness values among similar genotypes is likely the cause of the departure from the predictions of recent adaptation theory. Although in conflict with the current theory, these results suggest that more complex statistical generalizations about beneficial mutations may be possible.
Genetics 09/2005; 170(4):1449-57. · 4.01 Impact Factor
