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Introduction: Controversy exists in antiepileptic drug (AED) prophylaxis prescribing in patients with aneurysmal subarachnoid hemorrhage (SAH). We undertook the Use of Antiepileptic Drugs in Aneurysmal Subarachnoid Hemorrhage (ALIBI) study to identify factors associated with prescribing practices. Methods: A retrospective chart review of all consecutive patients requiring Level 1 care with aneurysmal SAH admitted between 2012 and 2014 to the intensive care unit at Toronto Western Hospital, Ontario, Canada, was conducted. Data were collected on clinical and imaging characteristics. Primary and secondary outcomes were AED prophylaxis and clinical seizure activity during hospitalization. Data were compared using chi-square or Mann–Whitney U-tests. Those variables found to be significant, or trending toward significance, on univariate analysis were fitted to multivariate regression. Results: Sixty-eight patients were included. Mean age was 62 ± 12.2, and 42.6% of patients were male. Of these, 21 patients (30.9%) received AED prophylactically, while 18 (26.5%) had reported seizures at some point during hospitalization. Female gender and presence of midline shift (MLS) were significantly associated or approached significance with AED prophylaxis in univariate analysis (p = 0.036 and p = 0.062, respectively). In multivariate analysis, only MLS was an independent predictor (odds ratio 5.09, p = 0.04). Conclusion: The presence of MLS was an independent predictor of seizure activity in patients with aneurysmal SAH. AED prophylaxis prescribing patterns seemed arbitrary and was not informed by identifiable clinical factors or true risk factors for seizure. A current lack of evidence guiding AED prescribing practice highlights the need for larger studies in this patient population.
“It seems to me, now,” reflected Troy Perry, four years after founding a successful new Protestant denomination, “that it must have been a matter of timing, and I think that it was fate, too! God chose me for my mission at a time when He knew the world would respond, once the need was made clear.” While the question of divine ordination is a bit outside the scholar's jurisdiction, the question of timing is a crucial one for historical inquiry, and Perry's remarks show an insightful awareness that the success of the Universal Fellowship of Metropolitan Community Churches (UFMCC) was due in large part to timing. As with any successful religious group, however, the seeds of the UFMCC germinated, sprouted, and grew as a result of a multitude of interconnected factors, including both external back-ground factors in American society at large and internal factors within the UFMCC itself. This article relates the history and early growth of the UFMCC to this constellation of factors in order to gain a clearer understanding of both the denomination itself and the social changes of which it was an integral part.
Solar five-minute oscillations of degree l = 3, 4, and 5 have been observed at Stanford, in the Doppler shift of the Fe 5124 line. The frequencies and amplitudes are in broad agreement with previous observations of modes with l ≤ 3, though we note that there are some systematic discrepancies between the results of different observers.
The solar oscillation with period near 160 min is found to be unique in a spectrum computed over the range of periods from about 71 to 278 min. Our best estimate of the period is 160.0095 ± 0.001 min, which is different from 160 min (1/9 of a day) by a highly significant amount. The width of the peak is approximately equal to the limiting resolution that can be obtained from an observation lasting 6 years, which suggests that the damping time of the oscillations is considerably longer than 6 years. A suggestion that this peak might be the result of a beating phenomenon between the five minute data averages and a solar oscillation with period near five minutes is shown to be incorrect by recomputing a portion of the spectrum using 15 s data averages.
A few recent observations of interplanetary fields and plasmas are discussed, including the evolution over several years of the longitudinal sector pattern, the corotating filamentary structure that exists within the sectors, guiding of solar cosmic rays along such magnetic filaments, a field-aligned thermal anisotropy of the plasma, and a small component of corotating plasma velocity observed at 1 AU. The solar wind plasma streaming past spacecraft near 1 AU contains a large amount of information about the detailed structure of the Sun.
Clinicians need guidance to address the heterogeneity of treatment responses of patients with major depressive disorder (MDD). While prediction schemes based on symptom clustering and biomarkers have so far not yielded results of sufficient strength to inform clinical decision-making, prediction schemes based on big data predictive analytic models might be more practically useful.
We review evidence suggesting that prediction equations based on symptoms and other easily-assessed clinical features found in previous research to predict MDD treatment outcomes might provide a foundation for developing predictive analytic clinical decision support models that could help clinicians select optimal (personalised) MDD treatments. These methods could also be useful in targeting patient subsamples for more expensive biomarker assessments.
Approximately two dozen baseline variables obtained from medical records or patient reports have been found repeatedly in MDD treatment trials to predict overall treatment outcomes (i.e., intervention v. control) or differential treatment outcomes (i.e., intervention A v. intervention B). Similar evidence has been found in observational studies of MDD persistence-severity. However, no treatment studies have yet attempted to develop treatment outcome equations using the full set of these predictors. Promising preliminary empirical results coupled with recent developments in statistical methodology suggest that models could be developed to provide useful clinical decision support in personalised treatment selection. These tools could also provide a strong foundation to increase statistical power in focused studies of biomarkers and MDD heterogeneity of treatment response in subsequent controlled trials.
Coordinated efforts are needed to develop a protocol for systematically collecting information about established predictors of heterogeneity of MDD treatment response in large observational treatment studies, applying and refining these models in subsequent pragmatic trials, carrying out pooled secondary analyses to extract the maximum amount of information from these coordinated studies, and using this information to focus future discovery efforts in the segment of the patient population in which continued uncertainty about treatment response exists.
In a 1-year survey at a university hospital we found that 20·6% (81/392) of patients with antibiotic associated diarrohea where positive for C. difficile. The most common PCR ribotypes were 012 (14·8%), 027 (12·3%), 046 (12·3%) and 014/020 (9·9). The incidence rate was 2·6 cases of C. difficile infection for every 1000 outpatients.
The large-scale structure of the solar magnetic field during the past five sunspot cycles (representing by implication a much longer interval of time) has been investigated using the polarity (toward or away from the Sun) of the interplanetary magnetic field as inferred from polar geomagnetic observations. The polarity of the interplanetary magnetic field has previously been shown to be closely related to the polarity (into or out of the Sun) of the large-scale solar magnetic field. It appears that a solar structure with four sectors per rotation persisted through the past five sunspot cycles, with a synodic rotation period near 27.0 days, and a small relative westward drift during the first half of each sunspot cycle and a relative eastward drift during the second half of each cycle. Superposed on this four-sector structure there is another structure with inward field polarity, a width in solar longitude of about 100° and a synodic rotation period of about 28 to 29 days. This 28.5 day structure is usually most prominent during a few years near sunspot maximum. Some preliminary comparisons of these observed solar structures with theoretical considerations are given.
The Sun as a magnetic star is described on the basis of recent work on solar magnetism. Observations at an arbitrary angle to the rotation axis would show a 22-year polar field variation and a 25–day equatorial sector variation. The sector variation would be similar to an oblique rotator with an angle of 90° between the magnetic and rotational axes.
The relation of solar active regions to the large-scale sector structure of the interplanetary field is discussed. In the winter of 1963–64 (observed by the satellite IMP-1) the plage density was greatest in the leading portion of the sectors and lesser in the trailing portion of the sectors. The boundaries of the sectors (places at which the direction of the interplanetary magnetic field changed from toward the Sun to away from the Sun, or vice versa) were remarkably free of plages. The very fact that since the first observations in 1962 the average interplanetary field has almost always had the property of being either toward the Sun or away from the Sun (along the Archimedean spiral angle) continuously for several days must be considered in the discussion of large-scale evolution of active regions. Using the observed interplanetary magnetic field at 1 AU and a set of reasonable assumptions the magnetic configuration in the ecliptic from 0·4 AU to 1·2 AU has been reconstructed. In at least one case a pattern emerges which appears to be related to the evolution of an active region from an early stage in which the magnetic lines closely couple the preceding and following halves of the region to a later stage in which the two halves of the region are more widely separated.
The solar sector structure consists of a boundary in the north-south direction such that on one side of the boundary the large-scale weak photospheric magnetic field is predominantly directed out of the Sun, and on the other side of the boundary this field is directed into the Sun. The region westward of a solar sector boundary tends to be unusually quiet and the region eastward of a solar sector boundary tends to be unusually active. This tendency is discussed in terms of flares, coronal enhancements, plage structure and geomagnetic response.
There is an opportunity for scaling up, optimizing, and controlling the process of production of nanoparticles due to their numerous diverse applications. We present a system for continuous, high rate production of nanoparticles, particularly those of carbon, using large volume thermal plasma based on a three-phase diverging electrode configuration. The goal of using this 3-phase plasma reactor is to have a plasma arc that is scalable, self-stabilizing, and low maintenance, with sufficient plasma volume to maximize residence time of feed materials for evaporation to atomic species. Plasma carrier gas, typically inert gas such as helium, is injected into the reactor allowing the vaporization of any feedstock due to plasma temperatures >5000 °C. Controlling plasma enthalpy, diffusion/temperature gradients and carbon feed rates allow the controlled growth of clusters leading to nanoparticles less than 100 nm. Once the desired size is achieved the gas stream is expanded to reduce the reaction rate and quenched by natural cooling to chamber walls or injection of a cooling gas stream, preferably of the same composition as plasma carrier gas. Recoverable yields in the nanoparticle-laden gas stream are then isolated by standard means (filtration, cyclone separation, electrostatic precipitation), and the plasma gas and unreacted feedstock are routed to the plasma reactor for recycling. Computational Fluid Dynamics (CFD) is employed to measure and predict fluid flow, energy/temperature, and other species distributions in the plasma process.
The first aim was to use confirmatory factor analysis (CFA) to test a hypothesis that two factors (internalizing and externalizing) account for lifetime co-morbid DSM-IV diagnoses among adults with bipolar I (BPI) disorder. The second aim was to use confirmatory latent class analysis (CLCA) to test the hypothesis that four clinical subtypes are detectible: pure BPI; BPI plus internalizing disorders only; BPI plus externalizing disorders only; and BPI plus internalizing and externalizing disorders.
A cohort of 699 multiplex BPI families was studied, ascertained and assessed (1998–2003) by the National Institute of Mental Health Genetics Initiative Bipolar Consortium: 1156 with BPI disorder (504 adult probands; 594 first-degree relatives; and 58 more distant relatives) and 563 first-degree relatives without BPI. Best-estimate consensus DSM-IV diagnoses were based on structured interviews, family history and medical records. MPLUS software was used for CFA and CLCA.
The two-factor CFA model fit the data very well, and could not be improved by adding or removing paths. The four-class CLCA model fit better than exploratory LCA models or post-hoc-modified CLCA models. The two factors and four classes were associated with distinctive clinical course and severity variables, adjusted for proband gender. Co-morbidity, especially more than one internalizing and/or externalizing disorder, was associated with a more severe and complicated course of illness. The four classes demonstrated significant familial aggregation, adjusted for gender and age of relatives.
The BPI two-factor and four-cluster hypotheses demonstrated substantial confirmatory support. These models may be useful for subtyping BPI disorders, predicting course of illness and refining the phenotype in genetic studies.
To examine cross-national patterns and correlates of lifetime and 12-month comorbid DSM-IV anxiety disorders among people with lifetime and 12-month DSM-IV major depressive disorder (MDD).
Nationally or regionally representative epidemiological interviews were administered to 74 045 adults in 27 surveys across 24 countries in the WHO World Mental Health (WMH) Surveys. DSM-IV MDD, a wide range of comorbid DSM-IV anxiety disorders, and a number of correlates were assessed with the WHO Composite International Diagnostic Interview (CIDI).
45.7% of respondents with lifetime MDD (32.0–46.5% inter-quartile range (IQR) across surveys) had one of more lifetime anxiety disorders. A slightly higher proportion of respondents with 12-month MDD had lifetime anxiety disorders (51.7%, 37.8–54.0% IQR) and only slightly lower proportions of respondents with 12-month MDD had 12-month anxiety disorders (41.6%, 29.9–47.2% IQR). Two-thirds (68%) of respondents with lifetime comorbid anxiety disorders and MDD reported an earlier age-of-onset (AOO) of their first anxiety disorder than their MDD, while 13.5% reported an earlier AOO of MDD and the remaining 18.5% reported the same AOO of both disorders. Women and previously married people had consistently elevated rates of lifetime and 12-month MDD as well as comorbid anxiety disorders. Consistently higher proportions of respondents with 12-month anxious than non-anxious MDD reported severe role impairment (64.4 v. 46.0%; χ21 = 187.0, p < 0.001) and suicide ideation (19.5 v. 8.9%; χ21 = 71.6, p < 0.001). Significantly more respondents with 12-month anxious than non-anxious MDD received treatment for their depression in the 12 months before interview, but this difference was more pronounced in high-income countries (68.8 v. 45.4%; χ21 = 108.8, p < 0.001) than low/middle-income countries (30.3 v. 20.6%; χ21 = 11.7, p < 0.001).
Patterns and correlates of comorbid DSM-IV anxiety disorders among people with DSM-IV MDD are similar across WMH countries. The narrow IQR of the proportion of respondents with temporally prior AOO of anxiety disorders than comorbid MDD (69.6–74.7%) is especially noteworthy. However, the fact that these proportions are not higher among respondents with 12-month than lifetime comorbidity means that temporal priority between lifetime anxiety disorders and MDD is not related to MDD persistence among people with anxious MDD. This, in turn, raises complex questions about the relative importance of temporally primary anxiety disorders as risk markers v. causal risk factors for subsequent MDD onset and persistence, including the possibility that anxiety disorders might primarily be risk markers for MDD onset and causal risk factors for MDD persistence.
State programs promoting their agricultural products have proliferated in response to increased consumer interest in locally grown foods. Tennessee, for example, currently has two state-funded programs promoting its agricultural products. This study examines the factors associated with participation by Tennessee fruit and vegetable farmers in those programs. The results suggest that farmer participation is associated with farm income, use of extension resources, and fresh produce sales. These results should be of interest to anyone attempting to increase producer participation in such programs.
Although variation in the long-term course of major depressive disorder (MDD) is not strongly predicted by existing symptom subtype distinctions, recent research suggests that prediction can be improved by using machine learning methods. However, it is not known whether these distinctions can be refined by added information about co-morbid conditions. The current report presents results on this question.
Data came from 8261 respondents with lifetime DSM-IV MDD in the World Health Organization (WHO) World Mental Health (WMH) Surveys. Outcomes included four retrospectively reported measures of persistence/severity of course (years in episode; years in chronic episodes; hospitalization for MDD; disability due to MDD). Machine learning methods (regression tree analysis; lasso, ridge and elastic net penalized regression) followed by k-means cluster analysis were used to augment previously detected subtypes with information about prior co-morbidity to predict these outcomes.
Predicted values were strongly correlated across outcomes. Cluster analysis of predicted values found three clusters with consistently high, intermediate or low values. The high-risk cluster (32.4% of cases) accounted for 56.6–72.9% of high persistence, high chronicity, hospitalization and disability. This high-risk cluster had both higher sensitivity and likelihood ratio positive (LR+; relative proportions of cases in the high-risk cluster versus other clusters having the adverse outcomes) than in a parallel analysis that excluded measures of co-morbidity as predictors.
Although the results using the retrospective data reported here suggest that useful MDD subtyping distinctions can be made with machine learning and clustering across multiple indicators of illness persistence/severity, replication with prospective data is needed to confirm this preliminary conclusion.
Methane (CH4) emissions by dairy cows vary with feed intake and diet composition. Even when fed on the same diet at the same intake, however, variation between cows in CH4 emissions can be substantial. The extent of variation in CH4 emissions among dairy cows on commercial farms is unknown, but developments in methodology now permit quantification of CH4 emissions by individual cows under commercial conditions. The aim of this research was to assess variation among cows in emissions of eructed CH4 during milking on commercial dairy farms. Enteric CH4 emissions from 1964 individual cows across 21 farms were measured for at least 7 days/cow using CH4 analysers at robotic milking stations. Cows were predominantly of Holstein Friesian breed and remained on the same feeding systems during sampling. Effects of explanatory variables on average CH4 emissions per individual cow were assessed by fitting a linear mixed model. Significant effects were found for week of lactation, daily milk yield and farm. The effect of milk yield on CH4 emissions varied among farms. Considerable variation in CH4 emissions was observed among cows after adjusting for fixed and random effects, with the CV ranging from 22% to 67% within farms. This study confirms that enteric CH4 emissions vary among cows on commercial farms, suggesting that there is considerable scope for selecting individual cows and management systems with reduced emissions.