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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.
To develop latent classes of exposure to traumatic experiences before the age of 13 years in an urban community sample and to use these latent classes to predict the development of negative behavioral outcomes in adolescence and young adulthood.
A total of 1815 participants in an epidemiologically based, randomized field trial as children completed comprehensive psychiatric assessments as young adults. Reported experiences of nine traumatic experiences before age 13 years were used in a latent class analysis to create latent profiles of traumatic experiences. Latent classes were used to predict psychiatric outcomes at age ⩾13 years, criminal convictions, physical health problems and traumatic experiences reported in young adulthood.
Three latent classes of childhood traumatic experiences were supported by the data. One class (8% of sample), primarily female, was characterized by experiences of sexual assault and reported significantly higher rates of a range of psychiatric outcomes by young adulthood. Another class (8%), primarily male, was characterized by experiences of violence exposure and reported higher levels of antisocial personality disorder and post-traumatic stress. The final class (84%) reported low levels of childhood traumatic experiences. Parental psychopathology was related to membership in the sexual assault group.
Classes of childhood traumatic experiences predict specific psychiatric and behavioral outcomes in adolescence and young adulthood. The long-term adverse effects of childhood traumas are primarily concentrated in victims of sexual and non-sexual violence. Gender emerged as a key covariate in the classes of trauma exposure and outcomes.
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.
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.
The sensitivity of iron-based LRO alloys to strain rate at elevated temperatures was investigated. The tensile results indicate that the iron-based LRO alloys exhibit a positive temperature dependence of yield behavior, but are insensitive to variations in strain rate between 10-5 and 100 sec-1. These observations, along with SEM and TEM results, suggest that previous proposed diffusion-controlled mechanisms are not responsible for the increase in yield strength with increasing temperature.
A new technique for producing hollow shell laser fusion fuel capsules was developed that starts with a depolymerizable mandrel. In this technique we use poly(alpha-methylstyrene) (PAMS) beads or shells as mandrels which are overcoated with plasma polymer. The PAMS mandrel is thermally depolymerized to gas phase monomer, which diffuses through the permeable and thermally more stable plasma polymer coating, leaving a hollow shell. We have developed methods for controlling the size of the PAMS mandrel by either grinding to make smaller sizes or melt sintering to form larger mandrels. Sphericity and surface finish are improved by heating the PAMS mandrels in hot water using a surfactant to prevent aggregation. Using this technique we have made shells from 200 μm to 4 mm diameter with 15 to 100 μm wall thickness having sphericity better than 2 μm and local surface finish better than 10 nm RMS.
We present a summary of the techniques used to produce hollow plastic microshells from solid polymer granules using drop tower techniques. Unlike solution drop tower techniques, the use of these granules allows one to produce good quality shells with diameters of 1 to 1.5 mm. The reasons for hollow plastic shell diameter limitations are discussed, and based on these studies we present a new drop tower furnace concept we call a ballistic furnace that has been designed to produce large (2 to 3 mm) polystyrene shells. The characteristics of the individual components such as the pellet injector and the fast cooling system are given.
To maintain a constant growth rate in the absence of convection it is necessary to program down the temperature. Trial and error numerical computations were performed to find the first approximation for the required isothermal dissolution period, linear ramp; and polynomial temperature variation period. The linear ramp rate was limited by the specified maximum temperature gradient. The isothermal dissolution turned out to be unnecessary. The linear ramp had to be stopped before the polynomial period was begun to avoid overshooting the specified maximum growth rate. After a few hours the temperature profile approached steady state behavior.
A total of 12902 neonatal samples collected on absorbent paper for routine metabolic screening were tested anonymously for antibodies to toxoplasma. Seroprevalence varied from 19.5% in inner London, to 11.6% in suburban London, and 7.6% in non-metropolitan districts. Much of this variation appeared to be associated with the proportions of livebirths in each district to women born outside the UK. However, additional geographical variation remained and seroprevalence in UK-born women was estimated to be 12.7% in inner London, 7.5% in suburban London, and 5.5% in non-metropolitan areas. These estimates are considerably lower than any previously reported in antenatal sera in the UK. The wide geographical variation highlights a need for further research to determine the relative importance of different routes of transmission.
Insular breeding seabirds are likely to be particularly vulnerable to introduced mammalian predators because they often lack behavioural, morphological and life-history defenses against predation. We studied the life-history of the black-vented shearwater (Puffinus opisthomelas) on Natividad Island, Baja California Sur, Mexico, to examine its vulnerability to introduced feral cats. Using an allometric equation, we estimated that feral cats consumed 328 g of food day-1 to satisfy their nutritional requirements. We used stable isotope analysis of cat scat to estimate that 90% of the cats' diet was composed of shearwaters. Using data from our focal species and from the closely related manx shearwater (Puffinus puffinus), we created a demographic model to evaluate the effects of cat population size on the annual growth rate (λ) of the shearwater. The annual growth rate for black-vented shearwaters was estimated to be 1.006 in the absence of cat predation. With predation, we estimated that annual growth rate declined approximately 5% for every 20 cats in a population of 150,000 birds. Persistence times of bird colonies decreased both with an increase in the size of the feral cat population and with a decrease in the size of the initial bird population.
Data from 5270 lactation records of 1380 cows sired by 132 bulls and recorded from 1962 to 1977 were analysed. Statistical analyses, using least squares and maximum likelihood methods, showed significant effects for genetic group, age of cow, month and year of calving, and lactation length. Overall mean milk yield was 2780 kg (CV = 0·31) with mean lactation length of 281 days. Maximum production occurred in the fifth lactation (104 or 105 months of age at calving) with a yield of 1·3 times that of the first lactation. Repeatability estimated by intraclass correlation was 0·40 (s.e. 0·03). Heritability estimated from paternal half-sib correlation was 0·16 (s.e. 0·06). Overall results were very similar to those obtained from research with European breeds in temperate areas.
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