Does case management improve outcomes for people with schizophrenia?

The Australian and New Zealand clinical practice guidelines recommend intensive case management for people with first-episode psychosis or an acute relapse of schizophrenia. Often initiated following discharge from hospital or transfer from community-based acute care, case management is a collaborative, community-based program designed to ensure people receive quality health care and integrated support services. Case management may provide substantial benefits for people suffering severe mental illnesses like schizophrenia, however, before case management services are made universally available, more work needs to be done to determine when, and for whom, these services are most effective

Are our policies and laws leading to treatment delays for people with schizophrenia?

Under Australian mental health laws, people with schizophrenia can only be involuntarily committed to a mental health facility if they are assessed and it is determined that their illness is making them dangerous to themselves or others. To determine whether they are to undergo involuntary treatment, mental health workers must assess people against an ‘Obligatory Dangerousness Criterion’. This criterion is an advance on methods used prior to the mid-1970s, when many countries authorised involuntary commitment to a mental health facility on medical certification alone, without court approval or any proof of an emergency situation. An Obligatory Dangerousness Criterion is now widely used in Australia, the USA, and some areas of Canada and Europe as the means by which patients are assessed for the appropriateness of involuntary (compulsory) treatment. There is no doubt the policy underpinning its use was well intentioned; an Obligatory Dangerousness Criterion was originally developed in an attempt to bett er balance the rights of the mentally ill with the need to protect the public. However, over time some experts have begun to raise questions about the utility of this criterion, suggesting that it sometimes means patients don’t get access to necessary treatment as quickly as they should

Multivariate neuroanatomical classification of cognitive subtypes in schizophrenia: A support vector machine learning approach

AbstractHeterogeneity in the structural brain abnormalities associated with schizophrenia has made identification of reliable neuroanatomical markers of the disease difficult. The use of more homogenous clinical phenotypes may improve the accuracy of predicting psychotic disorder/s on the basis of observable brain disturbances. Here we investigate the utility of cognitive subtypes of schizophrenia – ‘cognitive deficit’ and ‘cognitively spared’ – in determining whether multivariate patterns of volumetric brain differences can accurately discriminate these clinical subtypes from healthy controls, and from each other. We applied support vector machine classification to grey- and white-matter volume data from 126 schizophrenia patients previously allocated to the cognitive spared subtype, 74 cognitive deficit schizophrenia patients, and 134 healthy controls. Using this method, cognitive subtypes were distinguished from healthy controls with up to 72% accuracy. Cross-validation analyses between subtypes achieved an accuracy of 71%, suggesting that some common neuroanatomical patterns distinguish both subtypes from healthy controls. Notably, cognitive subtypes were best distinguished from one another when the sample was stratified by sex prior to classification analysis: cognitive subtype classification accuracy was relatively low (<60%) without stratification, and increased to 83% for females with sex stratification. Distinct neuroanatomical patterns predicted cognitive subtype status in each sex: sex-specific multivariate patterns did not predict cognitive subtype status in the other sex above chance, and weight map analyses demonstrated negative correlations between the spatial patterns of weights underlying classification for each sex. These results suggest that in typical mixed-sex samples of schizophrenia patients, the volumetric brain differences between cognitive subtypes are relatively minor in contrast to the large common disease-associated changes. Volumetric differences that distinguish between cognitive subtypes on a case-by-case basis appear to occur in a sex-specific manner that is consistent with previous evidence of disrupted relationships between brain structure and cognition in male, but not female, schizophrenia patients. Consideration of sex-specific differences in brain organization is thus likely to assist future attempts to distinguish subgroups of schizophrenia patients on the basis of neuroanatomical features

Impact of long-range correlations on trend detection in total ozone

Total ozone trends are typically studied using linear regression models that assume a first-order autoregression of the residuals [so-called AR(1) models]. We consider total ozone time series over 60°S–60°N from 1979 to 2005 and show that most latitude bands exhibit long-range correlated (LRC) behavior, meaning that ozone autocorrelation functions decay by a power law rather than exponentially as in AR(1). At such latitudes the uncertainties of total ozone trends are greater than those obtained from AR(1) models and the expected time required to detect ozone recovery correspondingly longer. We find no evidence of LRC behavior in southern middle-and high-subpolar latitudes (45°–60°S), where the long-term ozone decline attributable to anthropogenic chlorine is the greatest. We thus confirm an earlier prediction based on an AR(1) analysis that this region (especially the highest latitudes, and especially the South Atlantic) is the optimal location for the detection of ozone recovery, with a statistically significant ozone increase attributable to chlorine likely to be detectable by the end of the next decade. In northern middle and high latitudes, on the other hand, there is clear evidence of LRC behavior. This increases the uncertainties on the long-term trend attributable to anthropogenic chlorine by about a factor of 1.5 and lengthens the expected time to detect ozone recovery by a similar amount (from ∼2030 to ∼2045). If the long-term changes in ozone are instead fit by a piecewise-linear trend rather than by stratospheric chlorine loading, then the strong decrease of northern middle- and high-latitude ozone during the first half of the 1990s and its subsequent increase in the second half of the 1990s projects more strongly on the trend and makes a smaller contribution to the noise. This both increases the trend and weakens the LRC behavior at these latitudes, to the extent that ozone recovery (according to this model, and in the sense of a statistically significant ozone increase) is already on the verge of being detected. The implications of this rather controversial interpretation are discussed

The Early Growth Genetics (EGG) and EArly Genetics and Lifecourse Epidemiology (EAGLE) consortia : design, results and future prospects

The impact of many unfavorable childhood traits or diseases, such as low birth weight and mental disorders, is not limited to childhood and adolescence, as they are also associated with poor outcomes in adulthood, such as cardiovascular disease. Insight into the genetic etiology of childhood and adolescent traits and disorders may therefore provide new perspectives, not only on how to improve wellbeing during childhood, but also how to prevent later adverse outcomes. To achieve the sample sizes required for genetic research, the Early Growth Genetics (EGG) and EArly Genetics and Lifecourse Epidemiology (EAGLE) consortia were established. The majority of the participating cohorts are longitudinal population-based samples, but other cohorts with data on early childhood phenotypes are also involved. Cohorts often have a broad focus and collect(ed) data on various somatic and psychiatric traits as well as environmental factors. Genetic variants have been successfully identified for multiple traits, for example, birth weight, atopic dermatitis, childhood BMI, allergic sensitization, and pubertal growth. Furthermore, the results have shown that genetic factors also partly underlie the association with adult traits. As sample sizes are still increasing, it is expected that future analyses will identify additional variants. This, in combination with the development of innovative statistical methods, will provide detailed insight on the mechanisms underlying the transition from childhood to adult disorders. Both consortia welcome new collaborations. Policies and contact details are available from the corresponding authors of this manuscript and/or the consortium websites.Peer reviewe

Identifying neuroanatomical subtypes of psychosis

Background: The quantity and heterogeneity of structural magnetic resonance imaging(sMRI) studies in schizophrenia present a challenge to their meaningful interpretation.This thesis sought to synthesise the available literature on neuroanatomical alterations inpeople with schizophrenia, and explore brain volume differences among subgroups ofschizophrenia defined on the basis of cognitive ability. The thesis also investigatedwhether analogous cognitive subgroups extending across the psychosis-mood spectrum(including bipolar-I disorder) may be differentiated by brain volume.Methods: Meta-review of the existing sMRI literature was conducted using electronicdatabases. Random-effects meta-analysis was used to statistically collate studiesreporting insular cortex volume in schizophrenia. Subsequent analysis of structuralimaging data from two separate samples explored differences in grey and white mattervolume among cognitive subtypes of psychotic disorder relative to controls. Subgroupswithin a large schizophrenia sample were allocated to cognitively spared (CS;&#894; N=157)or cognitively deficit (CD;&#894; N=106), compared to healthy controls (N=181).Subsequently, a mixed sample of schizophrenia and bipolar-I disorder was stratifiedinto executively spared (ES;&#894; N=38) and executively deficit subgroups (ED;&#894; N=32) toassess differences in grey and white matter volume.Results: Critical synthesis of the sMRI literature identified limited high qualityevidence for widespread regional grey and white matter aberration in schizophrenia.Specific assessment of insular cortex identified moderate volume reductions, with largeheterogeneity not explained by age, sex, illness duration, medication, whole brainvolume, or hemisphere. Assessment of cognitive subtypes of schizophrenia identifieddistinct neuroanatomical profiles of each group relative to controls, with the cognitively impaired group showing more diffuse brain volume reductions. Assessment of thediagnostic specificity of these findings identified no differences between groups definedby bipolar-I disorder and schizophrenia diagnoses, but similarly diffuse volume deficitsacross the psychosis-mood spectrum in the executively impaired subgroup.Conclusions: Stratification according to intermediate cognitive phenotypes identifiedtrans-diagnostic subtypes that exhibited markedly discrepant brain aberrations andclinical features. These findings provide insight into potential neuropathologicalregions, and suggest the existence of discrete illness types who may be associated withdivergent neurodevelopmental or genetic vulnerabilities

A systematic meta-review grading the evidence for non-genetic risk factors and putative antecedents of schizophrenia

Introduction Identifying the relative strength of evidence associated with non-genetic risk factors and putative antecedents of schizophrenia will guide research and may inform the design of early detection and intervention strategies. Aims To present and quality assess current evidence for non-genetic risk factors and putative antecedents derived from well-conducted systematic reviews that report pooled data. Method Medline, Embase, CINAHL, Current Contents, and PsycINFO databases were searched systematically, and supplemented by hand searching. Review reporting quality was assessed using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) checklist, review methodology was assessed using the Assessment of Multiple Systematic Reviews (AMSTAR) checklist, and evidence quality was assessed using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach. Results Twenty-four reviews met inclusion criteria. The risk factors with the highest quality evidence, reporting medium effect sizes, were advanced paternal age, obstetric complications, and cannabis use. The strongest evidence among the putative antecedents was identified for motor dysfunction and low IQ. Conclusions More research is required that applies sound methodological practices, taking into consideration specificity for schizophrenia and possible confounding factors, to robustly identify the non-genetic risk factors and putative antecedents of schizophrenia

Systematic meta-review and quality assessment of the structural brain alterations in schizophrenia

Background The large quantity of systematic reviews of magnetic resonance imaging studies in schizophrenia challenges their meaningful interpretation. This meta-review synthesises the available information from systematic reviews of structural alteration in both chronic and first-episode schizophrenia. Methods Systematic reviews were identified using electronic databases. Review methodological quality was assessed according to the Assessment of Multiple Systematic Reviews checklist. Data were extracted in duplicate and quality assessed for consistency and precision, guided by Grading of Recommendations Assessment, Development and Evaluation recommendations. Results Integration of volumetric and voxel-based estimates allowed critical assessment of the magnitude and location of anatomical differences. There is evidence for grey matter reductions of anterior cingulate, frontal (particularly medial and inferior) and temporal lobes, hippocampus/amygdala, thalamus, and insula that may be magnified over time. Other regional alterations appear specific to illness stage or medication status. Conclusions There is limited high quality evidence supporting grey or white matter changes in schizophrenia, which has previously been obscured by a large volume of conflicting lower quality evidence

Meta-analysis of insula grey matter volume in schizophrenia

There is increasing interest in the insula as a key region of neuropathology in schizophrenia. Several voxel-based meta-analyses of magnetic resonance imaging (MRI) studies have highlighted insula grey matter deficits in people with schizophrenia. However, volumetric studies targeting insula grey matter volume, to date, do not give a clear picture of insula morphometry. We undertook the first systematic review with meta- analysis of studies examining insula volume in schizophrenia compared to healthy controls