Autism spectrum disorder (ASD) is a group of life-long neurodevelopmental disorders affecting 1.5% of the general population. The present study aimed to evaluate the psychiatric history of a group of ...adults who received the first diagnosis of ASD in two Italian university centers. Diagnoses of ASD were confirmed by a team of psychiatrists with wide expertise in the field, after the administration of standardized tools (i.e., ADOS-2, ADI-R). The sample comprised 161 participants, of which 114 (79.5%) were males. The median age of diagnosis was 23 years (range 18–55), with a median IQ of 100 (range 30–145). The first evaluation by a mental health professional was performed at a median age of 13 years, with a gap of 11 years between the first evaluation and the diagnosis of ASD. 33.5% of participants had never received a psychiatric diagnosis, while the rest of the sample had received one or more diagnoses different from ASD. The most common past diagnoses were intellectual disability, psychoses, personality disorders, and depression. Sex differences were detected in the age of diagnosis and ADOS-2 scores. Our results provide important information for both child and adult psychiatrists. Given the prevalence of autism and the high rates of co-occurrent psychiatric conditions, it is important for clinicians to consider ASD in the differential diagnostic process.
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DOBA, EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, IZUM, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UILJ, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
The nosology of the psychosis high-risk state is controversial. Traditionally conceived as an 'at risk' state for the development of psychotic disorders, it is also conceptualised as a clinical ...syndrome associated with functional impairment.
To investigate meta-analytically the functional status of patients at high clinical risk for psychosis and its association with longitudinal outcomes.
Three meta-analyses compared level of functioning (n = 3012) and quality of life (QoL) (n = 945) between a high-risk group, a healthy control group and group with psychosis, and baseline functioning in people in the high-risk group who did or did not have a transition to psychosis at follow-up (n = 654).
People at high risk had a large impairment in functioning (P<0.001) and worse QoL (P = 0.001) than the healthy control group, but only small to moderately better functioning (P = 0.012) and similar QoL (P = 0.958) compared with the psychosis group. Among the high-risk group, those who did not develop psychosis reported better functioning (P = 0.001) than those who did.
Our results indicate that the high-risk state is characterised by consistent and large impairments of functioning and reduction in QoL similar to those in other coded psychiatric disorders.
Abstract A large array of studies has investigated peripheral oxytocin (OT) and vasopressin (ADH) as potential biomarkers of psychiatric disorders, with highly conflicting and heterogenous findings. ...We searched Web of KnowledgeSM and Scopus® for English original articles investigating OT and/or ADH levels in different biological fluids (plasma/serum, saliva, urine and cerebrospinal fluid) across several psychiatric disorders. Sixty-four studies were included. We conducted 19 preliminary meta-analyses addressing OT alterations in plasma/serum, saliva, urine and cerebrospinal fluid of 7 psychiatric disorders and ADH alterations in plasma/serum, saliva, urine and cerebrospinal fluid of 6 psychiatric disorders compared to controls. Hedge's g was used as effect size measure, together with heterogeneity analyses, test of publication biases and quality control. None of them (except serum OT in anorexia nervosa) revealed significant differences. There is no convincing evidence that peripheral ADH or OT might be reliable biomarkers in psychiatric disorders. However, the lack of significant results was associated with high methodological heterogeneity, low quality of the studies, small sample size, and scarce reliability of the methods used in previous studies, which need to be validated and standardized.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
The usefulness of current psychiatric classification, which is based on ICD/DSM categorical diagnoses, remains questionable. A promising alternative has been put forward as the “transdiagnostic” ...approach. This is expected to cut across existing categorical diagnoses and go beyond them, to improve the way we classify and treat mental disorders. This systematic review explores whether self‐defining transdiagnostic research meets such high expectations. A multi‐step Web of Science literature search was performed according to an a priori protocol, to identify all studies that used the word “transdiagnostic” in their title, up to May 5, 2018. Empirical variables which indexed core characteristics were extracted, complemented by a bibliometric and conceptual analysis. A total of 111 studies were included. Most studies were investigating interventions, followed by cognition and psychological processes, and neuroscientific topics. Their samples ranged from 15 to 91,199 (median 148) participants, with a mean age from 10 to more than 60 (median 33) years. There were several methodological inconsistencies relating to the definition of the gold standard (DSM/ICD diagnoses), of the outcome measures and of the transdiagnostic approach. The quality of the studies was generally low and only a few findings were externally replicated. The majority of studies tested transdiagnostic features cutting across different diagnoses, and only a few tested new classification systems beyond the existing diagnoses. About one fifth of the studies were not transdiagnostic at all, because they investigated symptoms and not disorders, a single disorder, or because there was no diagnostic information. The bibliometric analysis revealed that transdiagnostic research largely restricted its focus to anxiety and depressive disorders. The conceptual analysis showed that transdiagnostic research is grounded more on rediscoveries than on true innovations, and that it is affected by some conceptual biases. To date, transdiagnostic approaches have not delivered a credible paradigm shift that can impact classification and clinical care. Practical “TRANSD”iagnostic recommendations are proposed here to guide future research in this field.
Prenatal and perinatal insults are implicated in the aetiopathogenesis of psychotic disorders but the consistency and magnitude of their associations with psychosis have not been updated for nearly ...two decades. The aim of this systematic review and meta-analysis was to provide a comprehensive and up-to-date synthesis of the evidence on the association between prenatal or perinatal risk and protective factors and psychotic disorders.
In this systematic review and meta-analysis, we searched the Web of Science database for articles published up to July 20, 2019. We identified cohort and case-control studies examining the association (odds ratio OR) between prenatal and perinatal factors and any International Classification of Diseases (ICD) or Diagnostic and Statistical Manual of Mental Disorders (DSM) non-organic psychotic disorder with a healthy comparison group. Other inclusion criteria were enough data available to do the analyses, and non-overlapping datasets. We excluded reviews, meta-analyses, abstracts or conference proceedings, and articles with overlapping datasets. Data were extracted according to EQUATOR and PRISMA guidelines. Extracted variables included first author, publication year, study type, sample size, type of psychotic diagnosis (non-affective psychoses or schizophrenia-spectrum disorders, affective psychoses) and diagnostic instrument (DSM or ICD and version), the risk or protective factor, and measure of association (primary outcome). We did random-effects pairwise meta-analyses, Q statistics, I
index, sensitivity analyses, meta-regressions, and assessed study quality and publication bias. The study protocol was registered at PROSPERO, CRD42017079261.
152 studies relating to 98 risk or protective factors were eligible for analysis. Significant risk factors were: maternal age younger than 20 years (OR 1·17) and 30-34 years (OR 1·05); paternal age younger than 20 years (OR 1·31) and older than 35 years (OR 1·28); any maternal (OR 4·60) or paternal (OR 2·73) psychopathology; maternal psychosis (OR 7·61) and affective disorder (OR 2·26); three or more pregnancies (OR 1·30); herpes simplex 2 (OR 1·35); maternal infections not otherwise specified (NOS; OR 1·27); suboptimal number of antenatal visits (OR 1·83); winter (OR 1·05) and winter to spring (OR 1·05) season of birth in the northern hemisphere; maternal stress NOS (OR 2·40); famine (OR 1·61); any famine or nutritional deficits in pregnancy (OR 1·40); maternal hypertension (OR 1·40); hypoxia (OR 1·63); ruptured (OR 1·86) and premature rupture (OR 2·29) of membranes; polyhydramnios (OR 3·05); definite obstetric complications NOS (OR 1·83); birthweights of less than 2000 g (OR 1·84), less than 2500 g (OR 1·53), or 2500-2999 g (OR 1·23); birth length less than 49 cm (OR 1·17); small for gestational age (OR 1·40); premature birth (OR 1·35), and congenital malformations (OR 2·35). Significant protective factors were maternal ages 20-24 years (OR 0·93) and 25-29 years (OR 0·92), nulliparity (OR 0·91), and birthweights 3500-3999 g (OR 0·90) or more than 4000 g (OR 0·86). The results were corrected for publication biases; sensitivity and meta-regression analyses confirmed the robustness of these findings for most factors.
Several prenatal and perinatal factors are associated with the later onset of psychosis. The updated knowledge emerging from this study could refine understanding of psychosis pathogenesis, enhance multivariable risk prediction, and inform preventive strategies.
None.
Discriminating subjects at clinical high risk (CHR) for psychosis who will develop psychosis from those who will not is a prerequisite for preventive treatments. However, it is not yet possible to ...make any personalized prediction of psychosis onset relying only on the initial clinical baseline assessment. Here, we first present a systematic review of prognostic accuracy parameters of predictive modeling studies using clinical, biological, neurocognitive, environmental, and combinations of predictors. In a second step, we performed statistical simulations to test different probabilistic sequential 3-stage testing strategies aimed at improving prognostic accuracy on top of the clinical baseline assessment. The systematic review revealed that the best environmental predictive model yielded a modest positive predictive value (PPV) (63%). Conversely, the best predictive models in other domains (clinical, biological, neurocognitive, and combined models) yielded PPVs of above 82%. Using only data from validated models, 3-stage simulations showed that the highest PPV was achieved by sequentially using a combined (clinical + electroencephalography), then structural magnetic resonance imaging and then a blood markers model. Specifically, PPV was estimated to be 98% (number needed to treat, NNT = 2) for an individual with 3 positive sequential tests, 71%-82% (NNT = 3) with 2 positive tests, 12%-21% (NNT = 11-18) with 1 positive test, and 1% (NNT = 219) for an individual with no positive tests. This work suggests that sequentially testing CHR subjects with predictive models across multiple domains may substantially improve psychosis prediction following the initial CHR assessment. Multistage sequential testing may allow individual risk stratification of CHR individuals and optimize the prediction of psychosis.
Diagnosing autism spectrum disorder (ASD) in adulthood often represents a challenge in clinical practice. The aim of the present study was to evaluate the sensitivity and specificity of the ADOS and ...ADI-R in diagnosing ASD in adults. 113 subjects with an IQ of 70 or above were assessed through an extensive clinical evaluation. The ADOS-2 Module 4 and the ADI-R were separately administered by staff members blind to clinical judgment. Our results cautiously confirm the accuracy of ADOS-2 Module 4, while suggest that ADI-R might not be reliable in adults without intellectual disability. Clinicians’ training and experience remains of primary importance while assessing adults who could potentially belong to the autism spectrum.
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DOBA, EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, IZUM, KILJ, KISLJ, MFDPS, NLZOH, NUK, OBVAL, ODKLJ, OILJ, PILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UILJ, UKNU, UL, UM, UPUK, VKSCE, VSZLJ, ZAGLJ
The number of trials aimed at evaluating treatments for autism spectrum disorder has been increasing progressively. However, it is not clear which outcome measures should be used to assess their ...efficacy, especially for treatments which target core symptoms. The present review aimed to provide a comprehensive overview regarding the outcome measures used in clinical trials for people with autism spectrum disorder. We systematically searched the Web of KnowledgeSM database between 1980 and 2016 to identify published controlled trials investigating the efficacy of interventions in autism spectrum disorder. We included 406 trials in the final database, from which a total of 327 outcome measures were identified. Only seven scales were used in more than 5% of the studies, among which only three measured core symptoms (Autism Diagnostic Observation Schedule, Childhood Autism Rating Scale, and Social Responsiveness Scale). Of note, 69% of the tools were used in the literature only once. Our systematic review has shown that the evaluation of efficacy in intervention trials for autism spectrum disorder relies on heterogeneous and often non-specific tools for this condition. The fragmentation of tools may significantly hamper the comparisons between studies and thus the discovery of effective treatments for autism spectrum disorder. Greater consensus regarding the choice of these measures should be reached.
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NUK, OILJ, SAZU, UKNU, UL, UM, UPUK
•From rest to task, GSCORR reduces in sensory but increases in associative areas.•Reallocation of functional resources from sensory to associative regions at task.•Two distinct clusters of areas are ...recruited during GO and STOP trials.•GSCORR correlates with deactivation rather than activation.•GSCORR, activation and deactivation reflect distinct neurofunctional processes.
The dynamics of global, state-dependent reconfigurations in brain connectivity are yet unclear. We aimed at assessing reconfigurations of the global signal correlation coefficient (GSCORR), a measure of the connectivity between each voxel timeseries and the global signal, from resting-state to a stop-signal task. The secondary aim was to assess the relationship between GSCORR and blood-oxygen-level-dependent (BOLD) activations or deactivation across three different trial-conditions (GO, STOP-correct, and STOP-incorrect).
As primary analysis we computed whole-brain, voxel-wise GSCORR during resting-state (GSCORR-rest) and stop-signal task (GSCORR-task) in 107 healthy subjects aged 21–50, deriving GSCORR-shift as GSCORR-task minus GSCORR-rest. GSCORR-tr and trGSCORR-shift were also computed on the task residual time series to quantify the impact of the task-related activity during the trials. To test the secondary aim, brain regions were firstly divided in one cluster showing significant task-related activation and one showing significant deactivation across the three trial conditions. Then, correlations between GSCORR-rest/task/shift and activation/deactivation in the two clusters were computed. As sensitivity analysis, GSCORR-shift was computed on the same sample after performing a global signal regression and GSCORR-rest/task/shift were correlated with the task performance.
Sensory and temporo-parietal regions exhibited a negative GSCORR-shift. Conversely, associative regions (ie. left lingual gyrus, bilateral dorsal posterior cingulate gyrus, cerebellum areas, thalamus, posterolateral parietal cortex) displayed a positive GSCORR-shift (FDR-corrected p < 0.05). GSCORR-shift showed similar patterns to trGSCORR-shift (magnitude increased) and after global signal regression (magnitude decreased). Concerning BOLD changes, Brodmann area 6 and inferior parietal lobule showed activation, while posterior parietal lobule, cuneus, precuneus, middle frontal gyrus showed deactivation (FDR-corrected p < 0.05). No correlations were found between GSCORR-rest/task/shift and beta-coefficients in the activation cluster, although negative correlations were observed between GSCORR-task and GO/STOP-correct deactivation (Pearson rho=-0.299/-0.273; Bonferroni-p < 0.05). Weak associations between GSCORR and task performance were observed (uncorrected p < 0.05).
GSCORR state-dependent reconfiguration indicates a reallocation of functional resources to associative areas during stop-signal task. GSCORR, activation and deactivation may represent distinct proxies of brain states with specific neurofunctional relevance.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Attention-Deficit/Hyperactivity Disorder (ADHD) comprises disturbances in attention, emotional regulation, and reward-related processes. In spite of the active efforts in researching neurofunctional ...correlates of these symptoms, how the activity of subcortical regions—such as basal ganglia—is related to ADHD has yet to be clarified. More specifically, how age may influence the critical changes observed in functional dynamics from childhood to adulthood remains relatively unexplored. We hence selected five core subcortical regions (amygdala, caudate, putamen, pallidum and hippocampus) as regions of interest from the previous literature, measuring their whole-brain voxel-wise rsFC in a sample of 95 ADHD and 90 neurotypical children and adolescents aged from 7 to 18. The only subcortical structure showing significant differences in rsFC was the caudate nucleus. Specifically, we measured increased rsFC with anterior cingulate and right insula, two mesolimbic regions pertaining to the Salience Network. The degree of hyper-rsFC positively correlated with ADHD symptomatology, and showed different patterns of evolution in ADHD vs neurotypical subjects. Finally, the rsFC scores allowed a fair discrimination of the ADHD group (Area Under the Curve ≥ 0.7). These findings shed further light on the fundamental role covered by subcortical structures in ADHD pathogenesis and neurodevelopment, providing new evidence to fill the gap between neurofunctional and clinical expressions of ADHD.
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DOBA, EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, IZUM, KILJ, KISLJ, MFDPS, NLZOH, NUK, ODKLJ, OILJ, PILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, SIK, UILJ, UKNU, UL, UM, UPUK, VKSCE, VSZLJ, ZAGLJ
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